
John Witte
Professor of Epidemiology and Population Health, of Biomedical Data Science and of Genetics
Bio
John is an internationally recognized expert in genetic epidemiology. In addition to his faculty positions, John is the Vice Chair of Epidemiology and Population Health and co-Leader of the Population Sciences program in the Stanford Cancer Institute. Before Stanford he was on the faculty at UC San Francisco and at Case Western Reserve University. John has received the Leadership Award from the International Genetic Epidemiology Society (highest award), and the Stephen B. Hulley Award for Excellence in Teaching. He teaches a genetic epidemiology course, has mentored over 50 graduate students and postdoctoral fellows, and has directed National Institutes of Health funded training programs in genetic epidemiology for over 20 years.
Academic Appointments
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Professor, Epidemiology and Population Health
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Professor, Department of Biomedical Data Science
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Professor, Genetics
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Member, Stanford Cancer Institute
Professional Education
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Post-doc, University of Southern California, Biostatistics (1995)
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PhD, University of California, Los Angeles, Epidemiology (1994)
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MS, University of California, Berkeley, Industrial Engineering & Operations Research (1988)
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BS, University of California, Santa Barbara, Mathematical Sciences (1986)
Current Research and Scholarly Interests
The Witte lab is a computational group developing and applying novel methods to decipher the mechanisms underlying complex diseases and traits. Recent research includes evaluating polygenic risk scores for trait prediction, investigating the shared genetic basis of cancer and other traits, and genetically adjusting biomarkers (e.g., prostate specific antigen) to improve disease screening.
2024-25 Courses
- Genetic Epidemiology
EPI 224, GENE 230 (Win) -
Independent Studies (4)
- Directed Reading and Research
BIOMEDIN 299 (Aut, Win, Spr, Sum) - Directed Reading in Epidemiology
EPI 299 (Aut, Win, Spr, Sum) - Graduate Research
EPI 399 (Aut, Win, Spr, Sum) - Undergraduate Research
EPI 199 (Aut, Win, Spr, Sum)
- Directed Reading and Research
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Prior Year Courses
2023-24 Courses
- Genetic Epidemiology
EPI 224, GENE 230 (Win)
2022-23 Courses
- Genetic Epidemiology
EPI 224, GENE 230 (Win)
2021-22 Courses
- Genetic Epidemiology
EPI 224 (Win)
- Genetic Epidemiology
Stanford Advisees
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Postdoctoral Faculty Sponsor
Martina Fu, Brenda Xiao -
Doctoral Dissertation Advisor (AC)
Karen Feng -
Master's Program Advisor
James Guo, Zoe Quake -
Doctoral Dissertation Co-Advisor (AC)
Jon Judd
All Publications
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SLCO1B1 Functional Variants, Bilirubin, Statin-Induced Myotoxicity, and Recent Sub-Saharan African Ancestry: A Precision Medicine Health Equity Study.
Clinical pharmacology and therapeutics
2025
Abstract
Statin pharmacogenetic implementation guidelines are derived from evidence of primarily Eurocentrically biased study populations. Functional SLCO1B1 variants that are rare in these study populations have not been equitably investigated and are thus missing from guidelines. The objective of this precision medicine health equity study was to determine the clinical validity of understudied candidate functional SLCO1B1 variants common in people with 1,000 Genomes sub-Saharan African superpopulation (1KG-AFR-like) genetic similarity. We conducted our analyses using the real-world evidence of participants from three large, electronic health record-linked biobanks. We used bilirubin levels (as an endogenous substrate of organic anion transporting polypeptide [OATP1B1] function) and severe statin-induced myotoxicity phenotypes. Loss-of-function splice variant rs77271279 (P=1.1*10-17) had the strongest association with elevated total bilirubin levels in Black participants (mean 84% AFR-like genetic similarity) followed by missense variant rs59502379 (P=7.4*10-12) then missense variant rs4149056 (P=6.0*10-5). In an exploratory subset of the Black study population who used statins (n=77 severe statin-induced myotoxicity cases), rs59502379 (odds ratio [OR]=2.85, 95% confidence interval [CI] 1.08-7.52), but not rs77271279 (OR=1.75, 95% CI 0.62-4.73) was associated with myotoxicity. Sensitivity analyses in participants with >5% AFR-like genetic similarity corroborated these findings. For white participants, rs77271279 and rs59502379 were rare precluding subsequent analyses. Our findings highlight the clinical relevance for understudied SLCO1B1 variants on pharmacogenetic testing panels with a potential immediate impact on reducing the risk of severe statin-induced myotoxicity primarily in Black patients, a group historically excluded from genomic research. Future studies require larger statin user study populations with less heterogeneity by statin type.
View details for DOI 10.1002/cpt.3624
View details for PubMedID 40047317
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Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves prediction across ancestry groups.
Nature genetics
2025
Abstract
We conducted a multiancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry, 58,236 African ancestry, 23,546 Hispanic/Latino and 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (P ≤ 5 × 10-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n = 95,768). Meta-analyzing discovery and replication (n = 392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our genome-wide polygenic risk scores ranged from 11.6% to 16.6% for European ancestry, 5.5% to 9.5% for African ancestry, 13.5% to 18.2% for Hispanic/Latino and 8.6% to 15.3% for Asian ancestry and decreased with increasing age. Midlife genetically adjusted PSA levels were more strongly associated with overall and aggressive prostate cancer than unadjusted PSA levels. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, offering potential to personalize prostate cancer screening.
View details for DOI 10.1038/s41588-024-02068-z
View details for PubMedID 39930085
View details for PubMedCentralID 424236
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Unraveling the genetic landscape of susceptibility to multiple primary cancers.
HGG advances
2025: 100413
Abstract
With advances in cancer screening and treatment, there is a growing population of cancer survivors who may develop subsequent primary cancers. While hereditary cancer syndromes account for only a portion of multiple cancer cases, we sought to explore the role of common genetic variation in susceptibility to multiple primary tumors. We conducted a cross-ancestry genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) of 10,983 individuals with multiple primary cancers, 84,475 individuals with single cancer, and 420,944 cancer-free controls from two large-scale studies. Our GWAS identified six lead variants across five genomic regions that were significantly associated (P<5*10-8) with the risk of developing multiple primary tumors (overall and invasive) relative to cancer-free controls (at 3q26, 8q24, 10q24, 11q13.3, and 17p13). We also found one variant significantly associated with multiple cancers when comparing to single cancer cases (at 22q13.1). Multi-tissue TWAS detected associations with genes involved in telomere maintenance in two of these regions (ACTRT3 in 3q26 and SLK and STN1 in 10q24) and the development of multiple cancers. Additionally, the TWAS also identified several novel genes associated with multiple cancers, including two immune-related genes, IRF4 and TNFRSF6B. Telomere maintenance and immune dysregulation emerge as central, common pathways influencing susceptibility to multiple cancers. These findings underscore the importance of exploring shared mechanisms in carcinogenesis, offering insights for targeted prevention and intervention strategies.
View details for DOI 10.1016/j.xhgg.2025.100413
View details for PubMedID 39910817
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Author Correction: Genetically adjusted PSA levels for prostate cancer screening.
Nature medicine
2025
View details for DOI 10.1038/s41591-025-03539-4
View details for PubMedID 39901049
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Genome-Wide Association Analyses of HPV16 and HPV18 Seropositivity Identify Susceptibility Loci for Cervical Cancer.
Journal of medical virology
2025; 97 (2): e70195
Abstract
Infection by high-risk human papillomavirus is known to exacerbate cervical cancer development. The host immune response is crucial in disease regression. Large-scale genetic association studies for cervical cancer have identified few susceptibility variants, mainly at the human leukocyte antigen locus on chromosome 6. We hypothesized that the host immune response modifies cervical cancer risk and performed three genome-wide association analyses for HPV16, HPV18 and HPV16/18 seropositivity in 7814, 7924, and 7924 samples from the UK Biobank, followed by validation genotyping in the German Cervigen case-control series of cervical cancer and dysplasia. In GWAS analyses, we identified two loci associated with HPV16 seropositivity (6p21.32 and 15q26.2), two loci associated with HPV18 seropositivity (5q31.2 and 14q24.3), and one locus for HPV16 and/or HPV18 seropositivity (at 6p21.32). MAGMA gene-based analysis identified HLA-DQA1 and HLA-DQB1 as genome-wide significant (GWS) genes. In validation genotyping, the genome-wide significant lead variant at 6p21.32, rs9272293 associated with overall cervical disease (OR = 0.86, p = 0.004, 95% CI = 0.78-0.95, n = 3710) and HPV16 positive invasive cancer (OR = 0.73, p = 0.005, 95% CI = 0.59-0.91, n = 1431). This variant was found to be a robust eQTL for HLA-DRB1, HLA-DQB1-AS1, C4B, HLA-DRB5, HLA-DRB6, HLA-DQB1, and HLA-DPB1 in a series of cervical epithelial tissue samples. We additionally genotyped twenty-four HPV seropositivity variants below the GWS threshold out of which eleven variants were found to be associated with cervical disease in our cohort, suggesting that further seropositivity variants may determine cervical disease outcome. Our study identifies novel genomic risk loci that associate with HPV type-specific cervical cancer and dysplasia risk and provides evidence for candidate genes at one of the risk loci.
View details for DOI 10.1002/jmv.70195
View details for PubMedID 39891432
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Tumor Necrosis Factor-Alpha Inhibitor Use and Malignancy Risk: A Systematic Review and Patient Level Meta-Analysis.
Cancers
2025; 17 (3)
Abstract
Over the last two decades, tumor necrosis factor-alpha inhibitors (TNF-Is) have become standard therapies for chronic inflammatory disorders, with an ongoing expansion of indications and off-label applications [...].
View details for DOI 10.3390/cancers17030390
View details for PubMedID 39941759
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Polygenic Risk Score and Upgrading in Patients With Prostate Cancer Receiving Active Surveillance.
JAMA oncology
2024
Abstract
Active surveillance is the preferred management strategy for patients with low- or favorable intermediate-risk prostate cancer (PCa); however, frequent health care visits can be costly and burdensome to patients. Identifying patients who may benefit from intensive vs passive surveillance could reduce these burdens.To investigate associations between a polygenic risk score (PRS) and risk of upgrading and other prostate tumor features in patients receiving active surveillance.This prospective multicenter cohort study across 10 US sites included 1220 patients from the Canary Prostate Active Surveillance Study (PASS) enrolled from July 2008 to November 2017, with follow-up (median, 5.3 years) through August 2022. Participants were those with clinically localized PCa (cT1-T2) receiving active surveillance. Analyses took place from January 2023 to April 2024.Multi-ancestry PRS of 451 PCa risk variants (PRS-451) and 400 PCa risk variants (PRS-400) after excluding prostate-specific antigen (PSA)-associated variants.The primary outcome was PCa upgrading (any Gleason grade increase) vs no upgrading. Secondary outcomes included prostate volume, PSA, PSA density, percentage of biopsy cores with cancer, and Gleason grade group at diagnosis.The median (IQR) age at diagnosis of the 1220 patients receiving active surveillance was 63 (58-67) years. During follow-up, 470 patients upgraded; the 2- and 5-year risks of upgrading were 17.7% (95% CI, 15.5%-19.9%) and 33.3% (95% CI, 30.5%-36.3%), respectively. Each 1-SD unit increase in PRS-451 was associated with 23% increased hazard of upgrading (95% CI, 1.11-1.35; P < .001), whereas PRS-400 was associated with 27% increased hazard (95% CI, 1.15-1.39; P < .001) at any point in time during follow-up. Except for PSA, associations with remaining outcomes were similar or stronger using PRS-400. Higher PRS-400 was associated with smaller prostate volume, a higher percentage of biopsy cores with cancer, and higher PSA density. A model with clinical risk factors had a C-index of 0.64 (95% CI, 0.62-0.67); adding PRS-400 led to a C-index of 0.65 (95% CI, 0.63-0.68).In this cohort study, among patients receiving active surveillance, high PRS was associated with risk of upgrading and possibly tumor multifocality. Excluding PSA variants from the PRS revealed an association with smaller prostate size, which has been previously associated with more aggressive tumors. Although PRS may inform active surveillance, it is yet to be seen whether they improve clinical decisions.
View details for DOI 10.1001/jamaoncol.2024.5398
View details for PubMedID 39666350
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Genomic risk loci for cervical cancer: Associations with disease severity and HPV type
SPRINGERNATURE. 2024: 1262-1263
View details for Web of Science ID 001421430501374
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Genomic risk loci for cervical cancer: Associations with disease severity and HPV type
SPRINGERNATURE. 2024: 1262-1263
View details for Web of Science ID 001407868901081
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The PRIMED Consortium: Reducing disparities in polygenic risk assessment.
American journal of human genetics
2024
Abstract
By improving disease risk prediction, polygenic risk scores (PRSs) could have a significant impact on health promotion and disease prevention. Due to the historical oversampling of populations with European ancestry for genome-wide association studies, PRSs perform less well in other, understudied populations, leading to concerns that clinical use in their current forms could widen health care disparities. The PRIMED Consortium was established to develop methods to improve the performance of PRSs in global populations and individuals of diverse genetic ancestry. To this end, PRIMED is aggregating and harmonizing multiple phenotype and genotype datasets on AnVIL, an interoperable secure cloud-based platform, to perform individual- and summary-level analyses using population and statistical genetics approaches. Study sites, the coordinating center, and representatives from the NIH work alongside other NHGRI and global consortia to achieve these goals. PRIMED is also evaluating ethical and social implications of PRS implementation and investigating the joint modeling of social determinants of health and PRS in computing disease risk. The phenotypes of interest are primarily cardiometabolic diseases and cancer, the leading causes of death and disability worldwide. Early deliverables of the consortium include methods for data sharing on AnVIL, development of a common data model to harmonize phenotype and genotype data from cohort studies as well as electronic health records, adaptation of recent guidelines for population descriptors to global cohorts, and sharing of PRS methods/tools. As a multisite collaboration, PRIMED aims to foster equity in the development and use of polygenic risk assessment.
View details for DOI 10.1016/j.ajhg.2024.10.010
View details for PubMedID 39561770
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Unraveling the genetic landscape of susceptibility to multiple primary cancers.
medRxiv : the preprint server for health sciences
2024
Abstract
With advances in cancer screening and treatment, there is a growing population of cancer survivors who may develop subsequent primary cancers. While hereditary cancer syndromes account for only a portion of multiple cancer cases, we sought to explore the role of common genetic variation in susceptibility to multiple primary tumors. We conducted a cross-ancestry genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) of 10,983 individuals with multiple primary cancers, 84,475 individuals with single cancer, and 420,944 cancer-free controls from two large-scale studies. Our GWAS identified six lead variants across five genomic regions that were significantly associated (P<5*10 -8 ) with the risk of developing multiple primary tumors (overall and invasive) relative to cancer-free controls (at 3q26, 8q24, 10q24, 11q13.3, and 17p13). We also found one variant significantly associated with multiple cancers when comparing to single cancer cases (at 22q13.1). Multi-tissue TWAS detected associations with genes involved in telomere maintenance in two of these regions ( ACTRT3 in 3q26 and SLK and STN1 in 10q24) and the development of multiple cancers. Additionally, the TWAS also identified several novel genes associated with multiple cancers, including two immune-related genes, IRF4 and TNFRSF6B . Telomere maintenance and immune dysregulation emerge as central, common pathways influencing susceptibility to multiple cancers. These findings underscore the importance of exploring shared mechanisms in carcinogenesis, offering insights for targeted prevention and intervention strategies.
View details for DOI 10.1101/2024.10.29.24316326
View details for PubMedID 39574869
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Transcriptome-Wide Association Analysis Identifies Candidate Susceptibility Genes for Prostate-Specific Antigen Levels in Men Without Prostate Cancer.
HGG advances
2024: 100315
Abstract
Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10×10-6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61×10-6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses identified 155 statistically significantly (p < 0.05/22,249 = 2.25×10-6) genes. Out of 173 unique PSA-associated genes across analyses, we replicated 151 (87.3%) in TWAS of 209,318 PCa-free individuals from the Million Veteran Program. Based on conditional analyses, we found 20 genes (11 single-tissue, nine cross-tissue) that were associated with PSA levels in the discovery TWAS that were not attributable to a lead variant from a genome-wide association study (GWAS). Ten of these 20 genes replicated, and two of the replicated genes had colocalization probability > 0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels.
View details for DOI 10.1016/j.xhgg.2024.100315
View details for PubMedID 38845201
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The full spectrum of SLC22 OCT1 mutations illuminates the bridge between drug transporter biophysics and pharmacogenomics.
Molecular cell
2024
Abstract
Mutations in transporters can impact an individual's response to drugs and cause many diseases. Few variants in transporters have been evaluated for their functional impact. Here, we combine saturation mutagenesis and multi-phenotypic screening to dissect the impact of 11,213 missense single-amino-acid deletions, and synonymous variants across the 554 residues of OCT1, a key liver xenobiotic transporter. By quantifying in parallel expression and substrate uptake, we find that most variants exert their primary effect on protein abundance, a phenotype not commonly measured alongside function. Using our mutagenesis results combined with structure prediction and molecular dynamic simulations, we develop accurate structure-function models of the entire transport cycle, providing biophysical characterization of all known and possible human OCT1 polymorphisms. This work provides a complete functional map of OCT1 variants along with a framework for integrating functional genomics, biophysical modeling, and human genetics to predict variant effects on disease and drug efficacy.
View details for DOI 10.1016/j.molcel.2024.04.008
View details for PubMedID 38703769
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Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.
Nature genetics
2023
Abstract
The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
View details for DOI 10.1038/s41588-023-01534-4
View details for PubMedID 37945903
View details for PubMedCentralID 8148035
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Clinical consequences of a genetic predisposition toward higher benign prostate-specific antigen levels.
EBioMedicine
2023; 97: 104838
Abstract
Prostate-specific antigen (PSA) levels are influenced by genetic variation unrelated to prostate cancer risk. Whether a genetic predisposition to a higher PSA level predisposes to a diagnostic work-up for prostate cancer is not known.Participants were 3110 men of African and European ancestries ages 45-70, without prostate cancer and with a baseline PSA < 4 ng/mL, undergoing routine clinical PSA screening. The exposure was a polygenic score (PGS) comprising 111 single nucleotide polymorphisms associated with PSA level, but not prostate cancer. We tested whether the PGS was associated with a: 1) PSA value > 4 ng/mL, 2) International Classification of Diseases (ICD) code for an elevated PSA, 3) encounter with a urologist, or 4) prostate biopsy. Multivariable Cox proportional hazards models were adjusted for age and genetic principal components. Analyses were stratified by age (45-59 years, and 60-70 years old). Association estimates are per standard deviation change in the PGS.The median age was 56.6 years, and 2118 (68%) participants were 45-59 years. The median (IQR) baseline PSA level was 1.0 (0.6-1.7) ng/mL. Among men ages 45-59, the PGS was associated with a PSA > 4 (hazard ratio [HR] = 1.35 [95% CI, 1.17-1.57], p = 4.5 × 10-5), an ICD code for elevated PSA (HR = 1.30 [1.12-1.52], p = 8.0 × 10-4), a urological evaluation (HR = 1.34 [1.14-1.57], p = 4.8 × 10-4), and undergoing a prostate biopsy (HR = 1.35 [1.11-1.64], p = 0.002). Among men ages 60-70, association effect sizes were smaller and not significant.A predisposition toward higher PSA levels was associated with clinical evaluations of an elevated PSA among men ages 45-59 years.National Institutes of Health (NIH).
View details for DOI 10.1016/j.ebiom.2023.104838
View details for PubMedID 37865044
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Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect.
Neuro-oncology advances
2023; 5 (1): vdad115
Abstract
Epigenetic inhibition of the O6-methylguanine-DNA-methyltransferase (MGMT) gene has emerged as a clinically relevant prognostic marker in glioblastoma (GBM). Methylation of the MGMT promoter has been shown to increase chemotherapy efficacy. While traditionally reported as a binary marker, recent methodological advancements have led to quantitative methods of measuring promoter methylation, providing clearer insight into its functional relationship with survival.A CLIA assay and bisulfite sequencing was utilized to develop a quantitative, 17-point, MGMT promoter methylation index. GBMs of 240 newly diagnosed patients were sequenced and risk for mortality was assessed. Nonlinearities were captured by fitting splines to Cox proportional hazard models and plotting smoothed residuals. Covariates included age, Karnofsky performance status, IDH1 mutation, and extent of resection.Median follow-up time and progression-free survival were 16 and 9 months, respectively. A total of 176 subjects experienced death. A one-unit increase in promoter CpG methylation resulted in a 4% reduction in hazard (95% CI 0.93-0.99, P < .005). GBM patients with low levels of promoter methylation (1-6 CpG sites) fared markedly worse (HR = 1.62, 95% CI 1.03-2.54, P < .036) than individuals who were unmethylated. Subjects with medium levels of promoter methylation (7-12 sites) had the greatest reduction in hazard (HR = 0.48, 95% CI 0.29-0.80, P < .004), followed by individuals in the highest promoter methylation tertile (HR = 0.62, 95% CI 0.40-0.97, P < .035).Our findings suggest that the relationship between the extent of MGMT promoter methylation and survival in GBM may be nonlinear. These findings challenge the current understanding of MGMT and underlines the clinical importance of determining its prognostic utility. Potential limitations include censoring, sample size, and extraneous mutations.
View details for DOI 10.1093/noajnl/vdad115
View details for PubMedID 37899778
View details for PubMedCentralID PMC10611422
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Principles and methods for transferring polygenic risk scores across global populations.
Nature reviews. Genetics
2023
Abstract
Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.
View details for DOI 10.1038/s41576-023-00637-2
View details for PubMedID 37620596
View details for PubMedCentralID 9391275
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A gene-based association test of interactions for maternal-fetal genotypes identifies genes associated with nonsyndromic congenital heart defects.
Genetic epidemiology
2023
Abstract
The risk of congenital heart defects (CHDs) may be influenced by maternal genes, fetal genes, and their interactions. Existing methods commonly test the effects of maternal and fetal variants one-at-a-time and may have reduced statistical power to detect genetic variants with low minor allele frequencies. In this article, we propose a gene-based association test of interactions for maternal-fetal genotypes (GATI-MFG) using a case-mother and control-mother design. GATI-MFG can integrate the effects of multiple variants within a gene or genomic region and evaluate the joint effect of maternal and fetal genotypes while allowing for their interactions. In simulation studies, GATI-MFG had improved statistical power over alternative methods, such as the single-variant test and functional data analysis (FDA) under various disease scenarios. We further applied GATI-MFG to a two-phase genome-wide association study of CHDs for the testing of both common variants and rare variants using 947 CHD case mother-infant pairs and 1306 control mother-infant pairs from the National Birth Defects Prevention Study (NBDPS). After Bonferroni adjustment for 23,035 genes, two genes on chromosome 17, TMEM107 (p = 1.64e-06) and CTC1 (p = 2.0e-06), were identified for significant association with CHD in common variants analysis. Gene TMEM107 regulates ciliogenesis and ciliary protein composition and was found to be associated with heterotaxy. Gene CTC1 plays an essential role in protecting telomeres from degradation, which was suggested to be associated with cardiogenesis. Overall, GATI-MFG outperformed the single-variant test and FDA in the simulations, and the results of application to NBDPS samples are consistent with existing literature supporting the association of TMEM107 and CTC1 with CHDs.
View details for DOI 10.1002/gepi.22533
View details for PubMedID 37341229
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Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry.
American journal of human genetics
2023
Abstract
Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.
View details for DOI 10.1016/j.ajhg.2023.05.010
View details for PubMedID 37311464
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The full spectrum of OCT1 (SLC22A1) mutations bridges transporter biophysics to drug pharmacogenomics.
bioRxiv : the preprint server for biology
2023
Abstract
Membrane transporters play a fundamental role in the tissue distribution of endogenous compounds and xenobiotics and are major determinants of efficacy and side effects profiles. Polymorphisms within these drug transporters result in inter-individual variation in drug response, with some patients not responding to the recommended dosage of drug whereas others experience catastrophic side effects. For example, variants within the major hepatic Human organic cation transporter OCT1 (SLC22A1) can change endogenous organic cations and many prescription drug levels. To understand how variants mechanistically impact drug uptake, we systematically study how all known and possible single missense and single amino acid deletion variants impact expression and substrate uptake of OCT1. We find that human variants primarily disrupt function via folding rather than substrate uptake. Our study revealed that the major determinants of folding reside in the first 300 amino acids, including the first 6 transmembrane domains and the extracellular domain (ECD) with a stabilizing and highly conserved stabilizing helical motif making key interactions between the ECD and transmembrane domains. Using the functional data combined with computational approaches, we determine and validate a structure-function model of OCT1s conformational ensemble without experimental structures. Using this model and molecular dynamic simulations of key mutants, we determine biophysical mechanisms for how specific human variants alter transport phenotypes. We identify differences in frequencies of reduced function alleles across populations with East Asians vs European populations having the lowest and highest frequency of reduced function variants, respectively. Mining human population databases reveals that reduced function alleles of OCT1 identified in this study associate significantly with high LDL cholesterol levels. Our general approach broadly applied could transform the landscape of precision medicine by producing a mechanistic basis for understanding the effects of human mutations on disease and drug response.
View details for DOI 10.1101/2023.06.06.543963
View details for PubMedID 37333090
View details for PubMedCentralID PMC10274788
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Genetically adjusted PSA levels for prostate cancer screening.
Nature medicine
2023
Abstract
Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P < 5 × 10-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P = 6.2 × 10-14, area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P = 1.1 × 10-12, AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P = 7.2 × 10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.
View details for DOI 10.1038/s41591-023-02277-9
View details for PubMedID 37264206
View details for PubMedCentralID 424236
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A complex systems model of breast cancer etiology: The Paradigm II Model.
PloS one
2023; 18 (5): e0282878
Abstract
Complex systems models of breast cancer have previously focused on prediction of prognosis and clinical events for individual women. There is a need for understanding breast cancer at the population level for public health decision-making, for identifying gaps in epidemiologic knowledge and for the education of the public as to the complexity of this most common of cancers.We developed an agent-based model of breast cancer for the women of the state of California using data from the U.S. Census, the California Health Interview Survey, the California Cancer Registry, the National Health and Nutrition Examination Survey and the literature. The model was implemented in the Julia programming language and R computing environment. The Paradigm II model development followed a transdisciplinary process with expertise from multiple relevant disciplinary experts from genetics to epidemiology and sociology with the goal of exploring both upstream determinants at the population level and pathophysiologic etiologic factors at the biologic level. The resulting model reproduces in a reasonable manner the overall age-specific incidence curve for the years 2008-2012 and incidence and relative risks due to specific risk factors such as BRCA1, polygenic risk, alcohol consumption, hormone therapy, breastfeeding, oral contraceptive use and scenarios for environmental toxin exposures.The Paradigm II model illustrates the role of multiple etiologic factors in breast cancer from domains of biology, behavior and the environment. The value of the model is in providing a virtual laboratory to evaluate a wide range of potential interventions into the social, environmental and behavioral determinants of breast cancer at the population level.
View details for DOI 10.1371/journal.pone.0282878
View details for PubMedID 37205649
View details for PubMedCentralID PMC10198497
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Evaluating Approaches for Constructing Polygenic Risk Scores for Prostate Cancer in Men of African and European Ancestry.
medRxiv : the preprint server for health sciences
2023
Abstract
Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer risk variants from multi-ancestry GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California/Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI=0.635-0.677) in African and 0.844 (95% CI=0.840-0.848) in European ancestry men and corresponding prostate cancer OR of 1.83 (95% CI=1.67-2.00) and 2.19 (95% CI=2.14-2.25), respectively, for each SD unit increase in the GW-PRS. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 had larger or similar AUCs (AUC=0.679, 95% CI=0.659-0.700 and AUC=0.845, 95% CI=0.841-0.849, respectively) and comparable prostate cancer OR (OR=2.05, 95% CI=1.87-2.26 and OR=2.21, 95% CI=2.16-2.26, respectively). Findings were similar in the validation data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.
View details for DOI 10.1101/2023.05.12.23289860
View details for PubMedID 37292833
View details for PubMedCentralID PMC10246022
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Development and testing of a polygenic risk score for breast cancer aggressiveness.
NPJ precision oncology
2023; 7 (1): 42
Abstract
Aggressive breast cancers portend a poor prognosis, but current polygenic risk scores (PRSs) for breast cancer do not reliably predict aggressive cancers. Aggressiveness can be effectively recapitulated using tumor gene expression profiling. Thus, we sought to develop a PRS for the risk of recurrence score weighted on proliferation (ROR-P), an established prognostic signature. Using 2363 breast cancers with tumor gene expression data and single nucleotide polymorphism (SNP) genotypes, we examined the associations between ROR-P and known breast cancer susceptibility SNPs using linear regression models. We constructed PRSs based on varying p-value thresholds and selected the optimal PRS based on model r2 in 5-fold cross-validation. We then used Cox proportional hazards regression to test the ROR-P PRS's association with breast cancer-specific survival in two independent cohorts totaling 10,196 breast cancers and 785 events. In meta-analysis of these cohorts, higher ROR-P PRS was associated with worse survival, HR per SD = 1.13 (95% CI 1.06-1.21, p = 4.0 × 10-4). The ROR-P PRS had a similar magnitude of effect on survival as a comparator PRS for estrogen receptor (ER)-negative versus positive cancer risk (PRSER-/ER+). Furthermore, its effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS provides additional prognostic information beyond ER status. In summary, we used integrated analysis of germline SNP and tumor gene expression data to construct a PRS associated with aggressive tumor biology and worse survival. These findings could potentially enhance risk stratification for breast cancer screening and prevention.
View details for DOI 10.1038/s41698-023-00382-z
View details for PubMedID 37188791
View details for PubMedCentralID PMC10185660
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Transcriptome-Wide Association Analysis Identifies Novel Candidate Susceptibility Genes for Prostate-Specific Antigen Levels in Men Without Prostate Cancer.
medRxiv : the preprint server for health sciences
2023
Abstract
Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility to screen for prostate cancer (PCa). We thus conducted a transcriptome-wide association study (TWAS) of PSA levels using genome-wide summary statistics from 95,768 PCa-free men, the MetaXcan framework, and gene prediction models trained in Genotype-Tissue Expression (GTEx) project data. Tissue-specific analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10e-6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61e-6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses that combined associations across 45 tissues identified 155 genes that were statistically significantly (p < 0.05/22,249 = 2.25e-6) associated with PSA levels. Based on conditional analyses that assessed whether TWAS associations were attributable to a lead GWAS variant, we found 20 novel genes (11 single-tissue, 9 cross-tissue) that were associated with PSA levels in the TWAS. Of these novel genes, five showed evidence of colocalization (colocalization probability > 0.5): EXOSC9, CCNA2, HIST1H2BN, RP11-182L21.6 , and RP11-327J17.2 . Six of the 20 novel genes are not known to impact PCa risk. These findings yield new hypotheses for genetic factors underlying PSA levels that should be further explored toward improving our understanding of PSA biology.
View details for DOI 10.1101/2023.05.04.23289526
View details for PubMedID 37205487
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A Polygenic Risk Score for Prostate Cancer Risk Prediction.
JAMA internal medicine
2023
Abstract
This retrospective cohort study compares 2 risk calculator systems that compute the probabilities of finding high-grade or any cancer on biopsy results in men undergoing a first prostate biopsy.
View details for DOI 10.1001/jamainternmed.2022.6795
View details for PubMedID 36877498
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Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry.
European urology
2023
Abstract
Genetic factors play an important role in prostate cancer (PCa) susceptibility.To discover common genetic variants contributing to the risk of PCa in men of African ancestry.We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry.Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness.Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4).This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry.In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.
View details for DOI 10.1016/j.eururo.2023.01.022
View details for PubMedID 36872133
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Re-envisioning community genetics: community empowerment in preventive genomics.
Journal of community genetics
2023
Abstract
As genomic technologies rapidly develop, polygenic scores (PGS) are entering into a growing conversation on how to improve precision in public health and prevent chronic disease. While the integration of PGS into public health and clinical services raises potential benefits, it also introduces potential harms. In particular, there is a high level of uncertainty about how to incorporate PGS into clinical settings in a manner that is equitable, just, and aligned with the long-term goals of many healthcare systems to support person-centered and value-based care. This paper argues that any conversation about whether and how to design and implement PGS clinical services requires dynamic engagement with local communities, patients, and families. These parties often face the consequences, both positive and negative, of such uncertainties and should therefore drive clinical translation. As a collaborative effort between hospital stakeholders, community partners, and researchers, this paper describes a community-empowered co-design process for addressing uncertainty and making programmatic decisions about the implementation of PGS into clinical services. We provide a framework for others interested in designing clinical programs that are responsive to, and inclusive and respectful of, local communities.
View details for DOI 10.1007/s12687-023-00638-y
View details for PubMedID 36765027
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Use of Monitoring Tests Among Patients With Localized Prostate Cancer Managed With Observation.
The Journal of urology
2023: 101097JU0000000000003159
Abstract
It is unknown whether compliance with recommended monitoring tests during observation of localized prostate cancer has changed over time.We performed a retrospective cohort study of Medicare beneficiaries diagnosed with low- or intermediate-risk prostate cancer in 2004-2016 who were initially managed with observation for a minimum of 12 months. The primary objective was to examine rates of PSA testing, prostate biopsy, and prostate MRI. We used multivariable mixed effects Poisson regression to determine whether rates of PSA testing and prostate biopsy increased over time. In addition, we identified clinical, sociodemographic, and provider factors associated with the frequency of monitoring tests during observation.We identified 10,639 patients diagnosed at a median age of 73 (IQR 69-77) years. The median follow-up time was 4.3 (IQR 2.7-6.6) years after diagnosis. Among patients managed without treatment for 5 years, 98% received at ≥1 PSA test, 48.0% ≥1 additional prostate biopsy, and 31.0% ≥1 prostate MRI. Among patients managed with observation for ≥12 months, mixed effects Poisson regression revealed that rates of PSA testing and biopsy increased over time (per calendar year: RR 1.02, 95% CI: 1.02-1.03 and RR 1.10, 95% CI: 1.08-1.11, respectively). Clinical and sociodemographic factors including age, clinical risk, race/ethnicity, census tract poverty, and region were associated with rates of biopsy and PSA testing.Use of recommended monitoring tests including repeat prostate biopsy remains low among Medicare beneficiaries undergoing observation for low and intermediate-risk prostate cancer.
View details for DOI 10.1097/JU.0000000000003159
View details for PubMedID 36753746
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Development and testing of a polygenic risk score for breast cancer. Aggressiveness.
AMER ASSOC CANCER RESEARCH. 2023
View details for Web of Science ID 001057852300092
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Development and testing of a polygenic risk score for breast cancer. Aggressiveness
AMER ASSOC CANCER RESEARCH. 2023
View details for Web of Science ID 001058158400008
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Development and testing of a polygenic risk score for breast cancer. Aggressiveness
AMER ASSOC CANCER RESEARCH. 2023
View details for DOI 10.1158/1940-6215.PrecPrev22-PR008
View details for Web of Science ID 001057852300096
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Assessment of genetic susceptibility to multiple primary cancers through whole-exome sequencing in two large multi-ancestry studies.
BMC medicine
2022; 20 (1): 332
Abstract
Up to one of every six individuals diagnosed with one cancer will be diagnosed with a second primary cancer in their lifetime. Genetic factors contributing to the development of multiple primary cancers, beyond known cancer syndromes, have been underexplored.To characterize genetic susceptibility to multiple cancers, we conducted a pan-cancer, whole-exome sequencing study of individuals drawn from two large multi-ancestry populations (6429 cases, 165,853 controls). We created two groupings of individuals diagnosed with multiple primary cancers: (1) an overall combined set with at least two cancers across any of 36 organ sites and (2) cancer-specific sets defined by an index cancer at one of 16 organ sites with at least 50 cases from each study population. We then investigated whether variants identified from exome sequencing were associated with these sets of multiple cancer cases in comparison to individuals with one and, separately, no cancers.We identified 22 variant-phenotype associations, 10 of which have not been previously discovered and were significantly overrepresented among individuals with multiple cancers, compared to those with a single cancer.Overall, we describe variants and genes that may play a fundamental role in the development of multiple primary cancers and improve our understanding of shared mechanisms underlying carcinogenesis.
View details for DOI 10.1186/s12916-022-02535-6
View details for PubMedID 36199081
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Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer.
Nature genetics
2022
Abstract
To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.
View details for DOI 10.1038/s41588-022-01115-x
View details for PubMedID 35915169
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Random Field Modeling of Multi-trait Multi-locus Association for Detecting Methylation Quantitative Trait Loci.
Bioinformatics (Oxford, England)
2022
Abstract
MOTIVATION: CpG sites within the same genomic region often share similar methylation patterns and tend to be co-regulated by multiple genetic variants that may interact with one another.RESULTS: We propose a multi-trait methylation random field (multi-MRF) method to evaluate the joint association between a set of CpG sites and a set of genetic variants. The proposed method has several advantages. First, it is a multi-trait method that allows flexible correlation structures between neighboring CpG sites (e.g., distance-based correlation). Second, it is also a multi-locus method that integrates the effect of multiple common and rare genetic variants. Third, it models the methylation traits with a beta distribution to characterize their bimodal and interval properties. Through simulations, we demonstrated that the proposed method had improved power over some existing methods under various disease scenarios. We further illustrated the proposed method via an application to a study of congenital heart defects (CHD) with 83 cardiac tissue samples. Our results suggested that gene BACE2, a mQTL candidate, colocalized with expression QTLs in artery tibial and harbored genetic variants with nominal significant associations in two genome-wide association studies of CHD.AVAILABILITY: https://github.com/chenlyu2656/Multi-MRF.SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
View details for DOI 10.1093/bioinformatics/btac443
View details for PubMedID 35781319
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Genetic determinants of PSA levels improve prostate cancer screening
AMER ASSOC CANCER RESEARCH. 2022
View details for Web of Science ID 000892509506337
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Genetic risk factors for the development of multiple primary cancers
AMER ASSOC CANCER RESEARCH. 2022
View details for Web of Science ID 000892509506341
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Cancer systems epidemiology: Overcoming misconceptions and integrating systems approaches into cancer research.
PLoS medicine
2022; 19 (6): e1004027
Abstract
Patricia Mabry and coauthors discuss application of systems approaches in cancer research.
View details for DOI 10.1371/journal.pmed.1004027
View details for PubMedID 35714096
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Genetic analysis of lung cancer and the germline impact on somatic mutation burden.
Journal of the National Cancer Institute
2022
Abstract
Germline genetic variation contributes to lung cancer (LC) susceptibility. Previous genome-wide association studies (GWAS) have implicated susceptibility loci involved in smoking propensity and DNA repair genes, but further work is required to identify susceptibility variants.To identify LC susceptibility loci, a family history-based genome-wide association (GWAx) study of LC (48,843 European "proxy" LC cases, 195,387 controls) was combined with previously LC GWAS (29,266 cases, 56,450 controls) by meta-analysis. Colocalisation was used to explore candidate genes and overlap with existing traits at discovered susceptibility loci. Polygenic Risk Scores (PRS) were tested within an independent validation cohort (1,666 LC cases vs 6,664 controls) using variants selected from the LC susceptibility loci and a novel selection approach using published GWAS summary statistics. Finally, the effects of the LC PRS on somatic mutational burden were explored in patients whose tumour resections have been profiled by exome (n = 685) and genome sequencing (n = 61). Statistical tests were 2-sided.The GWAx-GWAS meta-analysis identified 8 novel LC loci. Colocalization implicated DNA repair genes (CHEK1), metabolic genes (CYP1A1) and smoking propensity (CHRNA4 and CHRNB2). PRS analysis demonstrated that these variants, as well as sub-genome wide significant variants related to eQTLs and/or smoking propensity, assisted in LC genetic risk prediction (OR = 1.37, 95% CI 1.29-1.45, P = 1.44 x10-25). Patients with higher genetic PRS loads of smoking-related variants tended to have higher mutation burdens in their lung tumours.This study has expanded the number of LC susceptibility loci and provided insights into the molecular mechanisms by which these susceptibility variants contribute to LC development.
View details for DOI 10.1093/jnci/djac087
View details for PubMedID 35511172
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A genome-wide association study of obstructive heart defects among participants in the National Birth Defects Prevention Study.
American journal of medical genetics. Part A
2022
Abstract
Obstructive heart defects (OHDs) share common structural lesions in arteries and cardiac valves, accounting for ~25% of all congenital heart defects. OHDs are highly heritable, resulting from interplay among maternal exposures, genetic susceptibilities, and epigenetic phenomena. A genome-wide association study was conducted in National Birth Defects Prevention Study participants (Ndiscovery =3978; Nreplication =2507), investigating the genetic architecture of OHDs using transmission/disequilibrium tests (TDT) in complete case-parental trios (Ndiscovery_TDT =440; Nreplication_TDT =275) and case-control analyses separately in infants (Ndiscovery_CCI =1635; Nreplication_CCI =990) and mothers (case status defined by infant; Ndiscovery_CCM =1703; Nreplication_CCM =1078). In the TDT analysis, the SLC44A2 single nucleotide polymorphism (SNP) rs2360743 was significantly associated with OHD (pdiscovery =4.08*10-9 ; preplication =2.44*10-4 ). A CAPN11 SNP (rs55877192) was suggestively associated with OHD (pdiscovery =1.61*10-7 ; preplication =0.0016). Two other SNPs were suggestively associated (p<1*10-6 ) with OHD in only the discovery sample. In the case-control analyses, no SNPs were genome-wide significant, and, even with relaxed thresholds (*discovery <1*10-5 and preplication <0.05), only one SNP (rs188255766) in the infant analysis was associated with OHDs (pdiscovery =1.42*10-6 ; preplication =0.04). Additional SNPs with pdiscovery <1*10-5 were in loci supporting previous findings but did not replicate. Overall, there was modest evidence of an association between rs2360743 and rs55877192 and OHD and some evidence validating previously published findings.
View details for DOI 10.1002/ajmg.a.62759
View details for PubMedID 35451555
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Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas. Diabetes Care 2021;44:2673-2682
DIABETES CARE
2022; 45 (4): E82-E83
View details for DOI 10.2337/dci21-0066
View details for Web of Science ID 000876491300004
View details for PubMedID 35349657
View details for PubMedCentralID PMC9016729
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Association Between a 22-feature Genomic Classifier and Biopsy Gleason Upgrade During Active Surveillance for Prostate Cancer.
European urology open science
2022; 37: 113-119
Abstract
Background: Although the Decipher genomic classifier has been validated as a prognostic tool for several prostate cancer endpoints, little is known about its role in assessing the risk of biopsy reclassification for patients on active surveillance, a key event that often triggers treatment.Objective: To evaluate the association between Decipher genomic classifier scores and biopsy Gleason upgrading among patients on active surveillance.Design setting and participants: This was a retrospective cohort study among patients with low- and favorable intermediate-risk prostate cancer on active surveillance who underwent biopsy-based Decipher testing as part of their clinical care.Outcome measurements and statistical analysis: We evaluated the association between the Decipher score and any increase in biopsy Gleason grade group (GG) using univariable and multivariable logistic regression. We compared the area under the receiver operating characteristic curve (AUC) for models comprising baseline clinical variables with or without the Decipher score.Results and limitations: We identified 133 patients for inclusion with a median age of 67.7 yr and median prostate-specific of 5.6 ng/ml. At enrollment, 75.9% had GG1 and 24.1% had GG2 disease. Forty-three patients experienced biopsy upgrading. On multivariable logistic regression, the Decipher score was significantly associated with biopsy upgrading (odds ratio 1.37 per 0.10 unit increase, 95% confidence interval [CI] 1.05-1.79; p = 0.02). The Decipher score was associated with upgrading among patients with biopsy GG 1 disease, but not GG2 disease. The discriminative ability of a clinical model (AUC 0.63, 95% CI 0.51-0.74) was improved by integration of the Decipher score (AUC 0.69, 95% CI 0.58-0.80).Conclusions: The Decipher genomic classifier score was associated with short-term biopsy Gleason upgrading among patients on active surveillance.Patient summary: The results from this study indicate that among patients with prostate cancer undergoing active surveillance, those with higher Decipher scores were more likely to have higher-grade disease found over time. These findings indicate that the Decipher test might be useful for guiding the intensity of monitoring during active surveillance, such as more frequent biopsy for patients with higher scores.
View details for DOI 10.1016/j.euros.2022.01.008
View details for PubMedID 35243396
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Genetic Factors Associated with Prostate Cancer Conversion from Active Surveillance to Treatment.
HGG advances
1800; 3 (1)
Abstract
Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for prostate cancer, many men on AS eventually convert to active treatment. PC is one of the most heritable cancers, and genetic factors that predispose to aggressive tumors may help distinguish men who are more likely to discontinue AS. To investigate this, we undertook a multi-institutional genome-wide association study (GWAS) of 5,222 PC patients and 1,139 other patients from replication cohorts, all of whom initially elected AS and were followed over time for the potential outcome of conversion from AS to active treatment. In the GWAS we detected 18 variants associated with conversion, 15 of which were not previously associated with PC risk. With a transcriptome-wide association study (TWAS), we found two genes associated with conversion (MAST3, p = 6.9*10-7 and GAB2, p = 2.0*10-6). Moreover, increasing values of a previously validated 269-variant genetic risk score (GRS) for PC was positively associated with conversion (e.g., comparing the highest to the two middle deciles gave a hazard ratio [HR] = 1.13; 95% Confidence Interval [CI]= 0.94-1.36); whereas, decreasing values of a 36-variant GRS for prostate-specific antigen (PSA) levels were positively associated with conversion (e.g., comparing the lowest to the two middle deciles gave a HR = 1.25; 95% CI, 1.04-1.50). These results suggest that germline genetics may help inform and individualize the decision of AS-or the intensity of monitoring on AS-versus treatment for the initial management of patients with low-risk PC.
View details for DOI 10.1016/j.xhgg.2021.100070
View details for PubMedID 34993496
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The Role of Dementia Diagnostic Delay in the Inverse Cancer-Dementia Association
JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES
2022; 77 (6): 1254-1260
Abstract
Cancer is inversely associated with dementia. Using simulations, we examined whether this inverse association may be explained by dementia diagnosis timing, including death before dementia diagnosis and differential diagnosis patterns by cancer history.We used multistate Markov simulation models to generate cohorts 65 years of age and free of cancer and dementia at baseline; follow-up for incident cancer (all cancers, breast, prostate, and lung cancer), dementia, dementia diagnosis among those with dementia, and death occurred monthly over 30 years. Models specified no true effect of cancer on dementia, and used age-specific transition rates calibrated to U.S. population and cohort data. We varied the average lapse between dementia onset and diagnosis, including nondifferential and differential delays by cancer history, and examined observed incidence rate ratios (IRRs) for the effect of cancer on dementia diagnosis.Nondifferential dementia diagnosis delay introduced minimal bias (IRRs = 0.98-1.02) for all cancer, breast, and prostate models and substantial bias (IRR = 0.78) in lung cancer models. For the differential dementia diagnosis delay model of all cancer types combined, simulation scenarios with ≥20% lower dementia diagnosis rate (additional 4.5-month delay) in those with cancer history versus without yielded results consistent with literature estimates. Longer dementia diagnosis delays in those with cancer and higher mortality in those with cancer and dementia yielded more bias.Delays in dementia diagnosis may play a role in the inverse cancer-dementia relationship, especially for more fatal cancers, but moderate differential delays in those with cancer were needed to fully explain the literature-reported IRRs.
View details for DOI 10.1093/gerona/glab341
View details for Web of Science ID 000790049800001
View details for PubMedID 34788817
View details for PubMedCentralID PMC9159667
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Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas
DIABETES CARE
2021; 44 (12): 2673-2682
Abstract
Sulfonylureas, the first available drugs for the management of type 2 diabetes, remain widely prescribed today. However, there exists significant variability in glycemic response to treatment. We aimed to establish heritability of sulfonylurea response and identify genetic variants and interacting treatments associated with HbA1c reduction.As an initiative of the Metformin Genetics Plus Consortium (MetGen Plus) and the DIabetes REsearCh on patient straTification (DIRECT) consortium, 5,485 White Europeans with type 2 diabetes treated with sulfonylureas were recruited from six referral centers in Europe and North America. We first estimated heritability using the generalized restricted maximum likelihood approach and then undertook genome-wide association studies of glycemic response to sulfonylureas measured as HbA1c reduction after 12 months of therapy followed by meta-analysis. These results were supported by acute glipizide challenge in humans who were naïve to type 2 diabetes medications, cis expression quantitative trait loci (eQTL), and functional validation in cellular models. Finally, we examined for possible drug-drug-gene interactions.After establishing that sulfonylurea response is heritable (mean ± SEM 37 ± 11%), we identified two independent loci near the GXYLT1 and SLCO1B1 genes associated with HbA1c reduction at a genome-wide scale (P < 5 × 10-8). The C allele at rs1234032, near GXYLT1, was associated with 0.14% (1.5 mmol/mol), P = 2.39 × 10-8), lower reduction in HbA1c. Similarly, the C allele was associated with higher glucose trough levels (β = 1.61, P = 0.005) in healthy volunteers in the SUGAR-MGH given glipizide (N = 857). In 3,029 human whole blood samples, the C allele is a cis eQTL for increased expression of GXYLT1 (β = 0.21, P = 2.04 × 10-58). The C allele of rs10770791, in an intronic region of SLCO1B1, was associated with 0.11% (1.2 mmol/mol) greater reduction in HbA1c (P = 4.80 × 10-8). In 1,183 human liver samples, the C allele at rs10770791 is a cis eQTL for reduced SLCO1B1 expression (P = 1.61 × 10-7), which, together with functional studies in cells expressing SLCO1B1, supports a key role for hepatic SLCO1B1 (encoding OATP1B1) in regulation of sulfonylurea transport. Further, a significant interaction between statin use and SLCO1B1 genotype was observed (P = 0.001). In statin nonusers, C allele homozygotes at rs10770791 had a large absolute reduction in HbA1c (0.48 ± 0.12% [5.2 ± 1.26 mmol/mol]), equivalent to that associated with initiation of a dipeptidyl peptidase 4 inhibitor.We have identified clinically important genetic effects at genome-wide levels of significance, and important drug-drug-gene interactions, which include commonly prescribed statins. With increasing availability of genetic data embedded in clinical records these findings will be important in prescribing glucose-lowering drugs.
View details for DOI 10.2337/dc21-1152
View details for Web of Science ID 000743311000007
View details for PubMedID 34607834
View details for PubMedCentralID PMC8669535
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Residential particulate matter, proximity to major roads, traffic density and traffic volume as risk factors for preterm birth in California.
Paediatric and perinatal epidemiology
2021
Abstract
BACKGROUND: While pollution from vehicle sources is an established risk factor for preterm birth, it is unclear whether distance of residence to the nearest major road or related measures like major road density represent useful measures for characterising risk.OBJECTIVE: To determine whether major road proximity measures (including distance to major road, major road density and traffic volume) are more useful risk factors for preterm birth than other established vehicle-related measures (including particulate matter <2.5mum in diameter (PM2.5 ) and diesel particulate matter (diesel PM)).METHODS: This retrospective cohort study included 2.7 million births across the state of California from 2011-2017; each address at delivery was geocoded. Geocoding was used to calculate distance to the nearest major road, major road density within a 500m radius and major road density weighted by truck volume. We measured associations with preterm birth using risk ratios adjusted for target demographic, clinical, socioeconomic and environmental covariates (aRRs). We compared these to the associations between preterm birth and PM2.5 and diesel PM by census tract of residence.RESULTS: Findings showed that whereas higher mean levels of PM2.5 and diesel PM by census tract were associated with a higher risk of preterm birth, living closer to roads or living in higher traffic density areas was not associated with higher risk. Residence in a census tract with a mean PM2.5 in the top quartile compared with the lowest quartile was associated with the highest observed risk of preterm birth (aRR 1.04, 95% CI 1.04, 1.05).CONCLUSIONS: Over a large geographical region with a diverse population, PM2.5 and diesel PM were associated with preterm birth, while measures of distance to major road were not, suggesting that these distance measures do not serve as a proxy for measures of particulate matter in the context of preterm birth.
View details for DOI 10.1111/ppe.12820
View details for PubMedID 34797570
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Factors Associated With Time to Conversion from Active Surveillance to Treatment for Prostate Cancer in a Multi-Institutional Cohort
JOURNAL OF UROLOGY
2021; 206 (5): 1147
Abstract
We examined the demographic and clinicopathological parameters associated with the time to convert from active surveillance to treatment among men with prostate cancer.A multi-institutional cohort of 7,279 patients managed with active surveillance had data and biospecimens collected for germline genetic analyses.Of 6,775 men included in the analysis, 2,260 (33.4%) converted to treatment at a median followup of 6.7 years. Earlier conversion was associated with higher Gleason grade groups (GG2 vs GG1 adjusted hazard ratio [aHR] 1.57, 95% CI 1.36-1.82; ≥GG3 vs GG1 aHR 1.77, 95% CI 1.29-2.43), serum prostate specific antigen concentrations (aHR per 5 ng/ml increment 1.18, 95% CI 1.11-1.25), tumor stages (cT2 vs cT1 aHR 1.58, 95% CI 1.41-1.77; ≥cT3 vs cT1 aHR 4.36, 95% CI 3.19-5.96) and number of cancerous biopsy cores (3 vs 1-2 cores aHR 1.59, 95% CI 1.37-1.84; ≥4 vs 1-2 cores aHR 3.29, 95% CI 2.94-3.69), and younger age (age continuous per 5-year increase aHR 0.96, 95% CI 0.93-0.99). Patients with high-volume GG1 tumors had a shorter interval to conversion than those with low-volume GG1 tumors and behaved like the higher-risk patients. We found no significant association between the time to conversion and self-reported race or genetic ancestry.A shorter time to conversion from active surveillance to treatment was associated with higher-risk clinicopathological tumor features. Furthermore, patients with high-volume GG1 tumors behaved similarly to those with intermediate and high-risk tumors. An exploratory analysis of self-reported race and genetic ancestry revealed no association with the time to conversion.
View details for DOI 10.1097/JU.0000000000001937
View details for Web of Science ID 000708148000103
View details for PubMedID 34503355
View details for PubMedCentralID PMC8734323
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REPLY BY AUTHORS
JOURNAL OF UROLOGY
2021; 206 (5): 1156
View details for Web of Science ID 000708148000009
View details for PubMedID 34503354
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Genetic determinants of blood-cell traits influence susceptibility to childhood acute lymphoblastic leukemia.
American journal of human genetics
2021; 108 (10): 1823-1835
Abstract
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Despite overlap between genetic risk loci for ALL and hematologic traits, the etiological relevance of dysregulated blood-cell homeostasis remains unclear. We investigated this question in a genome-wide association study (GWAS) of childhood ALL (2,666 affected individuals, 60,272 control individuals) and a multi-trait GWAS of nine blood-cell indices in the UK Biobank. We identified 3,000 blood-cell-trait-associated (p < 5.0 × 10-8) variants, explaining 4.0% to 23.9% of trait variation and including 115 loci associated with blood-cell ratios (LMR, lymphocyte-to-monocyte ratio; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio). ALL susceptibility was genetically correlated with lymphocyte counts (rg = 0.088, p = 4.0 × 10-4) and PLR (rg = -0.072, p = 0.0017). In Mendelian randomization analyses, genetically predicted increase in lymphocyte counts was associated with increased ALL risk (odds ratio [OR] = 1.16, p = 0.031) and strengthened after accounting for other cell types (OR = 1.43, p = 8.8 × 10-4). We observed positive associations with increasing LMR (OR = 1.22, p = 0.0017) and inverse effects for NLR (OR = 0.67, p = 3.1 × 10-4) and PLR (OR = 0.80, p = 0.002). Our study shows that a genetically induced shift toward higher lymphocyte counts, overall and in relation to monocytes, neutrophils, and platelets, confers an increased susceptibility to childhood ALL.
View details for DOI 10.1016/j.ajhg.2021.08.004
View details for PubMedID 34469753
View details for PubMedCentralID PMC8546033
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Detecting methylation quantitative trait loci using a methylation random field method
BRIEFINGS IN BIOINFORMATICS
2021; 22 (6)
Abstract
DNA methylation may be regulated by genetic variants within a genomic region, referred to as methylation quantitative trait loci (mQTLs). The changes of methylation levels can further lead to alterations of gene expression, and influence the risk of various complex human diseases. Detecting mQTLs may provide insights into the underlying mechanism of how genotypic variations may influence the disease risk. In this article, we propose a methylation random field (MRF) method to detect mQTLs by testing the association between the methylation level of a CpG site and a set of genetic variants within a genomic region. The proposed MRF has two major advantages over existing approaches. First, it uses a beta distribution to characterize the bimodal and interval properties of the methylation trait at a CpG site. Second, it considers multiple common and rare genetic variants within a genomic region to identify mQTLs. Through simulations, we demonstrated that the MRF had improved power over other existing methods in detecting rare variants of relatively large effect, especially when the sample size is small. We further applied our method to a study of congenital heart defects with 83 cardiac tissue samples and identified two mQTL regions, MRPS10 and PSORS1C1, which were colocalized with expression QTL in cardiac tissue. In conclusion, the proposed MRF is a useful tool to identify novel mQTLs, especially for studies with limited sample sizes.
View details for DOI 10.1093/bib/bbab323
View details for Web of Science ID 000733325700191
View details for PubMedID 34414410
View details for PubMedCentralID PMC8575051
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The Association Between Cancer and Spousal Rate of Memory Decline A Negative Control Study to Evaluate (Unmeasured) Social Confounding of the Cancer-memory Relationship
ALZHEIMER DISEASE & ASSOCIATED DISORDERS
2021; 35 (3): 271-274
Abstract
Cancer diagnoses are associated with better long-term memory in older adults, possibly reflecting a range of social confounders that increase cancer risk but improve memory. We used spouse's memory as a negative control outcome to evaluate this possible confounding, since spouses share social characteristics and environments, and individuals' cancers are unlikely to cause better memory among their spouses. We estimated the association of an individual's incident cancer diagnosis (exposure) with their own (primary outcome) and their spouse's (negative control outcome) memory decline in 3601 couples from 1998 to 2014 in the Health and Retirement Study, using linear mixed-effects models. Incident cancer predicted better long-term memory for the diagnosed individual. We observed no association between an individual's cancer diagnosis and rate of spousal memory decline. This negative control study suggests that the inverse association between incident cancer and rate of memory decline is unlikely to be attributable to social/behavioral factors shared between spouses.
View details for DOI 10.1097/WAD.0000000000000398
View details for Web of Science ID 000690996800013
View details for PubMedID 32568784
View details for PubMedCentralID PMC7749066
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Inflammatory bowel disease induces inflammatory and preneoplastic changes in the prostate (May, 10.1038/s41391-021-00392-7, 2021)
PROSTATE CANCER AND PROSTATIC DISEASES
2022; 25 (2): 375
View details for DOI 10.1038/s41391-021-00409-1
View details for Web of Science ID 000664399600001
View details for PubMedID 34158596
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Inflammatory bowel disease induces inflammatory and pre-neoplastic changes in the prostate
PROSTATE CANCER AND PROSTATIC DISEASES
2022; 25 (3): 463-471
Abstract
Inflammatory bowel disease (IBD) has been implicated as a risk factor for prostate cancer, however, the mechanism of how IBD leads to prostate tumorigenesis is not known. Here, we investigated whether chronic intestinal inflammation leads to pro-inflammatory changes associated with tumorigenesis in the prostate.Using clinical samples of men with IBD who underwent prostatectomy, we analyzed whether prostate tumors had differences in lymphocyte infiltrate compared to non-IBD controls. In a mouse model of chemically-induced intestinal inflammation, we investigated whether chronic intestinal inflammation could be transferred to the wild-type mouse prostate. In addition, mouse prostates were evaluated for activation of pro-oncogenic signaling and genomic instability.A higher proportion of men with IBD had T and B lymphocyte infiltration within prostate tumors. Mice with chronic colitis showed significant increases in prostatic CD45 + leukocyte infiltration and elevation of three pro-inflammatory cytokines-TIMP-1, CCL5, and CXCL1 and activation of AKT and NF-kB signaling pathways. Lastly, mice with chronic colitis had greater prostatic oxidative stress/DNA damage, and prostate epithelial cells had undergone cell cycle arrest.These data suggest chronic intestinal inflammation is associated with an inflammatory-rich, pro-tumorigenic prostatic phenotype which may explain how gut inflammation fosters prostate cancer development in men with IBD.
View details for DOI 10.1038/s41391-021-00392-7
View details for Web of Science ID 000654094200001
View details for PubMedID 34035460
View details for PubMedCentralID PMC8647933
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A Large-Scale Association Study Detects Novel Rare Variants, Risk Genes, Functional Elements, and Polygenic Architecture of Prostate Cancer Susceptibility.
Cancer research
2021; 81 (7): 1695-1703
Abstract
To identify rare variants associated with prostate cancer susceptibility and better characterize the mechanisms and cumulative disease risk associated with common risk variants, we conducted an integrated study of prostate cancer genetic etiology in two cohorts using custom genotyping microarrays, large imputation reference panels, and functional annotation approaches. Specifically, 11,984 men (6,196 prostate cancer cases and 5,788 controls) of European ancestry from Northern California Kaiser Permanente were genotyped and meta-analyzed with 196,269 men of European ancestry (7,917 prostate cancer cases and 188,352 controls) from the UK Biobank. Three novel loci, including two rare variants (European ancestry minor allele frequency < 0.01, at 3p21.31 and 8p12), were significant genome wide in a meta-analysis. Gene-based rare variant tests implicated a known prostate cancer gene (HOXB13), as well as a novel candidate gene (ILDR1), which encodes a receptor highly expressed in prostate tissue and is related to the B7/CD28 family of T-cell immune checkpoint markers. Haplotypic patterns of long-range linkage disequilibrium were observed for rare genetic variants at HOXB13 and other loci, reflecting their evolutionary history. In addition, a polygenic risk score (PRS) of 188 prostate cancer variants was strongly associated with risk (90th vs. 40th-60th percentile OR = 2.62, P = 2.55 × 10-191). Many of the 188 variants exhibited functional signatures of gene expression regulation or transcription factor binding, including a 6-fold difference in log-probability of androgen receptor binding at the variant rs2680708 (17q22). Rare variant and PRS associations, with concomitant functional interpretation of risk mechanisms, can help clarify the full genetic architecture of prostate cancer and other complex traits. SIGNIFICANCE: This study maps the biological relationships between diverse risk factors for prostate cancer, integrating different functional datasets to interpret and model genome-wide data from over 200,000 men with and without prostate cancer.See related commentary by Lachance, p. 1637.
View details for DOI 10.1158/0008-5472.CAN-20-2635
View details for PubMedID 33293427
View details for PubMedCentralID PMC8137514
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Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry.
American journal of human genetics
2021
Abstract
Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.
View details for DOI 10.1016/j.ajhg.2021.02.011
View details for PubMedID 33713608
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Cell-free DNA concentration and fragment size as a biomarker for prostate cancer.
Scientific reports
2021; 11 (1): 5040
Abstract
Prostate cancer is the most commonly diagnosed neoplasm in American men. Although existing biomarkers may detect localized prostate cancer, additional strategies are necessary for improving detection and identifying aggressive disease that may require further intervention. One promising, minimally invasive biomarker is cell-free DNA (cfDNA), which consist of short DNA fragments released into circulation by dying or lysed cells that may reflect underlying cancer. Here we investigated whether differences in cfDNA concentration and cfDNA fragment size could improve the sensitivity for detecting more advanced and aggressive prostate cancer. This study included 268 individuals: 34 healthy controls, 112 men with localized prostate cancer who underwent radical prostatectomy (RP), and 122 men with metastatic castration-resistant prostate cancer (mCRPC). Plasma cfDNA concentration and fragment size were quantified with the Qubit 3.0 and the 2100 Bioanalyzer. The potential relationship between cfDNA concentration or fragment size and localized or mCRPC prostate cancer was evaluated with descriptive statistics, logistic regression, and area under the curve analysis with cross-validation. Plasma cfDNA concentrations were elevated in mCRPC patients in comparison to localized disease (OR5ng/mL=1.34, P=0.027) or to being a control (OR5ng/mL=1.69, P=0.034). Decreased average fragment size was associated with an increased risk of localized disease compared to controls (OR5bp=0.77, P=0.0008). This study suggests that while cfDNA concentration can identify mCRPC patients, it is unable to distinguish between healthy individuals and patients with localized prostate cancer. In addition to PSA, average cfDNA fragment size may be an alternative that can differentiate between healthy individuals and those with localized disease, but the low sensitivity and specificity results in an imperfect diagnostic marker. While quantification of cfDNA may provide a quick, cost-effective approach to help guide treatment decisions in advanced disease, its use is limited in the setting of localized prostate cancer.
View details for DOI 10.1038/s41598-021-84507-z
View details for PubMedID 33658587
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Cross-cancer evaluation of polygenic risk scores for 16 cancer types in two large cohorts.
Nature communications
2021; 12 (1): 970
Abstract
Even distinct cancer types share biological hallmarks. Here, we investigate polygenic risk score (PRS)-specific pleiotropy across 16 cancers in European ancestry individuals from the Genetic Epidemiology Research on Adult Health and Aging cohort (16,012 cases, 50,552 controls) and UK Biobank (48,969 cases, 359,802 controls). Within cohorts, each PRS is evaluated in multivariable logistic regression models against all other cancer types. Results are then meta-analyzed across cohorts. Ten positive and one inverse cross-cancer associations are found after multiple testing correction. Two pairs show bidirectional associations; the melanoma PRS is positively associated with oral cavity/pharyngeal cancer and vice versa, whereas the lung cancer PRS is positively associated with oral cavity/pharyngeal cancer, and the oral cavity/pharyngeal cancer PRS is inversely associated with lung cancer. Overall, we validate known, and uncover previously unreported, patterns of pleiotropy that have the potential to inform investigations of risk prediction, shared etiology, and precision cancer prevention strategies.
View details for DOI 10.1038/s41467-021-21288-z
View details for PubMedID 33579919
View details for PubMedCentralID PMC7880989
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A two-step approach to testing overall effect of gene-environment interaction for multiple phenotypes
BIOINFORMATICS
2020; 36 (24): 5640-5648
Abstract
While gene-environment (GxE) interactions contribute importantly to many different phenotypes, detecting such interactions requires well-powered studies and has proven difficult. To address this, we combine two approaches to improve GxE power: simultaneously evaluating multiple phenotypes and using a two-step analysis approach. Previous work shows that the power to identify a main genetic effect can be improved by simultaneously analyzing multiple related phenotypes. For a univariate phenotype, two-step methods produce higher power for detecting a GxE interaction compared to single step analysis. Therefore, we propose a two-step approach to test for an overall GxE effect for multiple phenotypes.Using simulations we demonstrate that, when more than one phenotype has GxE effect (i.e. GxE pleiotropy), our approach offers substantial gain in power (18-43%) to detect an aggregate-level GxE effect for a multivariate phenotype compared to an analogous two-step method to identify GxE effect for a univariate phenotype. We applied the proposed approach to simultaneously analyze three lipids, LDL, HDL and Triglyceride with the frequency of alcohol consumption as environmental factor in the UK Biobank. The method identified two loci with an overall GxE effect on the vector of lipids, one of which was missed by the competing approaches.We provide an R package MPGE implementing the proposed approach which is available from CRAN: https://cran.r-project.org/web/packages/MPGE/index.html.Supplementary data are available at Bioinformatics online.
View details for DOI 10.1093/bioinformatics/btaa1083
View details for Web of Science ID 000642297800010
View details for PubMedID 33453114
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Inclusion of variants discovered from diverse populations improves polygenic risk score transferability
HUMAN GENETICS AND GENOMICS ADVANCES
2021; 2 (1)
Abstract
The majority of polygenic risk scores (PRSs) have been developed and optimized in individuals of European ancestry and may have limited generalizability across other ancestral populations. Understanding aspects of PRSs that contribute to this issue and determining solutions is complicated by disease-specific genetic architecture and limited knowledge of sharing of causal variants and effect sizes across populations. Motivated by these challenges, we undertook a simulation study to assess the relationship between ancestry and the potential bias in PRSs developed in European ancestry populations. Our simulations show that the magnitude of this bias increases with increasing divergence from European ancestry, and this is attributed to population differences in linkage disequilibrium and allele frequencies of European-discovered variants, likely as a result of genetic drift. Importantly, we find that including into the PRS variants discovered in African ancestry individuals has the potential to achieve unbiased estimates of genetic risk across global populations and admixed individuals. We confirm our simulation findings in an analysis of hemoglobin A1c (HbA1c), asthma, and prostate cancer in the UK Biobank. Given the demonstrated improvement in PRS prediction accuracy, recruiting larger diverse cohorts will be crucial-and potentially even necessary-for enabling accurate and equitable genetic risk prediction across populations.
View details for DOI 10.1016/j.xhgg.2020.100017
View details for Web of Science ID 000787676000005
View details for PubMedID 33564748
View details for PubMedCentralID PMC7869832
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Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.
Nature genetics
2021
Abstract
Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.
View details for DOI 10.1038/s41588-020-00748-0
View details for PubMedID 33398198
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Cell-Free DNA Detection of Tumor Mutations in Heterogeneous, Localized Prostate Cancer Via Targeted, Multiregion Sequencing.
JCO precision oncology
2021; 5
Abstract
Cell-free DNA (cfDNA) may allow for minimally invasive identification of biologically relevant genomic alterations and genetically distinct tumor subclones. Although existing biomarkers may detect localized prostate cancer, additional strategies interrogating genomic heterogeneity are necessary for identifying and monitoring aggressive disease. In this study, we aimed to evaluate whether circulating tumor DNA can detect genomic alterations present in multiple regions of localized prostate tumor tissue.METHODS: Low-pass whole-genome and targeted sequencing with a machine-learning guided 2.5-Mb targeted panel were used to identify single nucleotide variants, small insertions and deletions (indels), and copy-number alterations in cfDNA. The majority of this study focuses on the subset of 21 patients with localized disease, although 45 total individuals were evaluated, including 15 healthy controls and nine men with metastatic castration-resistant prostate cancer. Plasma cfDNA was barcoded with duplex unique molecular identifiers. For localized cases, matched tumor tissue was collected from multiple regions (one to nine samples per patient) for comparison.RESULTS: Somatic tumor variants present in heterogeneous tumor foci from patients with localized disease were detected in cfDNA, and cfDNA mutational burden was found to track with disease severity. Somatic tissue alterations were identified in cfDNA, including nonsynonymous variants in FOXA1, PTEN, MED12, and ATM. Detection of these overlapping variants was associated with seminal vesicle invasion (P = .019) and with the number of variants initially found in the matched tumor tissue samples (P = .0005).CONCLUSION: Our findings demonstrate the potential of targeted cfDNA sequencing to detect somatic tissue alterations in heterogeneous, localized prostate cancer, especially in a setting where matched tumor tissue may be unavailable (ie, active surveillance or treatment monitoring).
View details for DOI 10.1200/PO.20.00428
View details for PubMedID 34250416
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Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction.
Nature communications
2020; 11 (1): 6084
Abstract
Cancer risk is determined by a complex interplay of environmental and heritable factors. Polygenic risk scores (PRS) provide a personalized genetic susceptibility profile that may be leveraged for disease prediction. Using data from the UK Biobank (413,753 individuals; 22,755 incident cancer cases), we quantify the added predictive value of integrating cancer-specific PRS with family history and modifiable risk factors for 16 cancers. We show that incorporating PRS measurably improves prediction accuracy for most cancers, but the magnitude of this improvement varies substantially. We also demonstrate that stratifying on levels of PRS identifies significantly divergent 5-year risk trajectories after accounting for family history and modifiable risk factors. At the population level, the top 20% of the PRS distribution accounts for 4.0% to 30.3% of incident cancer cases, exceeding the impact of many lifestyle-related factors. In summary, this study illustrates the potential for improving cancer risk assessment by integrating genetic risk scores.
View details for DOI 10.1038/s41467-020-19600-4
View details for PubMedID 33247094
View details for PubMedCentralID PMC7695829
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Association Between Alzheimer Disease and Cancer With Evaluation of Study Biases A Systematic Review and Meta-analysis
JAMA NETWORK OPEN
2020; 3 (11): e2025515
Abstract
Observational studies consistently report inverse associations between cancer and Alzheimer disease (AD). Shared inverse etiological mechanisms might explain this phenomenon, but a systematic evaluation of methodological biases in existing studies is needed.To systematically review and meta-analyze evidence on the association between cancer and subsequent AD, systematically identify potential methodological biases in studies, and estimate the influence of these biases on the estimated pooled association between cancer and AD.All-language publications were identified from PubMed, Embase, and PsycINFO databases through September 2, 2020.Longitudinal cohort studies and case-control studies on the risk of AD in older adults with a history of any cancer type, prostate cancer, breast cancer, colorectal cancer, or nonmelanoma skin cancer, relative to those with no cancer history.Two reviewers independently abstracted the data and evaluated study biases related to confounding, diagnostic bias, competing risks, or survival bias. Random-effects meta-analysis was used to provide pooled estimates of the association between cancer and AD. Metaregressions were used to evaluate whether the observed pooled estimate could be attributable to each bias. The study was designed and conducted according to the Preferring Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline.Incidence, hazard, or odds ratios for AD comparing older adults with vs without a previous cancer diagnosis.In total, 19 cohort studies and 3 case-control studies of the associations between any cancer type (n = 13), prostate cancer (n = 5), breast cancer (n = 1), and nonmelanoma skin cancer (n = 3) with AD were identified, representing 9 630 435 individuals. In all studies combined, cancer was associated with decreased AD incidence (cohort studies: random-effects hazard ratio, 0.89; 95% CI, 0.79-1.00; case-control studies: random-effects odds ratio, 0.75; 95% CI, 0.61-0.93). Studies with insufficient or inappropriate confounder control or greater likelihood of AD diagnostic bias had mean hazard ratios closer to the null value, indicating that these biases could not explain the observed inverse association. Competing risks bias was rare. Studies with greater likelihood of survival bias had mean hazard ratios farther from the null value.The weak inverse association between cancer and AD may reflect shared inverse etiological mechanisms or survival bias but is not likely attributable to diagnostic bias, competing risks bias, or insufficient or inappropriate control for potential confounding factors.
View details for DOI 10.1001/jamanetworkopen.2020.25515
View details for Web of Science ID 000593977500004
View details for PubMedID 33185677
View details for PubMedCentralID PMC7666424
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The landscape of host genetic factors involved in immune response to common viral infections.
Genome medicine
2020; 12 (1): 93
Abstract
BACKGROUND: Humans and viruses have co-evolved for millennia resulting in a complex host genetic architecture. Understanding the genetic mechanisms of immune response to viral infection provides insight into disease etiology and therapeutic opportunities.METHODS: We conducted a comprehensive study including genome-wide and transcriptome-wide association analyses to identify genetic loci associated with immunoglobulin G antibody response to 28 antigens for 16 viruses using serological data from 7924 European ancestry participants in the UK Biobank cohort.RESULTS: Signals in human leukocyte antigen (HLA) class II region dominated the landscape of viral antibody response, with 40 independent loci and 14 independent classical alleles, 7 of which exhibited pleiotropic effects across viral families. We identified specific amino acid (AA) residues that are associated with seroreactivity, the strongest associations presented in a range of AA positions within DRbeta1 at positions 11, 13, 71, and 74 for Epstein-Barr virus (EBV), Varicella zoster virus (VZV), human herpesvirus 7, (HHV7), and Merkel cell polyomavirus (MCV). Genome-wide association analyses discovered 7 novel genetic loci outside the HLA associated with viral antibody response (P<5.0*10-8), including FUT2 (19q13.33) for human polyomavirus BK (BKV), STING1 (5q31.2) for MCV, and CXCR5 (11q23.3) and TBKBP1 (17q21.32) for HHV7. Transcriptome-wide association analyses identified 114 genes associated with response to viral infection, 12 outside of the HLA region, including ECSCR: P=5.0*10-15 (MCV), NTN5: P=1.1*10-9 (BKV), and P2RY13: P=1.1*10-8 EBV nuclear antigen. We also demonstrated pleiotropy between viral response genes and complex diseases, from autoimmune disorders to cancer to neurodegenerative and psychiatric conditions.CONCLUSIONS: Our study confirms the importance of the HLA region in host response to viral infection and elucidates novel genetic determinants beyond the HLA that contribute to host-virus interaction.
View details for DOI 10.1186/s13073-020-00790-x
View details for PubMedID 33109261
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Pan-cancer study detects genetic risk variants and shared genetic basis in two large cohorts.
Nature communications
2020; 11 (1): 4423
Abstract
Deciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. Here, we undertake genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (408,786 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detect 21 genome-wide significant associations independent of previously reported results. Investigations of pleiotropy identify 12 cancer pairs exhibiting either positive or negative genetic correlations; 25 pleiotropic loci; and 100 independent pleiotropic variants, many of which are regulatory elements and/or influence cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.
View details for DOI 10.1038/s41467-020-18246-6
View details for PubMedID 32887889
View details for PubMedCentralID PMC7473862
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The competing risk of death and selective survival cannot fully explain the inverse cancer-dementia association
ALZHEIMERS & DEMENTIA
2020; 16 (12): 1696-1703
Abstract
We evaluated whether competing risk of death or selective survival could explain the reported inverse association between cancer history and dementia incidence (incidence rate ratio [IRR] ≈ 0.62-0.85).A multistate simulation model of a cancer- and dementia-free cohort of 65-year-olds was parameterized with real-world data (cancer and dementia incidence, mortality), assuming no effect of cancer on dementia (true IRR = 1.00). To introduce competing risk of death, cancer history increased mortality. To introduce selective survival, we included a factor (prevalence ranging from 10% to 50%) that reduced cancer mortality and dementia incidence (IRRs ranged from 0.30 to 0.90). We calculated IRRs for cancer history on dementia incidence in the simulated cohorts.Competing risk of death yielded unbiased cancer-dementia IRRs. With selective survival, bias was small (IRRs = 0.89 to 0.99), even under extreme scenarios.The bias induced by selective survival in simulations was too small to explain the observed inverse cancer-dementia link, suggesting other mechanisms drive this association.
View details for DOI 10.1002/alz.12168
View details for Web of Science ID 000626327000001
View details for PubMedID 32881307
View details for PubMedCentralID PMC7902336
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A machine learning approach to optimizing cell-free DNA sequencing panels: with an application to prostate cancer
BMC CANCER
2020; 20 (1): 820
Abstract
Cell-free DNA's (cfDNA) use as a biomarker in cancer is challenging due to genetic heterogeneity of malignancies and rarity of tumor-derived molecules. Here we describe and demonstrate a novel machine-learning guided panel design strategy for improving the detection of tumor variants in cfDNA. Using this approach, we first generated a model to classify and score candidate variants for inclusion on a prostate cancer targeted sequencing panel. We then used this panel to screen tumor variants from prostate cancer patients with localized disease in both in silico and hybrid capture settings.Whole Genome Sequence (WGS) data from 550 prostate tumors was analyzed to build a targeted sequencing panel of single point and small (< 200 bp) indel mutations, which was subsequently screened in silico against prostate tumor sequences from 5 patients to assess performance against commonly used alternative panel designs. The panel's ability to detect tumor-derived cfDNA variants was then assessed using prospectively collected cfDNA and tumor foci from a test set 18 prostate cancer patients with localized disease undergoing radical proctectomy.The panel generated from this approach identified as top candidates mutations in known driver genes (e.g. HRAS) and prostate cancer related transcription factor binding sites (e.g. MYC, AR). It outperformed two commonly used designs in detecting somatic mutations found in the cfDNA of 5 prostate cancer patients when analyzed in an in silico setting. Additionally, hybrid capture and 2500X sequencing of cfDNA molecules using the panel resulted in detection of tumor variants in all 18 patients of a test set, where 15 of the 18 patients had detected variants found in multiple foci.Machine learning-prioritized targeted sequencing panels may prove useful for broad and sensitive variant detection in the cfDNA of heterogeneous diseases. This strategy has implications for disease detection and monitoring when applied to the cfDNA isolated from prostate cancer patients.
View details for DOI 10.1186/s12885-020-07318-x
View details for Web of Science ID 000566944900002
View details for PubMedID 32859160
View details for PubMedCentralID PMC7456018
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Congenital diaphragmatic hernia and maternal dietary nutrient pathways and diet quality.
Birth defects research
2020
Abstract
INTRODUCTION: We examined the association of congenital diaphragmatic hernia (CDH) with maternal dietary intake, using semi-Bayes hierarchical models and principal components analysis to consider intake of nutrients that contribute to one-carbon metabolism and oxidative stress pathways, and a diet quality index.METHODS: We included data on 825 cases and 11,108 nonmalformed controls born from 1997-2011 whose mother participated in the National Birth Defects Prevention Study (NBDPS), a multisite, population-based case-control study. Exposure data were from maternal telephone interviews, which included a food frequency questionnaire. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were generated from logistic regression models that included nutritional factors as continuous variables and were adjusted for maternal energy intake, race-ethnicity, parity, and vitamin supplement intake.RESULTS: In the semi-Bayes hierarchical model that included all nutrients and confounders, riboflavin was the only nutrient for which the 95% CI excluded 1.0; the aOR for a 1SD increase was 0.83. The aORs were 0.79 (95% CI 0.69-0.91) for the one-carbon metabolism pathway score, 0.90 (95% CI 0.80-1.01) for oxidative stress, and 0.85 (95% CI 0.77-0.93) for diet quality (the aORs correspond to a 1 SD increase).CONCLUSIONS: The findings from this study provide some support for the hypothesis that better prepregnancy nutrition is associated with reduced risk for CDH. These results provide etiologic clues but should be interpreted with caution given the novelty of the investigation.
View details for DOI 10.1002/bdr2.1770
View details for PubMedID 32744808
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Genomewide Meta-Analysis Validates a Role for <i>S1PR1</i> in Microtubule Targeting Agent-Induced Sensory Peripheral Neuropathy
CLINICAL PHARMACOLOGY & THERAPEUTICS
2020; 108 (3): 625-634
Abstract
Microtubule targeting agents (MTAs) are anticancer therapies commonly prescribed for breast cancer and other solid tumors. Sensory peripheral neuropathy (PN) is the major dose-limiting toxicity for MTAs and can limit clinical efficacy. The current pharmacogenomic study aimed to identify genetic variations that explain patient susceptibility and drive mechanisms underlying development of MTA-induced PN. A meta-analysis of genomewide association studies (GWAS) from two clinical cohorts treated with MTAs (Cancer and Leukemia Group B (CALGB) 40502 and CALGB 40101) was conducted using a Cox regression model with cumulative dose to first instance of grade 2 or higher PN. Summary statistics from a GWAS of European subjects (n = 469) in CALGB 40502 that estimated cause-specific risk of PN were meta-analyzed with those from a previously published GWAS of European ancestry (n = 855) from CALGB 40101 that estimated the risk of PN. Novel single nucleotide polymorphisms in an enhancer region downstream of sphingosine-1-phosphate receptor 1 (S1PR1 encoding S1PR1 ; e.g., rs74497159, βCALGB 40101 per allele log hazard ratio (95% confidence interval (CI)) = 0.591 (0.254-0.928), βCALGB 40502 per allele log hazard ratio (95% CI) = 0.693 (0.334-1.053); PMETA = 3.62 × 10-7 ) were the most highly ranked associations based on P values with risk of developing grade 2 and higher PN. In silico functional analysis identified multiple regulatory elements and potential enhancer activity for S1PR1 within this genomic region. Inhibition of S1PR1 function in induced pluripotent stem cell-derived human sensory neurons shows partial protection against paclitaxel-induced neurite damage. These pharmacogenetic findings further support ongoing clinical evaluations to target S1PR1 as a therapeutic strategy for prevention and/or treatment of MTA-induced neuropathy.
View details for DOI 10.1002/cpt.1958
View details for Web of Science ID 000554398400001
View details for PubMedID 32562552
View details for PubMedCentralID PMC7718413
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A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans
AMER ASSOC CANCER RESEARCH. 2020
View details for DOI 10.1158/1538-7755.DISP19-PR05
View details for Web of Science ID 000580647800526
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Age-of-onset information helps identify 76 genetic variants associated with allergic disease
PLOS GENETICS
2020; 16 (6): e1008725
Abstract
Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.
View details for DOI 10.1371/journal.pgen.1008725
View details for Web of Science ID 000546949000001
View details for PubMedID 32603359
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Association between inflammatory bowel disease and prostate cancer: A large-scale, prospective, population-based study
INTERNATIONAL JOURNAL OF CANCER
2020; 147 (10): 2735-2742
Abstract
Inflammatory bowel disease (IBD) is an established risk factor for colorectal cancer. Recent reports suggesting IBD is also a risk factor for prostate cancer (PC) require further investigation. We studied 218 084 men in the population-based UK Biobank cohort, aged 40 to 69 at study entry between 2006 and 2010, with follow-up through mid-2015. We assessed the association between IBD and subsequent PC using multivariable Cox regression analyses, adjusting for age at assessment, ethnic group, UK region, smoking status, alcohol drinking frequency, body mass index, Townsend Deprivation Index, family history of PC and previous prostate-specific antigen testing. Mean age at study entry was 56 years, 94% of the men were white, and 1.1% (n = 2311) had a diagnosis of IBD. After a median follow-up of 78 months, men with IBD had an increased risk of PC (adjusted hazard ratio [aHR] = 1.31, 95% confidence interval [CI] = 1.03-1.67, P = .029). The association with PC was only among men with the ulcerative colitis (UC; aHR = 1.47, 95% CI = 1.11-1.95, P = .0070), and not Crohn's disease (aHR 1.06, 95% CI = 0.63-1.80, P = .82). Results are limited by lack of data on frequency of health care interactions. In a large-scale, prospective cohort study, we detected an association between IBD, and UC specifically, with incident PC diagnosis.
View details for DOI 10.1002/ijc.33048
View details for Web of Science ID 000536056500001
View details for PubMedID 32399975
View details for PubMedCentralID PMC7577830
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A meta-analysis of genome-wide association studies of multiple myeloma among men and women of African ancestry.
Blood advances
2020; 4 (1): 181–90
Abstract
Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 * 10-6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 * 10-12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.
View details for DOI 10.1182/bloodadvances.2019000491
View details for PubMedID 31935283
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Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility.
Nature communications
2020; 11 (1): 27
Abstract
Impaired lung function is often caused by cigarette smoking, making it challenging to disentangle its role in lung cancer susceptibility. Investigation of the shared genetic basis of these phenotypes in the UK Biobank and International Lung Cancer Consortium (29,266 cases, 56,450 controls) shows that lung cancer is genetically correlated with reduced forced expiratory volume in one second (FEV1: rg = 0.098, p = 2.3 × 10-8) and the ratio of FEV1 to forced vital capacity (FEV1/FVC: rg = 0.137, p = 2.0 × 10-12). Mendelian randomization analyses demonstrate that reduced FEV1 increases squamous cell carcinoma risk (odds ratio (OR) = 1.51, 95% confidence intervals: 1.21-1.88), while reduced FEV1/FVC increases the risk of adenocarcinoma (OR = 1.17, 1.01-1.35) and lung cancer in never smokers (OR = 1.56, 1.05-2.30). These findings support a causal role of pulmonary impairment in lung cancer etiology. Integrative analyses reveal that pulmonary function instruments, including 73 novel variants, influence lung tissue gene expression and implicate immune-related pathways in mediating the observed effects on lung carcinogenesis.
View details for DOI 10.1038/s41467-019-13855-2
View details for PubMedID 31911640
View details for PubMedCentralID PMC6946810
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The landscape of host genetic factors involved in infection to common viruses and SARS-CoV-2.
medRxiv : the preprint server for health sciences
2020
Abstract
Humans and viruses have co-evolved for millennia resulting in a complex host genetic architecture. Understanding the genetic mechanisms of immune response to viral infection provides insight into disease etiology and informs public health interventions.We conducted a comprehensive study linking germline genetic variation and gene expression with antibody response to 28 antigens for 16 viruses using serological data from 7924 participants in the UK Biobank cohort. Using test results from 2010 UK Biobank subjects, we also investigated genetic determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.Signals in human leukocyte antigen (HLA) class II region dominated the landscape of viral antibody response, with 40 independent loci and 14 independent classical alleles, 7 of which exhibited pleiotropic effects across viral families. Genome-wide association analyses discovered 7 novel genetic loci associated with viral antibody response (P<5.0×10-8), including FUT2 (19q13.33) for human polyomavirus BK (BKV), STING1 (5q31.2) for Merkel cell polyomavirus (MCV), as well as CXCR5 (11q23.3) and TBKBP1 (17q21.32) for human herpesvirus 7. Transcriptome-wide association analyses identified 114 genes associated with response to viral infection, 12 outside of the HLA region, including ECSCR: P=5.0×10-15 (MCV), NTN5: P=1.1×10-9 (BKV), and P2RY13: P=1.1×10-8 (Epstein-Barr virus nuclear antigen). We also demonstrated pleiotropy between viral response genes and complex diseases, such as C4A expression in varicella zoster virus and schizophrenia. Finally, our analyses of SARS-CoV-2 revealed the first genome-wide significant infection susceptibility signal in EHF, an epithelial-specific transcriptional repressor implicated in airway disease. Targeted analyses of expression quantitative trait loci suggest a possible role for tissue-specific ACE2 expression in modifying SARS-CoV-2 susceptibility.Our study confirms the importance of the HLA region in host response to viral infection and elucidates novel genetic determinants of host-virus interaction. Our results may have implications for complex disease etiology and COVID-19.
View details for DOI 10.1101/2020.05.01.20088054
View details for PubMedID 32511533
View details for PubMedCentralID PMC7273301
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Comprehensive Investigation of White Blood Cell and Gene Expression Profiles As Risk Factors for Multiple Myeloma in African Americans
AMER SOC HEMATOLOGY. 2019
View details for DOI 10.1182/blood-2019-129298
View details for Web of Science ID 000577164603111
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Development and pilot evaluation of a personalized decision support intervention for low risk prostate cancer patients
CANCER MEDICINE
2020; 9 (1): 125-132
Abstract
Development and pilot evaluation of a personalized decision support intervention to help men with early-stage prostate cancer choose among active surveillance, surgery, and radiation.We developed a decision aid featuring long-term survival and side effects data, based on focus group input and stakeholder endorsement. We trained premedical students to administer the intervention to newly diagnosed men with low-risk prostate cancer seen at the University of California, San Francisco. Before the intervention, and after the consultation with a urologist, we administered the Decision Quality Instrument for Prostate Cancer (DQI-PC). We hypothesized increases in two knowledge items from the DQI-PC: How many men diagnosed with early-stage prostate cancer will eventually die of prostate cancer? How much would waiting 3 months to make a treatment decision affect chances of survival? Correct answers were: "Most will die of something else" and "A little or not at all."The development phase involved 6 patients, 1 family member, 2 physicians, and 5 other health care providers. In our pilot test, 57 men consented, and 44 received the decision support intervention and completed knowledge surveys at both timepoints. Regarding the two knowledge items of interest, before the intervention, 35/56 (63%) answered both correctly, compared to 36/44 (82%) after the medical consultation (P = .04 by chi-square test).The intervention was associated with increased patient knowledge. Data from this pilot have guided the development of a larger scale randomized clinical trial to improve decision quality in men with prostate cancer being treated in community settings.
View details for DOI 10.1002/cam4.2685
View details for Web of Science ID 000495748100001
View details for PubMedID 31714037
View details for PubMedCentralID PMC6943165
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Germline testing in those at risk of prostate cancer.
The Canadian journal of urology
2019; 26 (5 Suppl 2): 31-33
Abstract
Men with germline mutations in DNA repair genes are at an increased risk of prostate cancer. These germline mutations are commonly seen in conjunction with somatic DNA repair gene mutations in prostate tumors. This indicates that men with a personal or family history of prostate cancer-as well as other cancer syndromes arising from mutations in DNA repair genes-should be considered for genetic testing and counseling.
View details for PubMedID 31629425
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Association of imputed prostate cancer transcriptome with disease risk reveals novel mechanisms (vol 10, 3107, 2019)
NATURE COMMUNICATIONS
2019; 10: 3948
Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
View details for DOI 10.1038/s41467-019-11810-9
View details for Web of Science ID 000482890500001
View details for PubMedID 31462633
View details for PubMedCentralID PMC6713745
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Association of imputed prostate cancer transcriptome with disease risk reveals novel mechanisms.
Nature communications
2019; 10 (1): 3107
Abstract
Here we train cis-regulatory models of prostate tissue gene expression and impute expression transcriptome-wide for 233,955 European ancestry men (14,616 prostate cancer (PrCa) cases, 219,339 controls) from two large cohorts. Among 12,014 genes evaluated in the UK Biobank, we identify 38 associated with PrCa, many replicating in the Kaiser Permanente RPGEH. We report the association of elevated TMPRSS2 expression with increased PrCa risk (independent of a previously-reported risk variant) and with increased tumoral expression of the TMPRSS2:ERG fusion-oncogene in The Cancer Genome Atlas, suggesting a novel germline-somatic interaction mechanism. Three novel genes, HOXA4, KLK1, and TIMM23, additionally replicate in the RPGEH cohort. Furthermore, 4 genes, MSMB, NCOA4, PCAT1, and PPP1R14A, are associated with PrCa in a trans-ethnic meta-analysis (N = 9117). Many genes exhibit evidence for allele-specific transcriptional activation by PrCa master-regulators (including androgen receptor) in Position Weight Matrix, Chip-Seq, and Hi-C experimental data, suggesting common regulatory mechanisms for the associated genes.
View details for DOI 10.1038/s41467-019-10808-7
View details for PubMedID 31308362
View details for PubMedCentralID PMC6629701
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A Genome-wide Association Study of Prostate Cancer in Latinos.
International journal of cancer
2019
Abstract
Latinos represent less than 1% of samples analyzed to date in genome-wide association studies of cancer. The clinical value of genetic information in guiding personalized medicine in populations of non-European ancestry will require additional discovery and risk locus characterization efforts across populations. In the present study, we performed a GWAS of PrCa in 2,820 Latino PrCa cases and 5,293 controls to search for novel PrCa risk loci and to examine the generalizability of known PrCa risk loci in Latino men. We also conducted a genetic admixture mapping scan to identify PrCa risk alleles associated with local ancestry. Genome-wide significant associations were observed with 84 variants all located at the known PrCa risk regions at 8q24 (128.484-128.548) and 10q11.22 (MSMB gene). In admixture mapping, we observed genome-wide significant associations with local African ancestry at 8q24. Of the 162 established PrCa risk variants that are common in Latino men, 135 (83.3%) had effects that were directionally consistent as previously reported, among which 55 (34.0%) were statistically significant with P<0.05. A polygenic risk model of the known PrCa risk variants showed that, compared to men with average risk (25th -75th percentile of the polygenic risk score distribution), men in the top 10% had a 3.19-fold (95% CI: 2.65, 3.84) increased PrCa risk. In conclusion, we found that the known PrCa risk variants can effectively stratify PrCa risk in Latino men. Larger studies in Latino populations will be required to discover and characterize genetic risk variants for PrCa and improve risk stratification for this population. This article is protected by copyright. All rights reserved.
View details for DOI 10.1002/ijc.32525
View details for PubMedID 31226226
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Personalized Prostate Cancer Screening Based on a Single Midlife Prostate-specific Antigen Measurement.
European urology
2019; 75 (3): 408-409
View details for DOI 10.1016/j.eururo.2018.09.019
View details for PubMedID 30268658
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A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance)
CLINICAL PHARMACOLOGY & THERAPEUTICS
2019; 105 (3): 738-745
Abstract
Genome-wide genotyping data are increasingly available for pharmacogenetic association studies, but application of these data for development of prediction models is limited. Prediction methods, such as elastic net regularization, have recently been applied to genetic studies but only limitedly to pharmacogenetic outcomes. An elastic net was applied to a pharmacogenetic study of progression-free survival (PFS) of 468 patients with advanced breast cancer in a clinical trial of paclitaxel, nab-paclitaxel, and ixabepilone. A final model included 13 single nucleotide polymorphisms (SNPs) in addition to clinical covariates (prior taxane status, hormone receptor status, disease-free interval, and presence of visceral metastases) with an area under the curve (AUC) integrated over time of 0.81, an increase compared to an AUC of 0.64 for a model with clinical covariates alone. This model may be of value in predicting PFS with microtubule targeting agents and may inform reverse translational studies to understand differential response to these drugs.
View details for DOI 10.1002/cpt.1241
View details for Web of Science ID 000458922600029
View details for PubMedID 30260474
View details for PubMedCentralID PMC6379108
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Identification of novel susceptibility loci and genes for prostate cancer risk: A transcriptome-wide association study in over 140,000 European descendants.
Cancer research
2019
Abstract
Genome-wide association studies have identified genetic variants associated with prostate cancer risk. However, these variants explain only a small fraction of the heritable component of prostate cancer risk, and the genes responsible for many of the identified associations remain unknown. To discover novel prostate cancer genetic loci and possible causal genes at previously identified risk loci, we performed a transcriptome-wide association study in 79,194 cases and 61,112 controls of European ancestry. Using data from the Genotype-Tissue Expression Project, we established genetic models to predict gene expression across the transcriptome for both prostate models and cross-tissue models and evaluated model performance using two independent datasets. We identified significant associations for 137 genes at P < 2.61×10-6, a Bonferroni-corrected threshold, including nine genes that remained significant at P < 2.61×10-6 after adjusting for all known prostate cancer risk variants in nearby regions. Of the 128 remaining associated genes, 94 have not yet been reported as potential target genes at known loci. We silenced 14 genes and many showed a consistent effect on viability and colony-forming efficiency in three cell lines. Our study provides substantial new information to advance our understanding of prostate cancer genetics and biology.
View details for DOI 10.1158/0008-5472.CAN-18-3536
View details for PubMedID 31101764
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Newborn Metabolic Profile Associated with Hyperbilirubinemia With and Without Kernicterus
CTS-CLINICAL AND TRANSLATIONAL SCIENCE
2019; 12 (1): 28-38
Abstract
Our objective was to assess the relationship between hyperbilirubinemia with and without kernicterus and metabolic profile at newborn screening. Included were 1,693,658 infants divided into a training or testing subset in a ratio of 3:1. Forty-two metabolites were analyzed using logistic regression (odds ratios (ORs), area under the receiver operating characteristic curve (AUC), 95% confidence intervals (CIs)). Several metabolite patterns remained consistent across gestational age groups for hyperbilirubinemia without kernicterus. Thyroid stimulating hormone (TSH) and C-18:2 were decreased, whereas tyrosine and C-3 were increased in infants across groupings. Increased C-3 was also observed for kernicterus (OR: 3.17; 95% CI: 1.18-8.53). Thirty-one metabolites were associated with hyperbilirubinemia without kernicterus in the training set. Phenylalanine (OR: 1.91; 95% CI: 1.85-1.97), ornithine (OR: 0.76; 95% 0.74-0.77), and isoleucine + leucine (OR: 0.63; 95% CI: 0.61-0.65) were the most strongly associated. This study showed that newborn metabolic function is associated with hyperbilirubinemia with and without kernicterus.
View details for DOI 10.1111/cts.12590
View details for Web of Science ID 000458454300004
View details for PubMedID 30369069
View details for PubMedCentralID PMC6342241
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Samasy: an automated system for sample selection and robotic transfer
BIOTECHNIQUES
2018; 65 (6): 357-360
Abstract
Sample automation and management is increasingly important as the number and size of population-scale and high-throughput projects grow. This is particularly the case in large-scale population studies where sample size is far outpacing the commonly used 96-well plate format. To facilitate management and transfer of samples in this format, we present Samasy, a web-based application for the construction of a sample database, intuitive display of sample and batch information, and facilitation of automated sample transfer or subset. Samasy is designed with ease-of-use in mind, can be quickly set up, and runs in any web browser.
View details for DOI 10.2144/btn-2018-0090
View details for Web of Science ID 000452398200010
View details for PubMedID 30477330
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Quantitative Spatial Profiling of PD-1/PD-L1 Interaction and HLA-DR/IDO-1 Predicts Improved Outcomes of Anti-PD-1 Therapies in Metastatic Melanoma.
Clinical cancer research : an official journal of the American Association for Cancer Research
2018; 24 (21): 5250-5260
Abstract
Purpose: PD-1/L1 axis-directed therapies produce clinical responses in a subset of patients; therefore, biomarkers of response are needed. We hypothesized that quantifying key immunosuppression mechanisms within the tumor microenvironment by multiparameter algorithms would identify strong predictors of anti-PD-1 response.Experimental Design: Pretreatment tumor biopsies from 166 patients treated with anti-PD-1 across 10 academic cancer centers were fluorescently stained with multiple markers in discovery (n = 24) and validation (n = 142) cohorts. Biomarker-positive cells and their colocalization were spatially profiled in pathologist-selected tumor regions using novel Automated Quantitative Analysis algorithms. Selected biomarker signatures, PD-1/PD-L1 interaction score, and IDO-1/HLA-DR coexpression were evaluated for anti-PD-1 treatment outcomes.Results: In the discovery cohort, PD-1/PD-L1 interaction score and/or IDO-1/HLA-DR coexpression was strongly associated with anti-PD-1 response (P = 0.0005). In contrast, individual biomarkers (PD-1, PD-L1, IDO-1, HLA-DR) were not associated with response or survival. This finding was replicated in an independent validation cohort: patients with high PD-1/PD-L1 and/or IDO-1/HLA-DR were more likely to respond (P = 0.0096). These patients also experienced significantly improved progression-free survival (HR = 0.36; P = 0.0004) and overall survival (HR = 0.39; P = 0.0011). In the combined cohort, 80% of patients exhibiting higher levels of PD-1/PD-L1 interaction scores and IDO-1/HLA-DR responded to PD-1 blockers (P = 0.000004). In contrast, PD-L1 expression was not predictive of survival.Conclusions: Quantitative spatial profiling of key tumor-immune suppression pathways by novel digital pathology algorithms could help more reliably select melanoma patients for PD-1 monotherapy. Clin Cancer Res; 24(21); 5250-60. ©2018 AACR.
View details for DOI 10.1158/1078-0432.CCR-18-0309
View details for PubMedID 30021908
View details for PubMedCentralID PMC6214750
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Two HLA Class II Gene Variants Are Independently Associated with Pediatric Osteosarcoma Risk
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2018; 27 (10): 1151-1158
Abstract
Background: The genetic etiology of osteosarcoma remains poorly understood despite the publication of a genome-wide association study. Association between HLA genetic variants and risk of several cancers has been observed, but HLA variation is not well captured by standard SNP arrays.Methods: We genotyped 207 Californian pediatric osteosarcoma cases and 696 controls of European ancestry using a custom genome-wide array supplemented with approximately 6,000 additional probes across the MHC region. We subsequently imputed 4-digit classical HLA alleles using a reference panel of 5,225 individuals who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for ancestry-informative principal components, and top associations from the discovery analysis underwent replication in an independent dataset of 657 cases and 1,183 controls.Results: Three highly correlated HLA class II variants (r 2 = 0.33-0.98) were associated with osteosarcoma risk in discovery analyses, including HLA-DRB1*0301 (OR = 0.52; P = 3.2 × 10-3), HLA-DQA1*0501 (OR = 0.74; P = 0.031), and HLA-DQB1*0201 (OR = 0.51; P = 2.7 × 10-3). Similar associations were observed in the replication data (P range = 0.011-0.037). Meta-analysis of the two datasets identified HLA-DRB1*0301 as the most significantly associated variant (ORmeta = 0.62; P meta = 1.5 × 10-4), reaching Bonferroni-corrected statistical significance. The meta-analysis also revealed a second significant independent signal at HLA-DQA1*01:01 (ORmeta = 1.33, P meta = 1.2 × 10-3), and a third suggestive association at HLA-DQB1*0302 (ORmeta = 0.73, P meta = 6.4 × 10-3).Conclusions: Multiple independent HLA class II alleles may influence osteosarcoma risk.Impact: Additional work is needed to extend our observations to other patient populations and to clarify the potential causal mechanisms underlying these associations. Understanding immunologic contributions to the etiology of osteosarcoma may inform rational therapeutic targets. Cancer Epidemiol Biomarkers Prev; 27(10); 1151-8. ©2018 AACR.
View details for DOI 10.1158/1055-9965.EPI-18-0306
View details for Web of Science ID 000446424800005
View details for PubMedID 30038050
View details for PubMedCentralID PMC6170682
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A Canadian genome-wide association study and meta-analysis confirm <i>HLA</i> as a risk factor for peanut allergy independent of asthma
JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY
2018; 141 (4): 1513-+
View details for DOI 10.1016/j.jaci.2017.10.047
View details for Web of Science ID 000429197800045
View details for PubMedID 29325868
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Orchid: a novel management, annotation and machine learning framework for analyzing cancer mutations
BIOINFORMATICS
2018; 34 (6): 936-942
Abstract
As whole-genome tumor sequence and biological annotation datasets grow in size, number and content, there is an increasing basic science and clinical need for efficient and accurate data management and analysis software. With the emergence of increasingly sophisticated data stores, execution environments and machine learning algorithms, there is also a need for the integration of functionality across frameworks.We present orchid, a python based software package for the management, annotation and machine learning of cancer mutations. Building on technologies of parallel workflow execution, in-memory database storage and machine learning analytics, orchid efficiently handles millions of mutations and hundreds of features in an easy-to-use manner. We describe the implementation of orchid and demonstrate its ability to distinguish tissue of origin in 12 tumor types based on 339 features using a random forest classifier.Orchid and our annotated tumor mutation database are freely available at https://github.com/wittelab/orchid. Software is implemented in python 2.7, and makes use of MySQL or MemSQL databases. Groovy 2.4.5 is optionally required for parallel workflow execution.JWitte@ucsf.edu.Supplementary data are available at Bioinformatics online.
View details for DOI 10.1093/bioinformatics/btx709
View details for Web of Science ID 000427887200005
View details for PubMedID 29106441
View details for PubMedCentralID PMC5860353
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Genome-wide association study and meta-analysis in multiple populations identifies new loci for peanut allergy and establishes <i>C11orf30/EMSY</i> as a genetic risk factor for food allergy
JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY
2018; 141 (3): 991-1001
Abstract
Peanut allergy (PA) is a complex disease with both environmental and genetic risk factors. Previously, PA loci were identified in filaggrin (FLG) and HLA in candidate gene studies, and loci in HLA were identified in a genome-wide association study and meta-analysis.We sought to investigate genetic susceptibility to PA.Eight hundred fifty cases and 926 hyper-control subjects and more than 7.8 million genotyped and imputed single nucleotide polymorphisms (SNPs) were analyzed in a genome-wide association study to identify susceptibility variants for PA in the Canadian population. A meta-analysis of 2 phenotypes (PA and food allergy) was conducted by using 7 studies from the Canadian, American (n = 2), Australian, German, and Dutch (n = 2) populations.An SNP near integrin α6 (ITGA6) reached genome-wide significance with PA (P = 1.80 × 10-8), whereas SNPs associated with Src kinase-associated phosphoprotein 1 (SKAP1), matrix metallopeptidase 12 (MMP12)/MMP13, catenin α3 (CTNNA3), rho GTPase-activating protein 24 (ARHGAP24), angiopoietin 4 (ANGPT4), chromosome 11 open reading frame (C11orf30/EMSY), and exocyst complex component 4 (EXOC4) reached a threshold suggestive of association (P ≤ 1.49 × 10-6). In the meta-analysis of PA, loci in or near ITGA6, ANGPT4, MMP12/MMP13, C11orf30, and EXOC4 were significant (P ≤ 1.49 × 10-6). When a phenotype of any food allergy was used for meta-analysis, the C11orf30 locus reached genome-wide significance (P = 7.50 × 10-11), whereas SNPs associated with ITGA6, ANGPT4, MMP12/MMP13, and EXOC4 and additional C11orf30 SNPs were suggestive (P ≤ 1.49 × 10-6). Functional annotation indicated that SKAP1 regulates expression of CBX1, which colocalizes with the EMSY protein coded by C11orf30.This study identifies multiple novel loci as risk factors for PA and food allergy and establishes C11orf30 as a risk locus for both PA and food allergy. Multiple genes (C11orf30/EMSY, SKAP1, and CTNNA3) identified by this study are involved in epigenetic regulation of gene expression.
View details for DOI 10.1016/j.jaci.2017.09.015
View details for Web of Science ID 000426974800019
View details for PubMedID 29030101
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An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations
PLOS GENETICS
2018; 14 (2): e1007139
Abstract
Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy). For a locus exhibiting overall pleiotropy, it is important to identify which specific traits underlie this association. We propose a Bayesian meta-analysis approach (termed CPBayes) that uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. This method uses a unified Bayesian statistical framework based on a spike and slab prior. CPBayes performs a fully Bayesian analysis by employing the Markov Chain Monte Carlo (MCMC) technique Gibbs sampling. It takes into account heterogeneity in the size and direction of the genetic effects across traits. It can be applied to both cohort data and separate studies of multiple traits having overlapping or non-overlapping subjects. Simulations show that CPBayes can produce higher accuracy in the selection of associated traits underlying a pleiotropic signal than the subset-based meta-analysis ASSET. We used CPBayes to undertake a genome-wide pleiotropic association study of 22 traits in the large Kaiser GERA cohort and detected six independent pleiotropic loci associated with at least two phenotypes. This includes a locus at chromosomal region 1q24.2 which exhibits an association simultaneously with the risk of five different diseases: Dermatophytosis, Hemorrhoids, Iron Deficiency, Osteoporosis and Peripheral Vascular Disease. We provide an R-package 'CPBayes' implementing the proposed method.
View details for DOI 10.1371/journal.pgen.1007139
View details for Web of Science ID 000426361900003
View details for PubMedID 29432419
View details for PubMedCentralID PMC5825176
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Identification of Pleiotropic Cancer Susceptibility Variants from Genome-Wide Association Studies Reveals Functional Characteristics
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2018; 27 (1): 75-85
Abstract
Background: There exists compelling evidence that some genetic variants are associated with the risk of multiple cancer sites (i.e., pleiotropy). However, the biological mechanisms through which the pleiotropic variants operate are unclear.Methods: We obtained all cancer risk associations from the National Human Genome Research Institute-European Bioinformatics Institute GWAS Catalog, and correlated cancer risk variants were clustered into groups. Pleiotropic variant groups and genes were functionally annotated. Associations of pleiotropic cancer risk variants with noncancer traits were also obtained.Results: We identified 1,431 associations between variants and cancer risk, comprised of 989 unique variants associated with 27 unique cancer sites. We found 20 pleiotropic variant groups (2.1%) composed of 33 variants (3.3%), including novel pleiotropic variants rs3777204 and rs56219066 located in the ELL2 gene. Relative to single-cancer risk variants, pleiotropic variants were more likely to be in genes (89.0% vs. 65.3%, P = 2.2 × 10-16), and to have somewhat larger risk allele frequencies (median RAF = 0.49 versus 0.39, P = 0.046). The 27 genes to which the pleiotropic variants mapped were suggestive for enrichment in response to radiation and hypoxia, alpha-linolenic acid metabolism, cell cycle, and extension of telomeres. In addition, we observed that 8 of 33 pleiotropic cancer risk variants were associated with 16 traits other than cancer.Conclusions: This study identified and functionally characterized genetic variants showing pleiotropy for cancer risk.Impact: Our findings suggest biological pathways common to different cancers and other diseases, and provide a basis for the study of genetic testing for multiple cancers and repurposing cancer treatments. Cancer Epidemiol Biomarkers Prev; 27(1); 75-85. ©2017 AACR.
View details for DOI 10.1158/1055-9965.EPI-17-0516
View details for Web of Science ID 000419551700008
View details for PubMedID 29150481
View details for PubMedCentralID PMC5760292
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Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology
NATURE GENETICS
2017; 49 (12): 1752-+
Abstract
Asthma, hay fever (or allergic rhinitis) and eczema (or atopic dermatitis) often coexist in the same individuals, partly because of a shared genetic origin. To identify shared risk variants, we performed a genome-wide association study (GWAS; n = 360,838) of a broad allergic disease phenotype that considers the presence of any one of these three diseases. We identified 136 independent risk variants (P < 3 × 10-8), including 73 not previously reported, which implicate 132 nearby genes in allergic disease pathophysiology. Disease-specific effects were detected for only six variants, confirming that most represent shared risk factors. Tissue-specific heritability and biological process enrichment analyses suggest that shared risk variants influence lymphocyte-mediated immunity. Six target genes provide an opportunity for drug repositioning, while for 36 genes CpG methylation was found to influence transcription independently of genetic effects. Asthma, hay fever and eczema partly coexist because they share many genetic risk variants that dysregulate the expression of immune-related genes.
View details for PubMedID 29083406
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Non-additive and epistatic effects of HLA polymorphisms contributing to risk of adult glioma
JOURNAL OF NEURO-ONCOLOGY
2017; 135 (2): 237-244
Abstract
Although genome-wide association studies have identified several susceptibility loci for adult glioma, little is known regarding the potential contribution of genetic variation in the human leukocyte antigen (HLA) region to glioma risk. HLA associations have been reported for various malignancies, with many studies investigating selected candidate HLA polymorphisms. However, no systematic analysis has been conducted in glioma patients, and no investigation into potential non-additive effects has been described. We conducted comprehensive genetic analyses of HLA variants among 1746 adult glioma patients and 2312 controls of European-ancestry from the GliomaScan Consortium. Genotype data were generated with the Illumina 660-Quad array, and we imputed HLA alleles using a reference panel of 5225 individuals in the Type 1 Diabetes Genetics Consortium who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for population stratification using ancestry-informative principal components. Because alleles in different loci across the HLA region are linked, we created multigene haplotypes consisting of the genes DRB1, DQA1, and DQB1. Although none of the haplotypes were associated with glioma in additive models, inclusion of a dominance term significantly improved the model for multigene haplotype HLA-DRB1*1501-DQA1*0102-DQB1*0602 (P = 0.002). Heterozygous carriers of the haplotype had an increased risk of glioma [odds ratio (OR) 1.23; 95% confidence interval (CI) 1.01-1.49], while homozygous carriers were at decreased risk compared with non-carriers (OR 0.64; 95% CI 0.40-1.01). Our results suggest that the DRB1*1501-DQA1*0102-DQB1*0602 haplotype may contribute to the risk of glioma in a non-additive manner, with the positive dominance effect partly explained by an epistatic interaction with HLA-DRB1*0401-DQA1*0301-DQB1*0301.
View details for DOI 10.1007/s11060-017-2569-7
View details for Web of Science ID 000414212300003
View details for PubMedID 28721485
View details for PubMedCentralID PMC5665694
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Up For A Challenge (U4C): Stimulating innovation in breast cancer genetic epidemiology
PLOS GENETICS
2017; 13 (9): e1006945
View details for DOI 10.1371/journal.pgen.1006945
View details for Web of Science ID 000411976100005
View details for PubMedID 28957327
View details for PubMedCentralID PMC5619686
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Two Novel Susceptibility Loci for Prostate Cancer in Men of African Ancestry
JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE
2017; 109 (8)
Abstract
Prostate cancer incidence is 1.6-fold higher in African Americans than in other populations. The risk factors that drive this disparity are unknown and potentially consist of social, environmental, and genetic influences. To investigate the genetic basis of prostate cancer in men of African ancestry, we performed a genome-wide association meta-analysis using two-sided statistical tests in 10 202 case subjects and 10 810 control subjects. We identified novel signals on chromosomes 13q34 and 22q12, with the risk-associated alleles found only in men of African ancestry (13q34: rs75823044, risk allele frequency = 2.2%, odds ratio [OR] = 1.55, 95% confidence interval [CI] = 1.37 to 1.76, P = 6.10 × 10-12; 22q12.1: rs78554043, risk allele frequency = 1.5%, OR = 1.62, 95% CI = 1.39 to 1.89, P = 7.50 × 10-10). At 13q34, the signal is located 5' of the gene IRS2 and 3' of a long noncoding RNA, while at 22q12 the candidate functional allele is a missense variant in the CHEK2 gene. These findings provide further support for the role of ancestry-specific germline variation in contributing to population differences in prostate cancer risk.
View details for PubMedID 29117387
View details for PubMedCentralID PMC5448553
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Familial Risk and Heritability of Colorectal Cancer in the Nordic Twin Study of Cancer
CLINICAL GASTROENTEROLOGY AND HEPATOLOGY
2017; 15 (8): 1256-1264
Abstract
We analyzed data from twins to determine how much the familial risk of colorectal cancer can be attributed to genetic factors vs environment. We also examined whether heritability is distinct for colon vs rectal cancer, given evidence of distinct etiologies.Our data set included 39,990 monozygotic and 61,443 same-sex dizygotic twins from the Nordic Twin Study of Cancer. We compared each cancer's risk in twins of affected co-twins relative to the cohort risk (familial risk ratio [FRR]). We then estimated the proportion of variation in risk that could be attributed to genetic factors (heritability).From earliest registration in 1943 through 2010, there were 1861 individuals diagnosed with colon cancer and 1268 diagnosed with rectal cancer. Monozygotic twins of affected co-twins had an FRR for colorectal cancer of 3.1 (95% confidence interval [CI], 2.4-3.8) relative to the cohort risk. Dizygotic twins of affected co-twins had an FRR for colorectal cancer of 2.2 (95% CI, 1.7-2.7). We estimated that 40% (95% CI, 33%-48%) of the variation in colorectal cancer risk could be attributed to genetic factors; unique environment only accounted for the remaining liability. For colon cancer, the FRR was 3.3 (95% CI, 2.1-4.5) for monozygotic twins and 2.6 (95% CI, 1.7-3.5) for dizygotic twins. For rectal cancer, comparable estimates were 3.3 (95% CI, 1.5-5.1) for monozygotic twins and 2.6 (95% CI, 1.2-4.0) for dizygotic twins. Heritability estimates for colon and rectal cancer were 16% (95% CI, 0-46%) and 15% (95% CI, 0-50%), common environment estimates were 15% (95% CI, 0-38%) and 11% (95% CI, 0-38%), and unique environment estimates were 68% (95% CI, 57%-79%) and 75% (95% CI, 61%-88%), respectively.Interindividual genetic differences could account for 40% of the variation in susceptibility to colorectal cancer; risk for colon and rectal cancers might have less of a genetic component than risk for colorectal cancer. Siblings, and particularly monozygotic co-twins, of individuals with colon or rectal cancer should consider personalized screening.
View details for DOI 10.1016/j.cgh.2016.12.041
View details for Web of Science ID 000405688900027
View details for PubMedID 28130150
View details for PubMedCentralID PMC5522647
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Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium
PLOS GENETICS
2017; 13 (4): e1006719
Abstract
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.
View details for PubMedID 28430825
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Investigating the Genetic Architecture of the PR Interval Using Clinical Phenotypes.
Circulation. Cardiovascular genetics
2017; 10 (2)
Abstract
BACKGROUND: One potential use for the PR interval is as a biomarker of disease risk. We hypothesized that quantifying the shared genetic architectures of the PR interval and a set of clinical phenotypes would identify genetic mechanisms contributing to PR variability and identify diseases associated with a genetic predictor of PR variability.METHODS AND RESULTS: We used ECG measurements from the ARIC study (Atherosclerosis Risk in Communities; n=6731 subjects) and 63 genetically modulated diseases from the eMERGE network (Electronic Medical Records and Genomics; n=12 978). We measured pairwise genetic correlations (rG) between PR phenotypes (PR interval, PR segment, P-wave duration) and each of the 63 phenotypes. The PR segment was genetically correlated with atrial fibrillation (rG=-0.88; P=0.0009). An analysis of metabolic phenotypes in ARIC also showed that the P wave was genetically correlated with waist circumference (rG=0.47; P=0.02). A genetically predicted PR interval phenotype based on 645 714 single-nucleotide polymorphisms was associated with atrial fibrillation (odds ratio=0.89 per SD change; 95% confidence interval, 0.83-0.95; P=0.0006). The differing pattern of associations among the PR phenotypes is consistent with analyses that show that the genetic correlation between the P wave and PR segment was not significantly different from 0 (rG=-0.03 [0.16]).CONCLUSIONS: The genetic architecture of the PR interval comprises modulators of atrial fibrillation risk and obesity.
View details for DOI 10.1161/CIRCGENETICS.116.001482
View details for PubMedID 28416512
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Tissue Sources for Accurate Measurement of Germline DNA Genotypes in Prostate Cancer Patients Treated With Radical Prostatectomy
PROSTATE
2017; 77 (4): 425-434
Abstract
Benign tissue from a tumor-containing organ is commonly the only available source for obtaining a patient's unmutated genome for use in cancer research. While it is critical to identify histologically normal tissue that is independent of the tumor lineage, few additional considerations are applied to the choice of this material for such measurements.Normal formalin-fixed, paraffin-embedded seminal vesicle, and urethral tissues, in addition to whole blood, were collected from 31 prostate cancer patients having undergone radical prostatectomy. Genotype concordance was evaluated for DNA from each tissue source in relation to whole blood.Overall, there was a greater genotype call rate for DNA derived from urethral tissue (97.0%) in comparison with patient-matched seminal vesicle tissues (95.9%, P = 0.0015). Furthermore, with reference to patient-matched whole blood, urethral samples exhibited higher genotype concordance (94.1%) than that of seminal vesicle samples (92.5%, P = 0.035).These findings highlight the heterogeneity between diverse sources of DNA in genotype measurement and motivate the consideration of normal tissue biases in tumor-normal analyses. Prostate 77: 425-434, 2017. © 2016 Wiley Periodicals, Inc.
View details for DOI 10.1002/pros.23283
View details for Web of Science ID 000393894100009
View details for PubMedID 27900799
View details for PubMedCentralID PMC5479703
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<i>Cis</i>-eQTL-based trans-ethnic meta-analysis reveals novel genes associated with breast cancer risk
PLOS GENETICS
2017; 13 (3): e1006690
Abstract
Breast cancer is the most common solid organ malignancy and the most frequent cause of cancer death among women worldwide. Previous research has yielded insights into its genetic etiology, but there remains a gap in the understanding of genetic factors that contribute to risk, and particularly in the biological mechanisms by which genetic variation modulates risk. The National Cancer Institute's "Up for a Challenge" (U4C) competition provided an opportunity to further elucidate the genetic basis of the disease. Our group leveraged the seven datasets made available by the U4C organizers and data from the publicly available UK Biobank cohort to examine associations between imputed gene expression and breast cancer risk. In particular, we used reference datasets describing the breast tissue and whole blood transcriptomes to impute expression levels in breast cancer cases and controls. In trans-ethnic meta-analyses of U4C and UK Biobank data, we found significant associations between breast cancer risk and the expression of RCCD1 (joint p-value: 3.6x10-06) and DHODH (p-value: 7.1x10-06) in breast tissue, as well as a suggestive association for ANKLE1 (p-value: 9.3x10-05). Expression of RCCD1 in whole blood was also suggestively associated with disease risk (p-value: 1.2x10-05), as were expression of ACAP1 (p-value: 1.9x10-05) and LRRC25 (p-value: 5.2x10-05). While genome-wide association studies (GWAS) have implicated RCCD1 and ANKLE1 in breast cancer risk, they have not identified the remaining three genes. Among the genetic variants that contributed to the predicted expression of the five genes, we found 23 nominally (p-value < 0.05) associated with breast cancer risk, among which 15 are not in high linkage disequilibrium with risk variants previously identified by GWAS. In summary, we used a transcriptome-based approach to investigate the genetic underpinnings of breast carcinogenesis. This approach provided an avenue for deciphering the functional relevance of genes and genetic variants involved in breast cancer.
View details for DOI 10.1371/journal.pgen.1006690
View details for Web of Science ID 000398043000004
View details for PubMedID 28362817
View details for PubMedCentralID PMC5391966
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Genome-wide association study of prostate-specific antigen levels identifies novel loci independent of prostate cancer
NATURE COMMUNICATIONS
2017; 8: 14248
Abstract
Prostate-specific antigen (PSA) levels have been used for detection and surveillance of prostate cancer (PCa). However, factors other than PCa-such as genetics-can impact PSA. Here we present findings from a genome-wide association study (GWAS) of PSA in 28,503 Kaiser Permanente whites and 17,428 men from replication cohorts. We detect 40 genome-wide significant (P<5 × 10-8) single-nucleotide polymorphisms (SNPs): 19 novel, 15 previously identified for PSA (14 of which were also PCa-associated), and 6 previously identified for PCa only. Further analysis incorporating PCa cases suggests that at least half of the 40 SNPs are PSA-associated independent of PCa. The 40 SNPs explain 9.5% of PSA variation in non-Hispanic whites, and the remaining GWAS SNPs explain an additional 31.7%; this percentage is higher in younger men, supporting the genetic basis of PSA levels. These findings provide important information about genetic markers for PSA that may improve PCa screening, thereby reducing over-diagnosis and over-treatment.
View details for DOI 10.1038/ncomms14248
View details for Web of Science ID 000392953600001
View details for PubMedID 28139693
View details for PubMedCentralID PMC5290311
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Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases.
American journal of epidemiology
2017; 186 (7): 753–61
Abstract
Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G×Es) in large-scale studies of human populations. There are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G×E discovery. This paper highlights current and critical issues and themes in G×E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.
View details for DOI 10.1093/aje/kwx227
View details for PubMedID 28978193
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Telomere structure and maintenance gene variants and risk of five cancer types.
International journal of cancer
2016; 139 (12): 2655-2670
Abstract
Telomeres cap chromosome ends, protecting them from degradation, double-strand breaks, and end-to-end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset-based meta-analyses of 204,993 directly-measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene-level p value cutoffs ≤3.08 × 10(-5) ). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere-related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.
View details for DOI 10.1002/ijc.30288
View details for PubMedID 27459707
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Telomere structure and maintenance gene variants and risk of five cancer types
INTERNATIONAL JOURNAL OF CANCER
2016; 139 (12): 2655-2670
Abstract
Telomeres cap chromosome ends, protecting them from degradation, double-strand breaks, and end-to-end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset-based meta-analyses of 204,993 directly-measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene-level p value cutoffs ≤3.08 × 10(-5) ). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere-related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.
View details for DOI 10.1002/ijc.30288
View details for Web of Science ID 000387619400003
View details for PubMedCentralID PMC5198774
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A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2016; 25 (12): 1609-1618
Abstract
Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma.We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality.We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry-European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4 Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10(-7)) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7 CONCLUSIONS: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles.A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609-18. ©2016 AACR.
View details for PubMedID 27587788
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Sequence variation in folate pathway genes and risks of human cleft lip with or without cleft palate.
American journal of medical genetics. Part A
2016; 170 (11): 2777-2787
Abstract
In an effort to comprehensively interrogate genetic variation in the folate pathway for risk of cleft lip with or without cleft palate (CLP), we evaluated 504 common and rare variants in 35 folate-related genes in a panel of 330 infants with CLP and 367 non-malformed controls. Odds ratios (OR) with 95% confidence intervals were computed for common genotypes. A Case-Control Difference metric was calculated for rare variants to highlight differentially occurring alleles. Interactions between variants and a maternal folate intake variable were also evaluated. In gene-only results, significant odds ratios were observed for multiple variants in the BHMT/BHMT2/DMGDH gene cluster, particularly in Hispanic infants. Also in this cluster, rare variant analysis highlighted a substantial case-control difference in BHMT rs60340837 (synonymous Y284Y). In Hispanics, the ALDH1L1 I812V variant (rs4646750) was the most significant risk allele: OR = 3.8 (95%CI = 1.6-9.2) when heterozygous. In non-Hispanic white infants, we observed significant risk for AHCYL2 rs1095423 (homozygous OR = 3.0, 95%CI 1.1-7.8) and the 68 bp CBS insertion (c.844ins68; heterozygous OR = 2.4, 95%CI = 1.1-5.3). Rare variant analysis in this group revealed case-control differences in MTRR and several other methionine cycle genes, a process implicated previously in clefting risk. In women with low folate intake specifically, increased risks were observed for CBS rs2851391 (OR = 3.6, 95%CI = 1.3-9.6) and the R259P nonsynonymous variant of TCN2 (rs1801198; OR = 2.8, 95%CI = 1.2-6.3). This comprehensive study provides further direction on candidate loci to help disentangle the folate-related developmental phenomena in human clefting risk. © 2016 Wiley Periodicals, Inc.
View details for DOI 10.1002/ajmg.a.37874
View details for PubMedID 27604992
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Variation in the glucose transporter gene <i>SLC2A2</i> is associated with glycemic response to metformin
NATURE GENETICS
2016; 48 (9): 1055-+
Abstract
Metformin is the first-line antidiabetic drug with over 100 million users worldwide, yet its mechanism of action remains unclear. Here the Metformin Genetics (MetGen) Consortium reports a three-stage genome-wide association study (GWAS), consisting of 13,123 participants of different ancestries. The C allele of rs8192675 in the intron of SLC2A2, which encodes the facilitated glucose transporter GLUT2, was associated with a 0.17% (P = 6.6 × 10(-14)) greater metformin-induced reduction in hemoglobin A1c (HbA1c) in 10,577 participants of European ancestry. rs8192675 was the top cis expression quantitative trait locus (cis-eQTL) for SLC2A2 in 1,226 human liver samples, suggesting a key role for hepatic GLUT2 in regulation of metformin action. Among obese individuals, C-allele homozygotes at rs8192675 had a 0.33% (3.6 mmol/mol) greater absolute HbA1c reduction than T-allele homozygotes. This was about half the effect seen with the addition of a DPP-4 inhibitor, and equated to a dose difference of 550 mg of metformin, suggesting rs8192675 as a potential biomarker for stratified medicine.
View details for DOI 10.1038/ng.3632
View details for Web of Science ID 000382398800017
View details for PubMedID 27500523
View details for PubMedCentralID PMC5007158
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Joint effects of genetic variants and residential proximity to pesticide applications on hypospadias risk.
Birth defects research. Part A, Clinical and molecular teratology
2016; 106 (8): 653-658
Abstract
We examined risks associated with joint exposure of gene variants and pesticides.Analyses included 189 cases and 390 male controls born from 1991 to 2003 in California's San Joaquin Valley. We used logistic regression to examine risks associated with joint exposures of gene variants and pesticides that our previous work identified as associated with hypospadias. Genetic variables were based on variants in DGKK, genes involved in sex steroid synthesis/metabolism, and genes involved in genital tubercle development. Pesticide exposure was based on residential proximity to commercial agricultural pesticide applications.Odds ratios (ORs) were highest among babies with joint exposures, who had two- to fourfold increased risks; for example, the OR was 3.7 (95% confidence interval [CI], 0.8-16.5) among subjects with the risk-associated DGKK haplotype and pesticide exposure; OR, 1.5 (95% CI, 0.7-3.1) among subjects with the haplotype and no pesticide exposure; and OR, 0.9 (95% CI, 0.5-1.6) among subjects without the haplotype but with pesticide exposure, relative to subjects with neither. However, results did not provide statistical evidence that these risks were significantly greater than expected on an additive scale, relative to risks associated with one exposure at a time.We observed elevated risks associated with joint exposures to selected pesticides and genetic variants but no statistical evidence for interaction. Birth Defects Research (Part A) 106:653-658, 2016. © 2016 Wiley Periodicals, Inc.
View details for DOI 10.1002/bdra.23508
View details for PubMedID 27098078
View details for PubMedCentralID PMC4983249
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Erratum to: Hierarchical modeling identifies novel lung cancer susceptibility variants in inflammation pathways among 10,140 cases and 11,012 controls.
Human genetics
2016; 135 (8): 963
View details for DOI 10.1007/s00439-016-1692-4
View details for PubMedID 27264937
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Host genetic predictors of the kynurenine pathway of tryptophan catabolism among treated HIV-infected Ugandans
AIDS
2016; 30 (11): 1807-1815
Abstract
Plasma kynurenine/tryptophan ratio, a biomarker of indoleamine 2,3-dioxygenase-1 (IDO) activity, is a strong independent predictor of mortality in HIV-infected Ugandans initiating antiretroviral therapy (ART) and may play a key role in HIV pathogenesis. We performed a genome-wide study to identify potential host genetic determinants of kynurenine/tryptophan ratio in HIV-infected ART-suppressed Ugandans.We performed genome-wide and exome array genotyping and measured plasma kynurenine/tryptophan ratio during the initial 6-12 months of suppressive ART in Ugandans. We evaluated more than 16 million single nucleotide polymorphisms in association with log10 kynurenine/tryptophan ratio using linear mixed models adjusted for cohort, sex, pregnancy, and ancestry.Among 597 Ugandans, 62% were woman, median age was 35, median baseline CD4 cell count was 135 cells/μl, and median baseline HIV-1 RNA was 5.1 log10 copies/ml. Several polymorphisms in candidate genes TNF, IFNGR1, and TLR4 were associated with log10 kynurenine/tryptophan ratio (P < 5.0 × 10). An intergenic polymorphism between CSPG5 and ELP6 was genome-wide significant, whereas several others exhibited suggestive associations (P < 5.0 × 10), including genes encoding protein tyrosine phosphatases (PTPRM and PTPRN2) and the vitamin D metabolism gene, CYP24A1. Several of these single nucleotide polymorphisms were associated with markers of inflammation, coagulation, and monocyte activation, but did not replicate in a small US cohort (N = 262; 33% African-American).Our findings highlight a potentially important role of IFN-γ, TNF-α, and Toll-like receptor signaling in determining IDO activity and subsequent mortality risk in HIV-infected ART-suppressed Ugandans. These results also identify potential novel pathways involved in IDO immunoregulation. Further studies are needed to confirm these findings in treated HIV-infected populations.
View details for DOI 10.1097/QAD.0000000000001124
View details for Web of Science ID 000379665100015
View details for PubMedID 27088321
View details for PubMedCentralID PMC4925250
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Prostate Cancer Susceptibility in Men of African Ancestry at 8q24.
Journal of the National Cancer Institute
2016; 108 (7)
Abstract
The 8q24 region harbors multiple risk variants for distinct cancers, including >8 for prostate cancer. In this study, we conducted fine mapping of the 8q24 risk region (127.8-128.8Mb) in search of novel associations with common and rare variation in 4853 prostate cancer case patients and 4678 control subjects of African ancestry. All statistical tests were two-sided. We identified three independent associations at P values of less than 5.00×10(-8), all of which were replicated in studies from Ghana and Uganda (combined sample = 5869 case patients, 5615 control subjects; rs114798100: risk allele frequency [RAF] = 0.04, per-allele odds ratio [OR] = 2.31, 95% confidence interval [CI] = 2.04 to 2.61, P = 2.38×10(-40); rs72725879: RAF = 0.33, OR = 1.37, 95% CI = 1.30 to 1.45, P = 3.04×10(-27); and rs111906932: RAF = 0.03, OR = 1.79, 95% CI = 1.53 to 2.08, P = 1.39×10(-13)). Risk variants rs114798100 and rs111906923 are only found in men of African ancestry, with rs111906923 representing a novel association signal. The three variants are located within or near a number of prostate cancer-associated long noncoding RNAs (lncRNAs), including PRNCR1, PCAT1, and PCAT2. These findings highlight ancestry-specific risk variation and implicate prostate-specific lncRNAs at the 8q24 prostate cancer susceptibility region.
View details for DOI 10.1093/jnci/djv431
View details for PubMedID 26823525
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Determining Which Phenotypes Underlie a Pleiotropic Signal
GENETIC EPIDEMIOLOGY
2016; 40 (5): 366-381
Abstract
Discovering pleiotropic loci is important to understand the biological basis of seemingly distinct phenotypes. Most methods for assessing pleiotropy only test for the overall association between genetic variants and multiple phenotypes. To determine which specific traits are pleiotropic, we evaluate via simulation and application three different strategies. The first is model selection techniques based on the inverse regression of genotype on phenotypes. The second is a subset-based meta analysis ASSET [Bhattacharjee et al., ], which provides an optimal subset of nonnull traits. And the third is a modified Benjamini-Hochberg (B-H) procedure of controlling the expected false discovery rate [Benjamini and Hochberg, ] in the framework of phenome-wide association study. From our simulations we see that an inverse regression-based approach MultiPhen [O'Reilly et al., ] is more powerful than ASSET for detecting overall pleiotropic association, except for when all the phenotypes are associated and have genetic effects in the same direction. For determining which specific traits are pleiotropic, the modified B-H procedure performs consistently better than the other two methods. The inverse regression-based selection methods perform competitively with the modified B-H procedure only when the phenotypes are weakly correlated. The efficiency of ASSET is observed to lie below and in between the efficiency of the other two methods when the traits are weakly and strongly correlated, respectively. In our application to a large GWAS, we find that the modified B-H procedure also performs well, indicating that this may be an optimal approach for determining the traits underlying a pleiotropic signal.
View details for DOI 10.1002/gepi.21973
View details for Web of Science ID 000379073200002
View details for PubMedID 27238845
View details for PubMedCentralID PMC4929010
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Selection and explosive growth alter genetic architecture and hamper the detection of causal rare variants
GENOME RESEARCH
2016; 26 (7): 863-873
Abstract
The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature.
View details for DOI 10.1101/gr.202440.115
View details for Web of Science ID 000378986000001
View details for PubMedID 27197206
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Association of common genetic variation in the protein C pathway genes with clinical outcomes in acute respiratory distress syndrome
CRITICAL CARE
2016; 20: 151
Abstract
Altered plasma levels of protein C, thrombomodulin, and the endothelial protein C receptor are associated with poor clinical outcomes in patients with acute respiratory distress syndrome (ARDS). We hypothesized that common variants in these genes would be associated with mortality as well as ventilator-free and organ failure-free days in patients with ARDS.We genotyped linkage disequilibrium-based tag single-nucleotide polymorphisms in the ProteinC, Thrombomodulin and Endothelial Protein C Reptor Genes among 320 self-identified white patients of European ancestry from the ARDS Network Fluid and Catheter Treatment Trial. We then tested their association with mortality as well as ventilator-free and organ-failure free days.The GG genotype of rs1042580 (p = 0.02) and CC genotype of rs3716123 (p = 0.002), both in the thrombomodulin gene, and GC/CC genotypes of rs9574 (p = 0.04) in the endothelial protein C receptor gene were independently associated with increased mortality. An additive effect on mortality (p < 0.001), ventilator-free days (p = 0.01), and organ failure-free days was observed with combinations of these high-risk genotypes. This association was independent of age, severity of illness, presence or absence of sepsis, and treatment allocation.Genetic variants in thrombomodulin and endothelial protein C receptor genes are additively associated with mortality in ARDS. These findings suggest that genetic differences may be at least partially responsible for the observed associations between dysregulated coagulation and poor outcomes in ARDS.
View details for DOI 10.1186/s13054-016-1330-5
View details for Web of Science ID 000376235800001
View details for PubMedID 27215212
View details for PubMedCentralID PMC4876559
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Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation
NATURE COMMUNICATIONS
2016; 7
Abstract
Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.
View details for DOI 10.1038/ncomms10979
View details for PubMedID 27052111
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Identifying genetically driven clinical phenotypes using linear mixed models
NATURE COMMUNICATIONS
2016; 7: 11433
Abstract
We hypothesized that generalized linear mixed models (GLMMs), which estimate the additive genetic variance underlying phenotype variability, would facilitate rapid characterization of clinical phenotypes from an electronic health record. We evaluated 1,288 phenotypes in 29,349 subjects of European ancestry with single-nucleotide polymorphism (SNP) genotyping on the Illumina Exome Beadchip. We show that genetic liability estimates are primarily driven by SNPs identified by prior genome-wide association studies and SNPs within the human leukocyte antigen (HLA) region. We identify 44 (false discovery rate q<0.05) phenotypes associated with HLA SNP variation and show that hypothyroidism is genetically correlated with Type I diabetes (rG=0.31, s.e. 0.12, P=0.003). We also report novel SNP associations for hypothyroidism near HLA-DQA1/HLA-DQB1 at rs6906021 (combined odds ratio (OR)=1.2 (95% confidence interval (CI): 1.1-1.2), P=9.8 × 10(-11)) and for polymyalgia rheumatica near C6orf10 at rs6910071 (OR=1.5 (95% CI: 1.3-1.6), P=1.3 × 10(-10)). Phenome-wide application of GLMMs identifies phenotypes with important genetic drivers, and focusing on these phenotypes can identify novel genetic associations.
View details for DOI 10.1038/ncomms11433
View details for Web of Science ID 000374685700001
View details for PubMedID 27109359
View details for PubMedCentralID PMC4848547
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Mutational Landscape of Aggressive Prostate Tumors in African American Men
CANCER RESEARCH
2016; 76 (7): 1860-1868
Abstract
Prostate cancer is the most frequently diagnosed and second most fatal nonskin cancer among men in the United States. African American men are two times more likely to develop and die of prostate cancer compared with men of other ancestries. Previous whole genome or exome tumor-sequencing studies of prostate cancer have primarily focused on men of European ancestry. In this study, we sequenced and characterized somatic mutations in aggressive (Gleason ≥7, stage ≥T2b) prostate tumors from 24 African American patients. We describe the locations and prevalence of small somatic mutations (up to 50 bases in length), copy number aberrations, and structural rearrangements in the tumor genomes compared with patient-matched normal genomes. We observed several mutation patterns consistent with previous studies, such as large copy number aberrations in chromosome 8 and complex rearrangement chains. However, TMPRSS2-ERG gene fusions and PTEN losses occurred in only 21% and 8% of the African American patients, respectively, far less common than in patients of European ancestry. We also identified mutations that appeared specific to or more common in African American patients, including a novel CDC27-OAT gene fusion occurring in 17% of patients. The genomic aberrations reported in this study warrant further investigation of their biologic significant role in the incidence and clinical outcomes of prostate cancer in African Americans. Cancer Res; 76(7); 1860-8. ©2016 AACR.
View details for DOI 10.1158/0008-5472.CAN-15-1787
View details for Web of Science ID 000374169600021
View details for PubMedID 26921337
View details for PubMedCentralID PMC4772140
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A Cross-Cancer Genetic Association Analysis of the DNA Repair and DNA Damage Signaling Pathways for Lung, Ovary, Prostate, Breast, and Colorectal Cancer
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2016; 25 (1): 193-200
Abstract
DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility.We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling.We identified three susceptibility DNA repair genes, RAD51B (P < 5.09 × 10(-6)), MSH5 (P < 5.09 × 10(-6)), and BRCA2 (P = 5.70 × 10(-6)). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways.Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways.Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria.
View details for DOI 10.1158/1055-9965.EPI-15-0649
View details for Web of Science ID 000372171400025
View details for PubMedID 26637267
View details for PubMedCentralID PMC4713268
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Semiparametric Allelic Tests for Mapping Multiple Phenotypes: Binomial Regression and Mahalanobis Distance
GENETIC EPIDEMIOLOGY
2015; 39 (8): 635-650
Abstract
Binary phenotypes commonly arise due to multiple underlying quantitative precursors and genetic variants may impact multiple traits in a pleiotropic manner. Hence, simultaneously analyzing such correlated traits may be more powerful than analyzing individual traits. Various genotype-level methods, e.g., MultiPhen (O'Reilly et al. []), have been developed to identify genetic factors underlying a multivariate phenotype. For univariate phenotypes, the usefulness and applicability of allele-level tests have been investigated. The test of allele frequency difference among cases and controls is commonly used for mapping case-control association. However, allelic methods for multivariate association mapping have not been studied much. In this article, we explore two allelic tests of multivariate association: one using a Binomial regression model based on inverted regression of genotype on phenotype (Binomial regression-based Association of Multivariate Phenotypes [BAMP]), and the other employing the Mahalanobis distance between two sample means of the multivariate phenotype vector for two alleles at a single-nucleotide polymorphism (Distance-based Association of Multivariate Phenotypes [DAMP]). These methods can incorporate both discrete and continuous phenotypes. Some theoretical properties for BAMP are studied. Using simulations, the power of the methods for detecting multivariate association is compared with the genotype-level test MultiPhen's. The allelic tests yield marginally higher power than MultiPhen for multivariate phenotypes. For one/two binary traits under recessive mode of inheritance, allelic tests are found to be substantially more powerful. All three tests are applied to two different real data and the results offer some support for the simulation study. We propose a hybrid approach for testing multivariate association that implements MultiPhen when Hardy-Weinberg Equilibrium (HWE) is violated and BAMP otherwise, because the allelic approaches assume HWE.
View details for DOI 10.1002/gepi.21930
View details for Web of Science ID 000366605200005
View details for PubMedID 26493781
View details for PubMedCentralID PMC4958458
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Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions.
Human molecular genetics
2015; 24 (19): 5603-5618
Abstract
Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10(-4)-5.6 × 10(-3)) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10(-6)) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation.
View details for DOI 10.1093/hmg/ddv269
View details for PubMedID 26162851
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Strategies for Imputing and Analyzing Rare Variants in Association Studies
TRENDS IN GENETICS
2015; 31 (10): 556-563
Abstract
Rare genetic variants may be responsible for a significant amount of the uncharacterized genetic risk underlying many diseases. An efficient approach to characterizing the disease burden of rare variants may be to impute them into existing large datasets. It is well known that the ability to impute a rare variant is dependent both on the array choice and number of individuals in the reference panel carrying that variant, although it is still unclear exactly how well imputation will work for rare variants. Here, we review the additional challenges that arise when imputing rare variants, looking at studies that have been able to impute rare variants, methods behind merging reference panels, approaches for imputing rare variants, and methods for analyzing rare variants.
View details for DOI 10.1016/j.tig.2015.07.006
View details for Web of Science ID 000363349900003
View details for PubMedID 26450338
View details for PubMedCentralID PMC4600126
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Detecting gene-environment interactions in human birth defects: Study designs and statistical methods
BIRTH DEFECTS RESEARCH PART A-CLINICAL AND MOLECULAR TERATOLOGY
2015; 103 (8): 692-702
Abstract
The National Birth Defects Prevention Study (NBDPS) contains a wealth of information on affected and unaffected family triads, and thus provides numerous opportunities to study gene-environment interactions (G×E) in the etiology of birth defect outcomes. Depending on the research objective, several analytic options exist to estimate G×E effects that use varying combinations of individuals drawn from available triads.In this study, we discuss important considerations in the collection of genetic data and environmental exposures.We will also present several population- and family-based approaches that can be applied to data from the NBDPS including case-control, case-only, family-based trio, and maternal versus fetal effects. For each, we describe the data requirements, applicable statistical methods, advantages, and disadvantages.A range of approaches can be used to evaluate potentially important G×E effects in the NBDPS. Investigators should be aware of the limitations inherent to each approach when choosing a study design and interpreting results. Birth Defects Research (Part A) 103:692-702, 2015. © 2015 Wiley Periodicals, Inc.
View details for DOI 10.1002/bdra.23382
View details for Web of Science ID 000359740800006
View details for PubMedID 26010994
View details for PubMedCentralID PMC4537677
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A Large Multiethnic Genome-Wide Association Study of Prostate Cancer Identifies Novel Risk Variants and Substantial Ethnic Differences
CANCER DISCOVERY
2015; 5 (8): 878-891
Abstract
A genome-wide association study (GWAS) of prostate cancer in Kaiser Permanente health plan members (7,783 cases, 38,595 controls; 80.3% non-Hispanic white, 4.9% African-American, 7.0% East Asian, and 7.8% Latino) revealed a new independent risk indel rs4646284 at the previously identified locus 6q25.3 that replicated in PEGASUS (N = 7,539) and the Multiethnic Cohort (N = 4,679) with an overall P = 1.0 × 10(-19) (OR, 1.18). Across the 6q25.3 locus, rs4646284 exhibited the strongest association with expression of SLC22A1 (P = 1.3 × 10(-23)) and SLC22A3 (P = 3.2 × 10(-52)). At the known 19q13.33 locus, rs2659124 (P = 1.3 × 10(-13); OR, 1.18) nominally replicated in PEGASUS. A risk score of 105 known risk SNPs was strongly associated with prostate cancer (P < 1.0 × 10(-8)). Comparing the highest to lowest risk score deciles, the OR was 6.22 for non-Hispanic whites, 5.82 for Latinos, 3.77 for African-Americans, and 3.38 for East Asians. In non-Hispanic whites, the 105 risk SNPs explained approximately 7.6% of disease heritability. The entire GWAS array explained approximately 33.4% of heritability, with a 4.3-fold enrichment within DNaseI hypersensitivity sites (P = 0.004).Taken together, our findings of independent risk variants, ethnic variation in existing SNP replication, and remaining unexplained heritability have important implications for further clarifying the genetic risk of prostate cancer. Our findings also suggest that there may be much promise in evaluating understudied variation, such as indels and ethnically diverse populations.
View details for DOI 10.1158/2159-8290.CD-15-0315
View details for Web of Science ID 000359317700020
View details for PubMedID 26034056
View details for PubMedCentralID PMC4527942
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Developments in our understanding of the genetic basis of birth defects
BIRTH DEFECTS RESEARCH PART A-CLINICAL AND MOLECULAR TERATOLOGY
2015; 103 (8): 680-691
Abstract
Birth defects are a major cause of morbidity and mortality worldwide. There has been much progress in understanding the genetic basis of familial and syndromic forms of birth defects. However, the etiology of nonsydromic birth defects is not well-understood. Although there is still much work to be done, we have many of the tools needed to accomplish the task. Advances in next-generation sequencing have introduced a sea of possibilities, from disease-gene discovery to clinical screening and diagnosis. These advances have been fruitful in identifying a host of candidate disease genes, spanning the spectrum of birth defects. With the advent of CRISPR-Cas9 gene editing, researchers now have a precise tool for characterizing this genetic variation in model systems. Work in model organisms has also illustrated the importance of epigenetics in human development and birth defects etiology. Here we review past and current knowledge in birth defects genetics. We describe genotyping and sequencing methods for the detection and analysis of rare and common variants. We remark on the utility of model organisms and explore epigenetics in the context of structural malformation. We conclude by highlighting approaches that may provide insight into the complex genetics of birth defects. Birth Defects Research (Part A) 103:680-691, 2015. © 2015 Wiley Periodicals, Inc.
View details for DOI 10.1002/bdra.23385
View details for Web of Science ID 000359740800005
View details for PubMedID 26033863
View details for PubMedCentralID PMC4537658
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Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults
PLOS ONE
2015; 10 (6)
Abstract
Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.
View details for DOI 10.1371/journal.pone.0131106
View details for Web of Science ID 000358151300033
View details for PubMedCentralID PMC4488332
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Replication and Heritability of Prostate Cancer Risk Variants: Impact of Population-Specific Factors
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2015; 24 (6): 938-943
Abstract
Prostate cancer incidence and mortality rates vary across populations, with African American men exhibiting the highest rates. To date, genome-wide association studies have identified 104 SNPs independently associated with prostate cancer in men of European ancestry.We investigated whether the ability to replicate findings for these 104 SNPs in African American, Asian, and Latino populations depends on variation in risk allele frequencies (RAF), strength of associations, and/or patterns of linkage disequilibrium (LD) at the associated loci. We extracted estimates of effect from the literature, and determined RAF and LD information across the populations from the 1000 Genomes Project.Risk variants were largely replicated across populations. Relative to Europeans, 83% had smaller effect sizes among African Americans and 73% demonstrated smaller effect sizes among Latinos. Among Asians, however, 56% showed larger effect sizes than among Europeans. The largest difference in RAFs was observed between European and African ancestry populations, but this difference did not impact our ability to replicate. The extent of LD within 250 kb of risk loci in Asian ancestry populations was suggestively lower for variants that did not replicate (P = 0.013).Despite substantial overlap in prostate cancer risk SNPs across populations, the variation in prostate cancer incidence among different populations may still in part reflect unique underlying genetic architectures.Studying different ancestral populations is crucial for deciphering the genetic basis of prostate cancer.
View details for DOI 10.1158/1055-9965.EPI-14-1372
View details for Web of Science ID 000357425200007
View details for PubMedID 25809866
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Genetic Polymorphisms in ESR1 and ESR2 Genes, and Risk of Hypospadias in a Multiethnic Study Population
JOURNAL OF UROLOGY
2015; 193 (5): 1625-1631
Abstract
Estrogenic endocrine disruptors acting via estrogen receptors α (ESR1) and β (ESR2) have been implicated in the etiology of hypospadias, a common congenital malformation of the male external genitalia. We determined the association of single nucleotide polymorphisms in ESR1 and ESR2 genes with hypospadias in a racially/ethnically diverse study population of California births.We investigated the relationship between hypospadias and 108 ESR1 and 36 ESR2 single nucleotide polymorphisms in 647 cases and 877 population based nonmalformed controls among infants born in selected California counties from 1990 to 2003. Subgroup analyses were performed by race/ethnicity (nonHispanic white and Hispanic subjects) and by hypospadias severity (mild to moderate and severe).Odds ratios for 33 of the 108 ESR1 single nucleotide polymorphisms had p values less than 0.05 (p = 0.05 to 0.007) for risk of hypospadias. However, none of the 36 ESR2 single nucleotide polymorphisms was significantly associated. In stratified analyses the association results were consistent by disease severity but different sets of single nucleotide polymorphisms were significantly associated with hypospadias in nonHispanic white and Hispanic subjects. Due to high linkage disequilibrium across the single nucleotide polymorphisms, haplotype analyses were conducted and identified 6 haplotype blocks in ESR1 gene that had haplotypes significantly associated with an increased risk of hypospadias (OR 1.3 to 1.8, p = 0.04 to 0.00001). Similar to single nucleotide polymorphism analysis, different ESR1 haplotypes were associated with risk of hypospadias in nonHispanic white and Hispanic subjects. No significant haplotype association was observed for ESR2.The data provide evidence that ESR1 single nucleotide polymorphisms and haplotypes influence the risk of hypospadias in white and Hispanic subjects, and warrant further examination in other study populations.
View details for DOI 10.1016/j.juro.2014.11.087
View details for Web of Science ID 000353113200073
View details for PubMedID 25463985
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Generalizability of established prostate cancer risk variants in men of African ancestry
INTERNATIONAL JOURNAL OF CANCER
2015; 136 (5): 1210-1217
Abstract
Genome-wide association studies have identified more than 80 risk variants for prostate cancer, mainly in European or Asian populations. The generalizability of these variants in other racial/ethnic populations needs to be understood before the loci can be used widely in risk modeling. In our study, we examined 82 previously reported risk variants in 4,853 prostate cancer cases and 4,678 controls of African ancestry. We performed association testing for each variant using logistic regression adjusted for age, study and global ancestry. Of the 82 known risk variants, 68 (83%) had effects that were directionally consistent in their association with prostate cancer risk and 30 (37%) were significantly associated with risk at p < 0.05, with the most statistically significant variants being rs116041037 (p = 3.7 × 10(-26) ) and rs6983561 (p = 1.1 × 10(-16) ) at 8q24, as well as rs7210100 (p = 5.4 × 10(-8) ) at 17q21. By exploring each locus in search of better markers, the number of variants that captured risk in men of African ancestry (p < 0.05) increased from 30 (37%) to 44 (54%). An aggregate score comprised of these 44 markers was strongly associated with prostate cancer risk [per-allele odds ratio (OR) = 1.12, p = 7.3 × 10(-98) ]. In summary, the consistent directions of effects for the vast majority of variants in men of African ancestry indicate common functional alleles that are shared across populations. Further exploration of these susceptibility loci is needed to identify the underlying biologically relevant variants to improve prostate cancer risk modeling in populations of African ancestry.
View details for DOI 10.1002/ijc.29066
View details for Web of Science ID 000346350500046
View details for PubMedCentralID PMC4268262
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Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways
NATURE NEUROSCIENCE
2015; 18 (2): 199-209
Abstract
Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.
View details for DOI 10.1038/nn.3922
View details for Web of Science ID 000348631800010
View details for PubMedID 25599223
View details for PubMedCentralID PMC4378867
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Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults.
PloS one
2015; 10 (6)
Abstract
Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.
View details for DOI 10.1371/journal.pone.0131106
View details for PubMedID 26125186
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Selenoprotein and Antioxidant Genes and the Risk of High-Grade Prostate Cancer and Prostate Cancer Recurrence
PROSTATE
2015; 75 (1): 60-69
Abstract
Observational studies suggest an inverse association between selenium and risk of prostate cancer. However, randomized controlled trials of selenium supplementation have reported conflicting results. Thus, we examined plasma selenium and selenium-related genes in relation to risk of high-grade prostate cancer and prostate cancer recurrence among men initially diagnosed with non-metastatic disease.We measured plasma selenium and genotyped 73 single nucleotide polymorphisms in TXNRD1, TXNRD2, GPX1, GPX3, GPX4, SEP15, SEPP1, SELENBP1, OGG1, and CAT among 568 men with non-metastatic prostate cancer who underwent radical prostatectomy. We examined associations between plasma selenium, genotypes, and risk of high-grade prostate cancer (Gleason grade ≥8 or 7 with primary score ≥4; n = 111) using logistic regression, and risk of prostate cancer recurrence (61 events; 3.8 y median follow-up) using Cox proportional hazards regression.Plasma selenium was not associated with risk of high-grade prostate cancer or prostate cancer recurrence. Less common alleles of rs11913319 in TXNRD2 and rs125701 in OGG1 were associated with an increased risk of high-grade prostate cancer. We observed associations between the risk of prostate cancer recurrence and multiple SNPs in TXNRD1, TXNRD2, GPX3, and SEP15. These associations were no longer statistically significant after adjustment for multiple comparisons.Among men with non-metastatic prostate cancer, there is suggestive evidence that genetic variation in selenoproteins and related antioxidant enzymes may be associated with risk of high-grade disease at diagnosis and prostate cancer recurrence.
View details for DOI 10.1002/pros.22892
View details for Web of Science ID 000346073500007
View details for PubMedID 25284284
View details for PubMedCentralID PMC4257852
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Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases
WILEY. 2015: 11-19
Abstract
Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled "Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases" at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to (1) identify opportunities, challenges, and resource needs for the development and application of genetic simulation models; (2) improve the integration of tools for modeling and analysis of simulated data; and (3) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting, the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation.
View details for DOI 10.1002/gepi.21870
View details for Web of Science ID 000346469900003
View details for PubMedID 25371374
View details for PubMedCentralID PMC4270837
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Imputation of the Rare <i>HOXB13</i> G84E Mutation and Cancer Risk in a Large Population-Based Cohort
PLOS GENETICS
2015; 11 (1): e1004930
Abstract
An efficient approach to characterizing the disease burden of rare genetic variants is to impute them into large well-phenotyped cohorts with existing genome-wide genotype data using large sequenced referenced panels. The success of this approach hinges on the accuracy of rare variant imputation, which remains controversial. For example, a recent study suggested that one cannot adequately impute the HOXB13 G84E mutation associated with prostate cancer risk (carrier frequency of 0.0034 in European ancestry participants in the 1000 Genomes Project). We show that by utilizing the 1000 Genomes Project data plus an enriched reference panel of mutation carriers we were able to accurately impute the G84E mutation into a large cohort of 83,285 non-Hispanic White participants from the Kaiser Permanente Research Program on Genes, Environment and Health Genetic Epidemiology Research on Adult Health and Aging cohort. Imputation authenticity was confirmed via a novel classification and regression tree method, and then empirically validated analyzing a subset of these subjects plus an additional 1,789 men from Kaiser specifically genotyped for the G84E mutation (r2 = 0.57, 95% CI = 0.37–0.77). We then show the value of this approach by using the imputed data to investigate the impact of the G84E mutation on age-specific prostate cancer risk and on risk of fourteen other cancers in the cohort. The age-specific risk of prostate cancer among G84E mutation carriers was higher than among non-carriers. Risk estimates from Kaplan-Meier curves were 36.7% versus 13.6% by age 72, and 64.2% versus 24.2% by age 80, for G84E mutation carriers and non-carriers, respectively (p = 3.4x10-12). The G84E mutation was also associated with an increase in risk for the fourteen other most common cancers considered collectively (p = 5.8x10-4) and more so in cases diagnosed with multiple cancer types, both those including and not including prostate cancer, strongly suggesting pleiotropic effects. [corrected].
View details for DOI 10.1371/journal.pgen.1004930
View details for Web of Science ID 000349314600042
View details for PubMedID 25629170
View details for PubMedCentralID PMC4309593
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Population Genetic Simulations of Complex Phenotypes with Implications for Rare Variant Association Tests
GENETIC EPIDEMIOLOGY
2015; 39 (1): 35-44
Abstract
Demographic events and natural selection alter patterns of genetic variation within populations and may play a substantial role in shaping the genetic architecture of complex phenotypes and disease. However, the joint impact of these basic evolutionary forces is often ignored in the assessment of statistical tests of association. Here, we provide a simulation-based framework for generating DNA sequences that incorporates selection and demography with flexible models for simulating phenotypic variation (sfs_coder). This tool also allows the user to perform locus-specific simulations by automatically querying annotated genomic functional elements and genetic maps. We demonstrate the effects of evolutionary forces on patterns of genetic variation by simulating recently inferred models of human selection and demography. We use these simulations to show that the demographic model and locus-specific features, such as the proportion of sites under selection, may have practical implications for estimating the statistical power of sequencing-based rare variant association tests. In particular, for some phenotype models, there may be higher power to detect rare variant associations in African populations compared to non-Africans, but power is considerably reduced in regions of the genome with rampant negative selection. Furthermore, we show that existing methods for simulating large samples based on resampling from a small set of observed haplotypes fail to recapitulate the distribution of rare variants in the presence of rapid population growth (as has been observed in several human populations).
View details for DOI 10.1002/gepi.21866
View details for Web of Science ID 000346469900006
View details for PubMedID 25417809
View details for PubMedCentralID PMC4270825
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Leveraging population admixture to characterize the heritability of complex traits
NATURE GENETICS
2014; 46 (12): 1356-1362
Abstract
Despite recent progress on estimating the heritability explained by genotyped SNPs (h(2)g), a large gap between h(2)g and estimates of total narrow-sense heritability (h(2)) remains. Explanations for this gap include rare variants or upward bias in family-based estimates of h(2) due to shared environment or epistasis. We estimate h(2) from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (h(2)γ). We show that h(2)γ = 2FSTCθ(1 - θ)h(2), where FSTC measures frequency differences between populations at causal loci and θ is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We applied this approach to the analysis of 13 phenotypes in 21,497 African-American individuals from 3 cohorts. For height and body mass index (BMI), we obtained h(2) estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of h(2)g in these and other data but smaller than family-based estimates of h(2).
View details for DOI 10.1038/ng.3139
View details for Web of Science ID 000345547300019
View details for PubMedCentralID PMC4244251
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The contribution of genetic variants to disease depends on the ruler
NATURE REVIEWS GENETICS
2014; 15 (11): 765-776
Abstract
Our understanding of the genetic basis of disease has evolved from descriptions of overall heritability or familiality to the identification of large numbers of risk loci. One can quantify the impact of such loci on disease using a plethora of measures, which can guide future research decisions. However, different measures can attribute varying degrees of importance to a variant. In this Analysis, we consider and contrast the most commonly used measures - specifically, the heritability of disease liability, approximate heritability, sibling recurrence risk, overall genetic variance using a logarithmic relative risk scale, the area under the receiver-operating curve for risk prediction and the population attributable fraction - and give guidelines for their use that should be explicitly considered when assessing the contribution of genetic variants to disease.
View details for DOI 10.1038/nrg3786
View details for Web of Science ID 000344014300012
View details for PubMedID 25223781
View details for PubMedCentralID PMC4412738
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Polymorphisms of an Innate Immune Gene, Toll-Like Receptor 4, and Aggressive Prostate Cancer Risk: A Systematic Review and Meta-Analysis
PLOS ONE
2014; 9 (10): e110569
Abstract
Toll-like receptor 4 (TLR4) is one of the best known TLR members expressed on the surface of several leukocytes and tissue cells and has a key function in detecting pathogen and danger-associated molecular patterns. The role of TLR4 in the pathophysiology of several age-related diseases is also well recognized, such as prostate cancer (PCa). TLR4 polymorphisms have been related to PCa risk, but the relationship between TLR4 genotypes and aggressive PCa risk has not been evaluated by any systematic reviews.We performed a systematic review and meta-analysis of candidate-gene and genome-wide association studies analyzing this relationship and included only white population. Considering appropriate criteria, only nine studies were analyzed in the meta-analysis, including 3,937 aggressive PCa and 7,382 controls.Using random effects model, no significant association was found in the ten TLR4 SNPs reported by at least four included studies under any inheritance model (rs2737191, rs1927914, rs10759932, rs1927911, rs11536879, rs2149356, rs4986790, rs11536889, rs7873784, and rs1554973). Pooled estimates from another ten TLR4 SNPs reported by three studies also showed no significant association (rs10759930, rs10116253, rs11536869, rs5030717, rs4986791, rs11536897, rs1927906, rs913930, rs1927905, and rs7045953). Meta-regression revealed that study type was not a significant source of between-study heterogeneity.TLR4 polymorphisms were not significantly associated with the risk of aggressive PCa.
View details for DOI 10.1371/journal.pone.0110569
View details for Web of Science ID 000343943700038
View details for PubMedID 25360682
View details for PubMedCentralID PMC4215920
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Genome-wide Scan of 29,141 African Americans Finds No Evidence of Directional Selection since Admixture
AMERICAN JOURNAL OF HUMAN GENETICS
2014; 95 (4): 437-444
Abstract
The extent of recent selection in admixed populations is currently an unresolved question. We scanned the genomes of 29,141 African Americans and failed to find any genome-wide-significant deviations in local ancestry, indicating no evidence of selection influencing ancestry after admixture. A recent analysis of data from 1,890 African Americans reported that there was evidence of selection in African Americans after their ancestors left Africa, both before and after admixture. Selection after admixture was reported on the basis of deviations in local ancestry, and selection before admixture was reported on the basis of allele-frequency differences between African Americans and African populations. The local-ancestry deviations reported by the previous study did not replicate in our very large sample, and we show that such deviations were expected purely by chance, given the number of hypotheses tested. We further show that the previous study's conclusion of selection in African Americans before admixture is also subject to doubt. This is because the FST statistics they used were inflated and because true signals of unusual allele-frequency differences between African Americans and African populations would be best explained by selection that occurred in Africa prior to migration to the Americas.
View details for DOI 10.1016/j.ajhg.2014.08.011
View details for Web of Science ID 000342654300008
View details for PubMedCentralID PMC4185117
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A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer
NATURE GENETICS
2014; 46 (10): 1103-1109
Abstract
Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.
View details for DOI 10.1038/ng.3094
View details for Web of Science ID 000342554100013
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Copy Number Variation in Bronchopulmonary Dysplasia
AMERICAN JOURNAL OF MEDICAL GENETICS PART A
2014; 164 (10): 2672–75
View details for DOI 10.1002/ajmg.a.36659
View details for Web of Science ID 000342279600041
View details for PubMedID 24975634
View details for PubMedCentralID PMC4167221
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Radiogenomics: Radiobiology Enters the Era of Big Data and Team Science
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS
2014; 89 (4): 709-713
View details for DOI 10.1016/j.ijrobp.2014.03.009
View details for Web of Science ID 000338707700003
View details for PubMedID 24969789
View details for PubMedCentralID PMC5119272
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Plasma Antioxidants, Genetic Variation in SOD2, CAT, GPX1, GPX4, and Prostate Cancer Survival
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2014; 23 (6): 1037-1046
Abstract
Antioxidants may reduce risk of aggressive prostate cancer, and single-nucleotide polymorphisms (SNP) in antioxidant genes may modify this association.We used Cox proportional hazards regression to examine circulating prediagnostic α-tocopherol, γ-tocopherol, and lycopene; SNPs in SOD2 (n = 5), CAT (n = 6), GPX1 (n = 2), GPX4, (n = 3); and their interactions and risk of lethal prostate cancer among 2,439 men with nonmetastatic prostate cancer in the Health Professionals Follow-up Study and Physicians' Health Study.We observed 223 events over a median follow-up of 10 years. Higher α-tocopherol levels were associated with lower risk of lethal prostate cancer [HR 3rd versus 1st quartile (Q): 0.51; 95% confidence interval (CI), 0.30-0.89; HR 4th versus 1st Q: 0.68; 95% CI, 0.41-1.13; P trend: 0.02]. Men homozygous for the less common allele (G) at rs3746165 in GPX4 had a 35% lower risk of lethal prostate cancer compared with men homozygous for the more common allele (A; HR, 0.65; 95% CI, 0.43-0.99). Among men homozygous for the less common allele in rs3746165, high γ-tocopherol levels were associated with a 3.5-fold increased risk of lethal prostate cancer (95% CI, 1.27-9.72; P value, 0.02; interaction P value, 0.01).Among men with nonmetastatic prostate cancer, higher circulating prediagnostic α-tocopherol may be associated with lower risk of developing lethal disease. Variants in GPX4 may be associated with risk of lethal prostate cancer, and may modify the relation between γ-tocopherol and prostate cancer survival.Circulating tocopherol levels and variants in GPX4 may affect prostate cancer progression. Cancer Epidemiol Biomarkers Prev; 23(6); 1037-46. ©2014 AACR.
View details for DOI 10.1158/1055-9965.EPI-13-0670
View details for Web of Science ID 000345270800015
View details for PubMedID 24711484
View details for PubMedCentralID PMC4047147
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Genetic Epidemiology and Nonsyndromic Structural Birth Defects From Candidate Genes to Epigenetics
JAMA PEDIATRICS
2014; 168 (4): 371-377
Abstract
Birth defects are a leading cause of infant morbidity and mortality worldwide. The vast majority of birth defects are nonsyndromic, and although their etiologies remain mostly unknown, evidence supports the hypothesis that they result from the complex interaction of genetic, epigenetic, environmental, and lifestyle factors. Since our last review published in 2002 describing the basic tools of genetic epidemiology used to study nonsyndromic structural birth defects, many new approaches have become available and have been used with varying success. Through rapid advances in genomic technologies, investigators are now able to investigate large portions of the genome at a fraction of previous costs. With next-generation sequencing, research has progressed from assessing a small percentage of single-nucleotide polymorphisms to assessing the entire human protein-coding repertoire (exome)-an approach that is starting to uncover rare but informative mutations associated with nonsyndromic birth defects. Herein, we report on the current state of the genetic epidemiology of birth defects and comment on future challenges and opportunities. We consider issues of study design, and we discuss common variant approaches, including candidate gene studies and genome-wide association studies. We also discuss the complexities embedded in exploring interactions between genes and the environment. We complete our review by describing new and promising next-generation sequencing technologies and examining how the study of epigenetic mechanisms could become the key to unraveling the complex etiologies of nonsyndromic structural birth defects.
View details for DOI 10.1001/jamapediatrics.2013.4858
View details for Web of Science ID 000336839200014
View details for PubMedID 24515445
View details for PubMedCentralID PMC3981910
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Mechanistic Phenotypes: An Aggregative Phenotyping Strategy to Identify Disease Mechanisms Using GWAS Data
PLOS ONE
2013; 8 (12): e81503
Abstract
A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1) non-synonymous SNPs (nsSNPs) associated with "mechanistic phenotypes", comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1) thrombosis, evaluated in a population of 1,655 African Americans; and (2) four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs), and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher's p = 0.0001, FDR p = 0.03), driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p = 2×10-5, FDR p = 0.03) (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L) while the additive model showed enrichment related to chromatid segregation (p = 4×10-6, FDR p = 0.005) (KIF25, PINX1). We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.
View details for DOI 10.1371/journal.pone.0081503
View details for Web of Science ID 000328731800020
View details for PubMedID 24349080
View details for PubMedCentralID PMC3861317
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Antioxidant and Vitamin E Transport Genes and Risk of High-Grade Prostate Cancer and Prostate Cancer Recurrence
PROSTATE
2013; 73 (16): 1786-1795
Abstract
Observational studies suggest an inverse association between vitamin E and risk of prostate cancer, particularly aggressive tumors. However, three large randomized controlled trials have reported conflicting results. Thus, we examined circulating vitamin E and vitamin E-related genes in relation to risk of high-grade prostate cancer and prostate cancer recurrence among men initially diagnosed with clinically organ-confined disease.We measured circulating α- and γ-tocopherol and genotyped 30 SNPs in SOD1, SOD2, SOD3, TTPA, and SEC14L2 among 573 men with organ-confined prostate cancer who underwent radical prostatectomy. We examined associations between circulating vitamin E, genotypes, and risk of high-grade prostate cancer (Gleason grade ≥ 8 or 7 with primary score ≥ 4; n = 117) using logistic regression, and risk of recurrence (56 events; 3.7 years median follow-up) using Cox proportional hazards regression.Circulating γ-tocopherol was associated with an increased risk of high-grade prostate cancer (Q4 v. Q1 odds ratio [OR] = 1.87; 95% confidence intervals [CI]: 0.97-3.58; P trend =0.02). The less common allele in SOD3 rs699473 was associated with an increased risk of high-grade disease (T > C: OR = 1.40, 95% CI: 1.04-1.89). Two independent SNPs in SOD1 were inversely associated with prostate cancer recurrence in additive models (rs17884057 hazard ratio [HR] = 0.49, 95%CI: 0.25-0.96; rs9967983 HR = 0.62, 95% CI: 0.40-0.95).Among men with clinically organ-confined prostate cancer, genetic variation in SOD may be associated with risk of high-grade disease at diagnosis and disease recurrence. Circulating γ-tocopherol levels may also be associated with an increased risk of high-grade disease at diagnosis.
View details for DOI 10.1002/pros.22717
View details for Web of Science ID 000326048800007
View details for PubMedID 24038157
View details for PubMedCentralID PMC5501162
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Hypospadias and Genes Related to Genital Tubercle and Early Urethral Development
JOURNAL OF UROLOGY
2013; 190 (5): 1884-1892
Abstract
PURPOSE: We determined whether variants in genes associated with genital tubercle (the anlage for the penis) and early urethral development were associated with hypospadias in humans. MATERIALS AND METHODS: We examined 293 relatively common tagSNPs in BMP4, BMP7, FGF8, FGF10, FGFR2, HOXA13, HOXD13, HOXA4, HOXB6, SRY, WT1, WTAP, SHH, GLI1, GLI2, and GLI3. The analysis included 624 cases (81 mild, 319 moderate, 209 severe, 15 undetermined severity) and 844 population-based non-malformed male controls born in California from 1990-2003. RESULTS: There were 28 SNPs for which any of the comparisons (i.e., overall or for a specific severity) had a p-value <0.01. The homozygous variant genotypes for four SNPs in BMP7were associated with at least 2-fold increased risk of hypospadias, regardless of severity. Five SNPs for FGF10were associated with 3- to 4-fold increased risks, regardless of severity; for four of them, results were restricted to whites. For GLI1, GLI2and GLI3, there were 12 associated SNPs but results were inconsistent by severity and race-ethnicity. For SHH, one SNP was associated with 2.4-fold increased risk of moderate hypospadias. For WT1, six SNPs were associated with approximately 2-fold increased risks, primarily for severe hypospadias. CONCLUSIONS: This study provides evidence that SNPs in several genes that contribute to genital tubercle and early urethral development are associated with hypospadias risk.
View details for DOI 10.1016/j.juro.2013.05.061
View details for Web of Science ID 000325471400089
View details for PubMedID 23727413
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Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs
NATURE GENETICS
2013; 45 (9): 984-?
Abstract
Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.
View details for DOI 10.1038/ng.2711
View details for Web of Science ID 000323748200007
View details for PubMedID 23933821
View details for PubMedCentralID PMC3800159
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A Genome-Wide Association Study (GWAS) for Bronchopulmonary Dysplasia.
Pediatrics
2013; 132 (2): 290-297
Abstract
Twin studies suggest that heritability of moderate-severe bronchopulmonary dysplasia (BPD) is 53% to 79%, we conducted a genome-wide association study (GWAS) to identify genetic variants associated with the risk for BPD.The discovery GWAS was completed on 1726 very low birth weight infants (gestational age = 25(0)-29(6/7) weeks) who had a minimum of 3 days of intermittent positive pressure ventilation and were in the hospital at 36 weeks' postmenstrual age. At 36 weeks' postmenstrual age, moderate-severe BPD cases (n = 899) were defined as requiring continuous supplemental oxygen, whereas controls (n = 827) inhaled room air. An additional 795 comparable infants (371 cases, 424 controls) were a replication population. Genomic DNA from case and control newborn screening bloodspots was used for the GWAS. The replication study interrogated single-nucleotide polymorphisms (SNPs) identified in the discovery GWAS and those within the HumanExome beadchip.Genotyping using genomic DNA was successful. We did not identify SNPs associated with BPD at the genome-wide significance level (5 × 10(-8)) and no SNP identified in previous studies reached statistical significance (Bonferroni-corrected P value threshold .0018). Pathway analyses were not informative.We did not identify genomic loci or pathways that account for the previously described heritability for BPD. Potential explanations include causal mutations that are genetic variants and were not assayed or are mapped to many distributed loci, inadequate sample size, race ethnicity of our study population, or case-control differences investigated are not attributable to underlying common genetic variation.
View details for DOI 10.1542/peds.2013-0533
View details for PubMedID 23897914
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Impact of polymorphisms in drug pathway genes on disease-free survival in adults with acute myeloid leukemia
JOURNAL OF HUMAN GENETICS
2013; 58 (6): 353-361
Abstract
Acute myeloid leukemia (AML) is a clinically heterogeneous disease, with a 5-year disease-free survival (DFS) ranging from under 10% to over 70% for distinct groups of patients. At our institution, cytarabine, etoposide and busulfan are used in first or second remission patients treated with a two-step approach to autologous stem cell transplantation (ASCT). In this study, we tested the hypothesis that polymorphisms in the pharmacokinetic and pharmacodynamic pathway genes of these drugs are associated with DFS in AML patients. A total of 1659 variants in 42 genes were analyzed for their association with DFS using a Cox-proportional hazards model. One hundred and fifty-four genetically European patients were used for the primary analysis. An intronic single nucleotide polymorphism (SNP) in ABCC3 (rs4148405) was associated with a significantly shorter DFS (hazard ratios (HR)=3.2, P=5.6 × 10(-6)) in our primary cohort. In addition, a SNP in the GSTM1-GSTM5 locus, rs3754446, was significantly associated with a shorter DFS in all patients (HR=1.8, P=0.001 for 154 European ancestry; HR=1.7, P=0.028 for 125 non-European patients). Thus, for the first time, genetic variants in drug pathway genes are shown to be associated with DFS in AML patients treated with chemotherapy-based autologous ASCT.
View details for DOI 10.1038/jhg.2013.38
View details for Web of Science ID 000320843600009
View details for PubMedID 23677058
View details for PubMedCentralID PMC4068832
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The Impact of Improved Microarray Coverage and Larger Sample Sizes on Future Genome-Wide Association Studies
GENETIC EPIDEMIOLOGY
2013; 37 (4): 383-392
Abstract
Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) associated with complex traits. However, the genetic heritability of most of these traits remains unexplained. To help guide future studies, we address the crucial question of whether future GWAS can detect new SNP associations and explain additional heritability given the new availability of larger GWAS SNP arrays, imputation, and reduced genotyping costs. We first describe the pairwise and imputation coverage of all SNPs in the human genome by commercially available GWAS SNP arrays, using the 1000 Genomes Project as a reference. Next, we describe the findings from 6 years of GWAS of 172 chronic diseases, calculating the power to detect each of them while taking array coverage and sample size into account. We then calculate the power to detect these SNP associations under different conditions using improved coverage and/or sample sizes. Finally, we estimate the percentages of SNP associations and heritability previously detected and detectable by future GWAS under each condition. Overall, we estimated that previous GWAS have detected less than one-fifth of all GWAS-detectable SNPs underlying chronic disease. Furthermore, increasing sample size has a much larger impact than increasing coverage on the potential of future GWAS to detect additional SNP-disease associations and heritability.
View details for DOI 10.1002/gepi.21724
View details for Web of Science ID 000317854800008
View details for PubMedID 23529720
View details for PubMedCentralID PMC4291231
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A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry.
Nature genetics
2013; 45 (6): 690-696
Abstract
Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.
View details for DOI 10.1038/ng.2608
View details for PubMedID 23583978
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<i>HOXB13</i> Mutation and Prostate Cancer: Studies of Siblings and Aggressive Disease
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2013; 22 (4): 675-680
Abstract
Recent work detected for the first time a high-risk prostate cancer mutation, in homeobox B13 (HOXB13) among European-Americans.We further evaluated this G84E missense mutation (rs138213197) in two genetic association studies of prostate cancer: a family-based study of brothers and a case-control study of more aggressive disease (N = 2,665 total). We then calculated overall impact of this mutation by pooling all published studies of European-Americans.In our studies, the mutation was found exclusively among men with prostate cancer (carrier frequency = 1.48%) or unaffected brothers of cases carrying the mutation (frequency = 0.34%), and carrying the mutation gave an OR for disease = 4.79 (P = 0.01). The G84E mutation was more common among men with an earlier age of onset (≤55 years) or a family history of prostate cancer. We also observed for the first time an African-American case carrying the G84E mutation, although at HOXB13 both of his chromosomes were of European-American ancestry. The pooled analysis also indicated that carrying the G84E mutation results in an almost five-fold increase in risk of prostate cancer (P = 3.5 × 10(-17)), and this risk is even higher among cases with an early age of prostate cancer onset (≤55 years) or a family history of disease: a test of heterogeneity across these strata gives P < 1 × 10(-5).The HOXB13 mutation substantially increases risk of early onset, familial prostate cancer in European-American men.Testing for the G84E mutation in men with a positive family history may help distinguish those who merit more regular screening for prostate cancer.
View details for DOI 10.1158/1055-9965.EPI-12-1154
View details for Web of Science ID 000317960900025
View details for PubMedID 23396964
View details for PubMedCentralID PMC3617049
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Diacylglycerol Kinase K Variants Impact Hypospadias in a California Study Population
JOURNAL OF UROLOGY
2013; 189 (1): 305-311
Abstract
A recent genome wide association study demonstrated the novel finding that variants in DGKK are associated with hypospadias. Our objectives were to determine whether this finding could be replicated in a more racially/ethnically diverse study population of California births and to provide a more comprehensive investigation of variants.We examined the association of 27 DGKK single nucleotide polymorphisms with hypospadias relative to population based nonmalformed controls born in selected California counties from 1990 to 2003. Analyses included a maximum of 928 controls and 665 cases (mild in 91, moderate in 336, severe in 221 and undetermined in 17). Results for mild and moderate cases were similar, so they were grouped together.For mild and moderate cases OR for 15 of the 27 single nucleotide polymorphisms had p values less than 0.05, with 2 less than 1 and the others ranging from 1.3 to 1.8. Among severe cases ORs tended to be closer to 1, and none of the p values were less than 0.05. Due to high linkage disequilibrium across the single nucleotide polymorphisms, haplotype analyses were conducted and 2 blocks were generated. These analyses identified a set of 8 variants associated with a threefold to fourfold increased risk relative to the most common haplotype, regardless of severity of the phenotype (OR 4.1, p <10(-4) for mild to moderate cases and 3.3, p = 0.001 for severe cases).This study confirms that DGKK variants are associated with hypospadias. Additional studies are needed to allow a more thorough investigation of DGKK variability and to delineate the mechanism by which DGKK contributes to urethral development.
View details for DOI 10.1016/j.juro.2012.09.002
View details for Web of Science ID 000312604800107
View details for PubMedID 23177175
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High Quality Genome-Wide Genotyping from Archived Dried Blood Spots without DNA Amplification.
PloS one
2013; 8 (5): e64710
Abstract
Spots of blood are routinely collected from newborn babies onto filter paper called Guthrie cards and used to screen for metabolic and genetic disorders. The archived dried blood spots are an important and precious resource for genomic research. Whole genome amplification of dried blood spot DNA has been used to provide DNA for genome-wide SNP genotyping. Here we describe a 96 well format procedure to extract DNA from a portion of a dried blood spot that provides sufficient unamplified genomic DNA for genome-wide single nucleotide polymorphism (SNP) genotyping. We show that SNP genotyping of the unamplified DNA is more robust than genotyping amplified dried blood spot DNA, is comparable in cost, and can be done with thousands of samples. This procedure can be used for genome-wide association studies and other large-scale genomic analyses that require robust, high-accuracy genotyping of dried blood spot DNA.
View details for DOI 10.1371/journal.pone.0064710
View details for PubMedID 23737996
View details for PubMedCentralID PMC3667813
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Global patterns of prostate cancer incidence, aggressiveness, and mortality in men of african descent.
Prostate cancer
2013; 2013: 560857-?
Abstract
Prostate cancer (CaP) is the leading cancer among men of African descent in the USA, Caribbean, and Sub-Saharan Africa (SSA). The estimated number of CaP deaths in SSA during 2008 was more than five times that among African Americans and is expected to double in Africa by 2030. We summarize publicly available CaP data and collected data from the men of African descent and Carcinoma of the Prostate (MADCaP) Consortium and the African Caribbean Cancer Consortium (AC3) to evaluate CaP incidence and mortality in men of African descent worldwide. CaP incidence and mortality are highest in men of African descent in the USA and the Caribbean. Tumor stage and grade were highest in SSA. We report a higher proportion of T1 stage prostate tumors in countries with greater percent gross domestic product spent on health care and physicians per 100,000 persons. We also observed that regions with a higher proportion of advanced tumors reported lower mortality rates. This finding suggests that CaP is underdiagnosed and/or underreported in SSA men. Nonetheless, CaP incidence and mortality represent a significant public health problem in men of African descent around the world.
View details for DOI 10.1155/2013/560857
View details for PubMedID 23476788
View details for PubMedCentralID PMC3583061
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Association of the Innate Immunity and Inflammation Pathway with Advanced Prostate Cancer Risk
PLOS ONE
2012; 7 (12): e51680
Abstract
Prostate cancer is the most frequent and second most lethal cancer in men in the United States. Innate immunity and inflammation may increase the risk of prostate cancer. To determine the role of innate immunity and inflammation in advanced prostate cancer, we investigated the association of 320 single nucleotide polymorphisms, located in 46 genes involved in this pathway, with disease risk using 494 cases with advanced disease and 536 controls from Cleveland, Ohio. Taken together, the whole pathway was associated with advanced prostate cancer risk (P = 0.02). Two sub-pathways (intracellular antiviral molecules and extracellular pattern recognition) and four genes in these sub-pathways (TLR1, TLR6, OAS1, and OAS2) were nominally associated with advanced prostate cancer risk and harbor several SNPs nominally associated with advanced prostate cancer risk. Our results suggest that the innate immunity and inflammation pathway may play a modest role in the etiology of advanced prostate cancer through multiple small effects.
View details for DOI 10.1371/journal.pone.0051680
View details for Web of Science ID 000312386800063
View details for PubMedID 23272139
View details for PubMedCentralID PMC3522730
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Rare genetic variants and treatment response: sample size and analysis issues
STATISTICS IN MEDICINE
2012; 31 (25): 3041-3050
Abstract
Incorporating information about common genetic variants may help improve the design and analysis of clinical trials. For example, if genes impact response to treatment, one can pregenotype potential participants to screen out genetically determined nonresponders and substantially reduce the sample size and duration of a trial. Genetic associations with response to treatment are generally much larger than those observed for development of common diseases, as highlighted here by findings from genome-wide association studies. With the development and decreasing cost of next generation sequencing, more extensive genetic information - including rare variants - is becoming available on individuals treated with drugs and other therapies. We can use this information to evaluate whether rare variants impact treatment response. The sparseness of rare variants, however, raises issues of how the resulting data should be best analyzed. As shown here, simply evaluating the association between each rare variant and treatment response one-at-a-time will require enormous sample sizes. Combining the rare variants together can substantially reduce the required sample sizes, but require a number of assumptions about the similarity among the rare variants' effects on treatment response. We have developed an empirical approach for aggregating and analyzing rare variants that limit such assumptions and work well under a range of scenarios. Such analyses provide a valuable opportunity to more fully decipher the genomic basis of response to treatment.
View details for DOI 10.1002/sim.5428
View details for Web of Science ID 000309745200011
View details for PubMedID 22736504
View details for PubMedCentralID PMC3766744
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The Covariate's Dilemma
PLOS GENETICS
2012; 8 (11): e1003096
View details for DOI 10.1371/journal.pgen.1003096
View details for Web of Science ID 000311891600071
View details for PubMedID 23162385
View details for PubMedCentralID PMC3497901
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Reclassify Controls at Your Own Risk
EPIDEMIOLOGY
2012; 23 (6): 910-911
View details for DOI 10.1097/EDE.0b013e31826cc118
View details for Web of Science ID 000309965800023
View details for PubMedID 23038114
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A Genome-Wide Association Study Identifies Novel Loci for Paclitaxel-Induced Sensory Peripheral Neuropathy in CALGB 40101
CLINICAL CANCER RESEARCH
2012; 18 (18): 5099-5109
Abstract
Sensory peripheral neuropathy is a common and sometimes debilitating toxicity associated with paclitaxel therapy. This study aims to identify genetic risk factors for the development of this toxicity.A prospective pharmacogenetic analysis of patients with primary breast cancer, randomized to the paclitaxel arm of CALGB 40101, was used to identify genetic predictors of the onset and severity of sensory peripheral neuropathy. A genome-wide association study in 855 subjects of European ancestry was conducted and findings were replicated in additional European (n = 154) and African American (n = 117) subjects.A single nucleotide polymorphism in FGD4 was associated with the onset of sensory peripheral neuropathy in the discovery cohort [rs10771973; HR, 1.57; 95% confidence interval (CI), 1.30-1.91; P = 2.6 × 10(-6)] and in a European (HR, 1.72; 95% CI, 1.06-2.80; P = 0.013) and African American (HR, 1.93; 95% CI, 1.13-3.28; P = 6.7 × 10(-3)) replication cohort. There is also evidence that markers in additional genes, including EPHA5 (rs7349683) and FZD3 (rs10771973), were associated with the onset or severity of paclitaxel-induced sensory peripheral neuropathy.A genome-wide association study has identified novel genetic markers of paclitaxel-induced sensory peripheral neuropathy, including a common polymorphism in FGD4, a congenital peripheral neuropathy gene. These findings suggest that genetic variation may contribute to variation in development of this toxicity. Validation of these findings may allow for the identification of patients at increased risk of peripheral neuropathy and inform the use of an alternative to paclitaxel and/or the clinical management of this toxicity.
View details for DOI 10.1158/1078-0432.CCR-12-1590
View details for Web of Science ID 000309965700027
View details for PubMedID 22843789
View details for PubMedCentralID PMC3445665
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Joint Association Testing of Common and Rare Genetic Variants Using Hierarchical Modeling
GENETIC EPIDEMIOLOGY
2012; 36 (6): 642-651
Abstract
New sequencing technologies provide an opportunity for assessing the impact of rare and common variants on complex diseases. Several methods have been developed for evaluating rare variants, many of which use weighted collapsing to combine rare variants. Some approaches require arbitrary frequency thresholds below which to collapse alleles, and most assume that effect sizes for each collapsed variant are either the same or a function of minor allele frequency. Some methods also further assume that all rare variants are deleterious rather than protective. We expect that such assumptions will not hold in general, and as a result performance of these tests will be adversely affected. We propose a hierarchical model, implemented in the new program CHARM, to detect the joint signal from rare and common variants within a genomic region while properly accounting for linkage disequilibrium between variants. Our model explores the scale, rather than the center of the odds ratio distribution, allowing for both causative and protective effects. We use cross-validation to assess the evidence for association in a region. We use model averaging to widen the range of disease models under which we will have good power. To assess this approach, we simulate data under a range of disease models with effects at common and/or rare variants. Overall, our method had more power than other well-known rare variant approaches; it performed well when either only rare, or only common variants were causal, and better than other approaches when both common and rare variants contributed to disease.
View details for DOI 10.1002/gepi.21659
View details for Web of Science ID 000307499900012
View details for PubMedID 22807252
View details for PubMedCentralID PMC4339046
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The Association Between a <i>Darc</i> Gene Polymorphism and Clinical Outcomes in African American Patients With Acute Lung Injury
CHEST
2012; 141 (5): 1160-1169
Abstract
Acute lung injury (ALI) mortality is increased among African Americans compared with Americans of European descent, and genetic factors may be involved. A functional T-46C polymorphism (rs2814778) in the promoter region of Duffy antigen/receptor for chemokines (Darc) gene, present almost exclusively in people of African descent, results in isolated erythrocyte DARC deficiency and has been implicated in ALI pathogenesis in preclinical and murine models, possibly because of an increase in circulating Duffy-binding, proinflammatory chemokines like IL-8. We sought to determine the effect of the functional rs2814778 polymorphism, C/C genotype (Duffy null state), on clinical outcomes in African Americans with acute lung injury.Clinical data and biologic specimens from African American patients with ALI who enrolled in three randomized controlled trials were analyzed. Multivariate analysis accounted for proportion of African ancestry, sex, cirrhosis, and severity of illness on presentation.Among 132 subjects, 88 (67%) were Duffy null (C/C genotype). The Duffy null state was associated with a 17% absolute risk increase (95% CI, 1.4%-33%) in mortality at 60 days, a median of 8 fewer ventilator-free days (95% CI, 1-18.5), and 4.5 fewer organ failure-free days (95% CI, 0-18) compared with individuals with the C/T or T/T genotypes (all P values < .05). Estimates were similar on multivariate analysis. In African Americans without the null variant, clinical outcomes were similar to those in patients of European descent. A subgroup analysis suggested that plasma IL-8 levels are increased in Duffy null individuals.Our results provide evidence that the functional rs2814778 polymorphism in the gene encoding DARC is associated with worse clinical outcomes among African Americans with ALI, possibly via an increase in circulating IL-8.
View details for DOI 10.1378/chest.11-1766
View details for Web of Science ID 000303905700011
View details for PubMedID 22207676
View details for PubMedCentralID PMC3342784
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Does Accounting for Gene-Environment Interactions Help Uncover Association between Rare Variants and Complex Diseases?
HUMAN HEREDITY
2012; 74 (3-4): 205-214
Abstract
To determine whether accounting for gene-environment (G×E) interactions improves the power to detect associations between rare variants and a disease, we have extended three statistical methods and compared their power under various simulated disease models.To test for association of a group of rare variants with a disease, Min-P uses the lowest p value within the group of variants, CAST (Cohort Allelic Sums Test) uses an indicator variable to quantify the rare alleles within the group of variants, and SKAT (Sequence Kernel Association Test) uses a logistic regression based on kernel machine. For each method, we incorporate a term for the G×E interaction and test for association and interaction jointly.When testing for disease association with a set of rare variants, accounting for G×E interactions can improve power in specific situations (pure interaction or high proportion of causal variants interacting with the environment). However, the power of this approach can decrease, in particular in the presence of main genetic or environmental effects. Among the methods compared, the optimized and weighted SKAT performed best, whether to test for genetic association or to test it jointly with G×E interactions.This approach can be used in specific situations but is not appropriate for a primary analysis.
View details for DOI 10.1159/000346825
View details for Web of Science ID 000317569400010
View details for PubMedID 23594498
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Parallel biocomputing
SOURCE CODE FOR BIOLOGY AND MEDICINE
2011; 6 (1): 4
Abstract
With the advent of high throughput genomics and high-resolution imaging techniques, there is a growing necessity in biology and medicine for parallel computing, and with the low cost of computing, it is now cost-effective for even small labs or individuals to build their own personal computation cluster.Here we briefly describe how to use commodity hardware to build a low-cost, high-performance compute cluster, and provide an in-depth example and sample code for parallel execution of R jobs using MOSIX, a mature extension of the Linux kernel for parallel computing. A similar process can be used with other cluster platform software.As a statistical genetics example, we use our cluster to run a simulated eQTL experiment. Because eQTL is computationally intensive, and is conceptually easy to parallelize, like many statistics/genetics applications, parallel execution with MOSIX gives a linear speedup in analysis time with little additional effort.We have used MOSIX to run a wide variety of software programs in parallel with good results. The limitations and benefits of using MOSIX are discussed and compared to other platforms.
View details for DOI 10.1186/1751-0473-6-4
View details for Web of Science ID 000215859700004
View details for PubMedID 21418580
View details for PubMedCentralID PMC3068083
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A Genetic Signature of Spina Bifida Risk from Pathway-Informed Comprehensive Gene-Variant Analysis
PLOS ONE
2011; 6 (11)
Abstract
Despite compelling epidemiological evidence that folic acid supplements reduce the frequency of neural tube defects (NTDs) in newborns, common variant association studies with folate metabolism genes have failed to explain the majority of NTD risk. The contribution of rare alleles as well as genetic interactions within the folate pathway have not been extensively studied in the context of NTDs. Thus, we sequenced the exons in 31 folate-related genes in a 480-member NTD case-control population to identify the full spectrum of allelic variation and determine whether rare alleles or obvious genetic interactions within this pathway affect NTD risk. We constructed a pathway model, predetermined independent of the data, which grouped genes into coherent sets reflecting the distinct metabolic compartments in the folate/one-carbon pathway (purine synthesis, pyrimidine synthesis, and homocysteine recycling to methionine). By integrating multiple variants based on these groupings, we uncovered two provocative, complex genetic risk signatures. Interestingly, these signatures differed by race/ethnicity: a Hispanic risk profile pointed to alterations in purine biosynthesis, whereas that in non-Hispanic whites implicated homocysteine metabolism. In contrast, parallel analyses that focused on individual alleles, or individual genes, as the units by which to assign risk revealed no compelling associations. These results suggest that the ability to layer pathway relationships onto clinical variant data can be uniquely informative for identifying genetic risk as well as for generating mechanistic hypotheses. Furthermore, the identification of ethnic-specific risk signatures for spina bifida resonated with epidemiological data suggesting that the underlying pathogenesis may differ between Hispanic and non-Hispanic groups.
View details for DOI 10.1371/journal.pone.0028408
View details for Web of Science ID 000298168100069
View details for PubMedID 22140583
View details for PubMedCentralID PMC3227667
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Use of principal components to aggregate rare variants in case-control and family-based association studies in the presence of multiple covariates.
BMC proceedings
2011; 5 Suppl 9: S29
Abstract
Rare variants may help to explain some of the missing heritability of complex diseases. Technological advances in next-generation sequencing give us the opportunity to test this hypothesis. We propose two new methods (one for case-control studies and one for family-based studies) that combine aggregated rare variants and common variants located within a region through principal components analysis and allow for covariate adjustment. We analyzed 200 replicates consisting of 209 case subjects and 488 control subjects and compared the results to weight-based and step-up aggregation methods. The principal components and collapsing method showed an association between the gene FLT1 and the quantitative trait Q1 (P<10-30) in a fraction of the computation time of the other methods. The proposed family-based test has inconclusive results. The two methods provide a fast way to analyze simultaneously rare and common variants at the gene level while adjusting for covariates. However, further evaluation of the statistical efficiency of this approach is warranted.
View details for DOI 10.1186/1753-6561-5-S9-S29
View details for PubMedID 22373382
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Impact of Meat Consumption, Preparation, and Mutagens on Aggressive Prostate Cancer
PLOS ONE
2011; 6 (11): e27711
Abstract
The association between meat consumption and prostate cancer remains unclear, perhaps reflecting heterogeneity in the types of tumors studied and the method of meat preparation--which can impact the production of carcinogens.We address both issues in this case-control study focused on aggressive prostate cancer (470 cases and 512 controls), where men reported not only their meat intake but also their meat preparation and doneness level on a semi-quantitative food-frequency questionnaire. Associations between overall and grilled meat consumption, doneness level, ensuing carcinogens and aggressive prostate cancer were assessed using multivariate logistic regression.Higher consumption of any ground beef or processed meats were positively associated with aggressive prostate cancer, with ground beef showing the strongest association (OR = 2.30, 95% CI:1.39-3.81; P-trend = 0.002). This association primarily reflected intake of grilled or barbequed meat, with more well-done meat conferring a higher risk of aggressive prostate cancer. Comparing high and low consumptions of well/very well cooked ground beef to no consumption gave OR's of 2.04 (95% CI:1.41-2.96) and 1.51 (95% CI:1.06-2.14), respectively. In contrast, consumption of rare/medium cooked ground beef was not associated with aggressive prostate cancer. Looking at meat mutagens produced by cooking at high temperatures, we detected an increased risk with 2-amino-3,8-Dimethylimidazo-[4,5-f]Quinolaxine (MelQx) and 2-amino-3,4,8-trimethylimidazo(4,5-f)qunioxaline (DiMelQx), when comparing the highest to lowest quartiles of intake: OR = 1.69 (95% CI:1.08-2.64;P-trend = 0.02) and OR = 1.53 (95% CI:1.00-2.35; P-trend = 0.005), respectively.Higher intake of well-done grilled or barbequed red meat and ensuing carcinogens could increase the risk of aggressive prostate cancer.
View details for DOI 10.1371/journal.pone.0027711
View details for Web of Science ID 000298162000037
View details for PubMedID 22132129
View details for PubMedCentralID PMC3223211
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Identification, Replication, and Fine-Mapping of Loci Associated with Adult Height in Individuals of African Ancestry
PLOS GENETICS
2011; 7 (10)
Abstract
Adult height is a classic polygenic trait of high heritability (h(2) approximately 0.8). More than 180 single nucleotide polymorphisms (SNPs), identified mostly in populations of European descent, are associated with height. These variants convey modest effects and explain approximately10% of the variance in height. Discovery efforts in other populations, while limited, have revealed loci for height not previously implicated in individuals of European ancestry. Here, we performed a meta-analysis of genome-wide association (GWA) results for adult height in 20,427 individuals of African ancestry with replication in up to 16,436 African Americans. We found two novel height loci (Xp22-rs12393627, P = 3.4×10(-12) and 2p14-rs4315565, P = 1.2×10(-8)). As a group, height associations discovered in European-ancestry samples replicate in individuals of African ancestry (P = 1.7×10(-4) for overall replication). Fine-mapping of the European height loci in African-ancestry individuals showed an enrichment of SNPs that are associated with expression of nearby genes when compared to the index European height SNPs (P<0.01). Our results highlight the utility of genetic studies in non-European populations to understand the etiology of complex human diseases and traits.
View details for DOI 10.1371/journal.pgen.1002298
View details for Web of Science ID 000296665400007
View details for PubMedID 21998595
View details for PubMedCentralID PMC3188544
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The landscape of recombination in African Americans
NATURE
2011; 476 (7359): 170-U67
Abstract
Recombination, together with mutation, gives rise to genetic variation in populations. Here we leverage the recent mixture of people of African and European ancestry in the Americas to build a genetic map measuring the probability of crossing over at each position in the genome, based on about 2.1 million crossovers in 30,000 unrelated African Americans. At intervals of more than three megabases it is nearly identical to a map built in Europeans. At finer scales it differs significantly, and we identify about 2,500 recombination hotspots that are active in people of West African ancestry but nearly inactive in Europeans. The probability of a crossover at these hotspots is almost fully controlled by the alleles an individual carries at PRDM9 (P value < 10(-245)). We identify a 17-base-pair DNA sequence motif that is enriched in these hotspots, and is an excellent match to the predicted binding target of PRDM9 alleles common in West Africans and rare in Europeans. Sites of this motif are predicted to be risk loci for disease-causing genomic rearrangements in individuals carrying these alleles. More generally, this map provides a resource for research in human genetic variation and evolution.
View details for DOI 10.1038/nature10336
View details for Web of Science ID 000293731900028
View details for PubMedID 21775986
View details for PubMedCentralID PMC3154982
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Genome-wide association study of prostate cancer in men of African ancestry identifies a susceptibility locus at 17q21
NATURE GENETICS
2011; 43 (6): 570-U103
Abstract
In search of common risk alleles for prostate cancer that could contribute to high rates of the disease in men of African ancestry, we conducted a genome-wide association study, with 1,047,986 SNP markers examined in 3,425 African-Americans with prostate cancer (cases) and 3,290 African-American male controls. We followed up the most significant 17 new associations from stage 1 in 1,844 cases and 3,269 controls of African ancestry. We identified a new risk variant on chromosome 17q21 (rs7210100, odds ratio per allele = 1.51, P = 3.4 × 10(-13)). The frequency of the risk allele is ∼5% in men of African descent, whereas it is rare in other populations (<1%). Further studies are needed to investigate the biological contribution of this allele to prostate cancer risk. These findings emphasize the importance of conducting genome-wide association studies in diverse populations.
View details for DOI 10.1038/ng.839
View details for Web of Science ID 000291017000015
View details for PubMedID 21602798
View details for PubMedCentralID PMC3102788
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Polygenic Modeling of Genome-Wide Association Studies: An Application to Prostate and Breast Cancer
OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY
2011; 15 (6): 393-U66
Abstract
Genome-wide association studies (GWAS) have successfully detected and replicated associations with numerous diseases, including cancers of the prostate and breast. These findings are helping clarify the genomic basis of such diseases, but appear to explain little of disease heritability. This limitation might reflect the focus of conventional GWAS on a small set of the most statistically significant associations with disease. More information might be obtained by analyzing GWAS using a polygenic model, which allows for the possibility that thousands of genetic variants could impact disease. Furthermore, there may exist common polygenic effects between potentially related phenotypes (e.g., prostate and breast cancer). Here we present and apply a polygenic model to GWAS of prostate and breast cancer. Our results indicate that the polygenic model can explain an increasing--albeit low--amount of heritability for both of these cancers, even when excluding the most statistically significant associations. In addition, nonaggressive prostate cancer and breast cancer appear to share a common polygenic model, potentially reflecting a similar underlying biology. This supports the further development and application of polygenic models to genomic data.
View details for DOI 10.1089/omi.2010.0090
View details for Web of Science ID 000291198200008
View details for PubMedID 21348634
View details for PubMedCentralID PMC3125548
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Characterizing genetic risk at known prostate cancer susceptibility loci in African Americans.
PLoS genetics
2011; 7 (5): e1001387
Abstract
GWAS of prostate cancer have been remarkably successful in revealing common genetic variants and novel biological pathways that are linked with its etiology. A more complete understanding of inherited susceptibility to prostate cancer in the general population will come from continuing such discovery efforts and from testing known risk alleles in diverse racial and ethnic groups. In this large study of prostate cancer in African American men (3,425 prostate cancer cases and 3,290 controls), we tested 49 risk variants located in 28 genomic regions identified through GWAS in men of European and Asian descent, and we replicated associations (at p≤0.05) with roughly half of these markers. Through fine-mapping, we identified nearby markers in many regions that better define associations in African Americans. At 8q24, we found 9 variants (p≤6×10(-4)) that best capture risk of prostate cancer in African Americans, many of which are more common in men of African than European descent. The markers found to be associated with risk at each locus improved risk modeling in African Americans (per allele OR = 1.17) over the alleles reported in the original GWAS (OR = 1.08). In summary, in this detailed analysis of the prostate cancer risk loci reported from GWAS, we have validated and improved upon markers of risk in some regions that better define the association with prostate cancer in African Americans. Our findings with variants at 8q24 also reinforce the importance of this region as a major risk locus for prostate cancer in men of African ancestry.
View details for DOI 10.1371/journal.pgen.1001387
View details for PubMedID 21637779
View details for PubMedCentralID PMC3102736
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Co-regulatory expression quantitative trait loci mapping: method and application to endometrial cancer
BMC MEDICAL GENOMICS
2011; 4: 6
Abstract
Expression quantitative trait loci (eQTL) studies have helped identify the genetic determinants of gene expression. Understanding the potential interacting mechanisms underlying such findings, however, is challenging.We describe a method to identify the trans-acting drivers of multiple gene co-expression, which reflects the action of regulatory molecules. This method-termed co-regulatory expression quantitative trait locus (creQTL) mapping-allows for evaluation of a more focused set of phenotypes within a clear biological context than conventional eQTL mapping.Applying this method to a study of endometrial cancer revealed regulatory mechanisms supported by the literature: a creQTL between a locus upstream of STARD13/DLC2 and a group of seven IFNβ-induced genes. This suggests that the Rho-GTPase encoded by STARD13 regulates IFNβ-induced genes and the DNA damage response.Because of the importance of IFNβ in cancer, our results suggest that creQTL may provide a finer picture of gene regulation and may reveal additional molecular targets for intervention. An open source R implementation of the method is available at http://sites.google.com/site/kenkompass/.
View details for DOI 10.1186/1755-8794-4-6
View details for Web of Science ID 000286806100001
View details for PubMedID 21226949
View details for PubMedCentralID PMC3032645
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Personalized Prostate Cancer Screening: Improving PSA Tests with Genomic Information
SCIENCE TRANSLATIONAL MEDICINE
2010; 2 (62): 62ps55
Abstract
The use of a prostate-specific antigen (PSA) test to screen for prostate cancer is controversial because of its modest predictive value and the potential overdiagnosis and over-treatment of the disease. A research article in this issue of Science Translational Medicine describes single-nucleotide polymorphisms (SNPs) in or near six genes that are independently associated with serum PSA concentrations and that help to explain interindividual PSA variation. Three of these SNPs are also associated with prostate biopsy outcomes. These findings are an important step toward incorporating genetic markers into PSA screening, with the ultimate goal of devising personalized PSA tests for use in the clinic.
View details for DOI 10.1126/scitranslmed.3001861
View details for Web of Science ID 000288444300001
View details for PubMedID 21160075
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Comprehensive Approach to Analyzing Rare Genetic Variants
PLOS ONE
2010; 5 (11): e13584
Abstract
Recent findings suggest that rare variants play an important role in both monogenic and common diseases. Due to their rarity, however, it remains unclear how to appropriately analyze the association between such variants and disease. A common approach entails combining rare variants together based on a priori information and analyzing them as a single group. Here one must make some assumptions about what to aggregate. Instead, we propose two approaches to empirically determine the most efficient grouping of rare variants. The first considers multiple possible groupings using existing information. The second is an agnostic "step-up" approach that determines an optimal grouping of rare variants analytically and does not rely on prior information. To evaluate these approaches, we undertook a simulation study using sequence data from genes in the one-carbon folate metabolic pathway. Our results show that using prior information to group rare variants is advantageous only when information is quite accurate, but the step-up approach works well across a broad range of plausible scenarios. This agnostic approach allows one to efficiently analyze the association between rare variants and disease while avoiding assumptions required by other approaches for grouping such variants.
View details for DOI 10.1371/journal.pone.0013584
View details for Web of Science ID 000283780800001
View details for PubMedID 21072163
View details for PubMedCentralID PMC2972202
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Segmentation and Estimation for SNP Microarrays: A Bayesian Multiple Change-Point Approach
BIOMETRICS
2010; 66 (3): 675-683
Abstract
High-density single-nucleotide polymorphism (SNP) microarrays provide a useful tool for the detection of copy number variants (CNVs). The analysis of such large amounts of data is complicated, especially with regard to determining where copy numbers change and their corresponding values. In this article, we propose a Bayesian multiple change-point model (BMCP) for segmentation and estimation of SNP microarray data. Segmentation concerns separating a chromosome into regions of equal copy number differences between the sample of interest and some reference, and involves the detection of locations of copy number difference changes. Estimation concerns determining true copy number for each segment. Our approach not only gives posterior estimates for the parameters of interest, namely locations for copy number difference changes and true copy number estimates, but also useful confidence measures. In addition, our algorithm can segment multiple samples simultaneously, and infer both common and rare CNVs across individuals. Finally, for studies of CNVs in tumors, we incorporate an adjustment factor for signal attenuation due to tumor heterogeneity or normal contamination that can improve copy number estimates.
View details for DOI 10.1111/j.1541-0420.2009.01328.x
View details for Web of Science ID 000281950000002
View details for PubMedID 19764955
View details for PubMedCentralID PMC3766751
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Genome-Wide Association Studies and Beyond
ANNUAL REVIEW OF PUBLIC HEALTH, VOL 31
2010; 31: 9-20
Abstract
Genome-wide association studies (GWAS) provide an important avenue for undertaking an agnostic evaluation of the association between common genetic variants and risk of disease. Recent advances in our understanding of human genetic variation and the technology to measure such variation have made GWAS feasible. Over the past few years a multitude of GWAS have identified and replicated many associated variants. These findings are enriching our knowledge about the genetic basis of disease and leading some to advocate using GWA study results for genetic testing. For many of the GWA study results, however, the underlying mechanisms remain unclear and the findings explain only a limited amount of heritability. These issues may be clarified by more detailed investigations, including analyses of less common variants, sequence-level data, and environmental exposures. Such studies should help clarify the potential value of genetic testing to the public's health.
View details for DOI 10.1146/annurev.publhealth.012809.103723
View details for Web of Science ID 000277908800002
View details for PubMedID 20235850
View details for PubMedCentralID PMC3997166
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VALID: Visualization of Association Study Results and Linkage Disequilibrium
GENETIC EPIDEMIOLOGY
2009; 33 (7): 599-603
Abstract
Promising findings from genetic association studies are commonly presented with two distinct figures: one gives the association study results and the other indicates linkage disequilibrium (LD) between genetic markers in the region(s) of interest. Fully interpreting the results of such studies requires synthesizing the information in these figures, which is generally done in a subjective and unsystematic manner. Here we present a method to formally combine association results and LD and display them in the same figure; we have developed a freely available web-based application that can be used to generate figures to display the combined data. To demonstrate this approach we apply it to fine mapping data from the prostate cancer 8q24 loci. Combining these two sources of information in a single figure allows one to more clearly assess patterns of association, facilitating the interpretation of genome-wide and fine mapping data and improving our ability to localize causal variants.
View details for DOI 10.1002/gepi.20411
View details for Web of Science ID 000271406100004
View details for PubMedID 19197947
View details for PubMedCentralID PMC3258024
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Socioeconomic status and prostate cancer incidence and mortality rates among the diverse population of California
CANCER CAUSES & CONTROL
2009; 20 (8): 1431-1440
Abstract
The racial/ethnic disparities in prostate cancer rates are well documented, with the highest incidence and mortality rates observed among African-Americans followed by non-Hispanic Whites, Hispanics, and Asian/Pacific Islanders. Whether socioeconomic status (SES) can account for these differences in risk has been investigated in previous studies, but with conflicting results. Furthermore, previous studies have focused primarily on the differences between African-Americans and non-Hispanic Whites, and little is known for Hispanics and Asian/Pacific Islanders.To further investigate the relationship between SES and prostate cancer among African-Americans, non-Hispanic Whites, Hispanics, and Asian/Pacific Islanders, we conducted a large population-based cross-sectional study of 98,484 incident prostate cancer cases and 8,997 prostate cancer deaths from California.Data were abstracted from the California Cancer Registry, a population-based surveillance, epidemiology, and end results (SEER) registry. Each prostate cancer case and death was assigned a multidimensional neighborhood-SES index using the 2000 US Census data. SES quintile-specific prostate cancer incidence and mortality rates and rate ratios were estimated using SEER*Stat for each race/ethnicity categorized into 10-year age groups.For prostate cancer incidence, we observed higher levels of SES to be significantly associated with increased risk of disease [SES Q1 vs. Q5: relative risk (RR) = 1.28; 95% confidence interval (CI): 1.25-1.30]. Among younger men (45-64 years), African-Americans had the highest incidence rates followed by non-Hispanic Whites, Hispanics, and Asian/Pacific Islanders for all SES levels. Yet, among older men (75-84 years) Hispanics, following African-Americans, displayed the second highest incidence rates of prostate cancer. For prostate cancer deaths, higher levels of SES were associated with lower mortality rates of prostate cancer deaths (SES Q1 vs. Q5: RR = 0.88; 95% CI: 0.92-0.94). African-Americans had a twofold to fivefold increased risk of prostate cancer deaths in comparison to non-Hispanic Whites across all levels of SES.Our findings suggest that SES alone cannot account for the greater burden of prostate cancer among African-American men. In addition, incidence and mortality rates of prostate cancer display different age and racial/ethnic patterns across gradients of SES.
View details for DOI 10.1007/s10552-009-9369-0
View details for Web of Science ID 000270737900020
View details for PubMedID 19526319
View details for PubMedCentralID PMC2746891
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Carboxypeptidase 4 gene variants and early-onset intermediate-to-high risk prostate cancer
BMC CANCER
2009; 9
Abstract
Carboxypeptidase 4 (CPA4) is a zinc-dependent metallocarboxypeptidase on chromosome 7q32 in a region linked to prostate cancer aggressiveness. CPA4 is involved in the histone hyperacetylation pathway and may modulate the function of peptides that affect the growth and regulation of prostate epithelial cells. We examined the association between genetic variation in CPA4 and intermediate-to-high risk prostate cancer.We studied 1012 men (506 cases and 506 controls) from Cleveland, Ohio. All cases had Gleason > or = 7, clinical stage > or = T2c, or PSA > or = 10 ng/mL at diagnosis. Six CPA4 single-nucleotide polymorphisms were genotyped, and evaluated for their relation to prostate cancer. We also evaluated whether CPA4 variants influence risk of disease among men diagnosed at an earlier age (< 66 years).The nonsynonymous coding SNP (rs2171492, Cys303Gly) in CPA4 was associated with an increased risk of aggressive prostate cancer among younger patients (< 66 years). Specifically, men carrying the TT genotype had an approximately two-fold increased risk for being diagnosed with intermediate-to-high risk disease (Odds Ratio = 1.83, p = 0.04). In the overall population (all ages) none of the CPA4 SNPs demonstrated a statistically significant association with prostate cancer.Coding variation in CPA4 may confer increased risk of intermediate-to-high risk prostate cancer among younger patients. Further work is needed to identify the functional aspects of this variation and understand its biological effects on prostate cancer. Such work may translate into more precise screening of higher risk individuals as well as guiding clinicians and patients toward earlier and more definitive treatment modalities in patients genetically identified as higher risk.
View details for DOI 10.1186/1471-2407-9-69
View details for Web of Science ID 000264914200001
View details for PubMedID 19245716
View details for PubMedCentralID PMC2657151
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Prostate cancer genomics: towards a new understanding
NATURE REVIEWS GENETICS
2009; 10 (2): 77-82
Abstract
Recent genetics and genomics studies of prostate cancer have helped to clarify the genetic basis of this common but complex disease. Genome-wide studies have detected numerous variants associated with disease as well as common gene fusions and expression 'signatures' in prostate tumours. On the basis of these results, some advocate gene-based individualized screening for prostate cancer, although such testing might only be worthwhile to distinguish disease aggressiveness. Lessons learned from these studies provide strategies for further deciphering the genetic causes of prostate cancer and other diseases.
View details for DOI 10.1038/nrg2507
View details for Web of Science ID 000263091500009
View details for PubMedID 19104501
View details for PubMedCentralID PMC2721916
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ω-3 Fatty Acids, Genetic Variants in COX-2 and Prostate Cancer
JOURNAL OF NUTRIGENETICS AND NUTRIGENOMICS
2009; 2 (3): 149-158
Abstract
Dietary intake of fish and omega-3 polyunsaturated fatty acids (omega-3 PUFAs) may decrease the risk of prostate cancer development and progression to advanced stage disease. This could reflect the anti-inflammatory effects of PUFAs, possibly through mediation of cyclooxygenase (COX), a key enzyme in fatty acid metabolism and inflammation. Despite promising experimental evidence, epidemiological studies have reported somewhat conflicting results regarding the effects of fish/PUFAs on prostate cancer development and progression. The literature suggests that fish, and particularly long-chain omega-3 PUFAs, may have a more pronounced protective effect on biologically aggressive tumors or on their progression, and less on early steps of carcinogenesis. Moreover, the impact of LC omega-3 PUFAs may be modified by variation of the COX-2 gene. Overall, results to date support the hypothesis that long-chain omega-3 PUFAs may impact prostate inflammation and carcinogenesis via the COX-2 enzymatic pathway.
View details for DOI 10.1159/000235565
View details for Web of Science ID 000270915800005
View details for PubMedID 19776642
View details for PubMedCentralID PMC2820568
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8q24 and prostate cancer: association with advanced disease and meta-analysis
EUROPEAN JOURNAL OF HUMAN GENETICS
2008; 16 (4): 496-505
Abstract
Compelling evidence demonstrates chromosome 8q24 as a prostate cancer susceptibility locus. Multiple variants within three adjacent regions at 8q24 have recently been identified to impact the risk of prostate cancer. Yet, the role of these variants in more advanced disease has not been rigorously assessed. To examine the relationship between 8q24 variants and advanced disease, we tested 10 previously associated 8q24 variants in a case-control study of advanced prostate cancer (N=1012). Of these ten 8q24 variants, six were associated with the risk of advanced prostate cancer (P=0.001-0.038). Three of these variants (rs10090154-region 1, rs16901979-region 2, and rs6983267-region 3), each variant residing in one of the three previously reported 8q24 regions, could account for our 8q24 effects on advanced disease. A meta-analysis across 10 studies including our results of four 8q24 variants (rs1442295 and DG8S737-region 1, rs16901979-region 2, and rs6983267-region 3) and prostate cancer risk demonstrated strong associations across a wide array of study designs and populations. Our findings provide the first confirmation that the three 8q24 regions independently influence the risk of prostate cancer and, in particular, advanced disease.
View details for DOI 10.1038/sj.ejhg.5201959
View details for Web of Science ID 000254134700012
View details for PubMedID 18231127
View details for PubMedCentralID PMC2819154
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Enriching the analysis of genomewide association studies with hierarchical modeling
AMERICAN JOURNAL OF HUMAN GENETICS
2007; 81 (2): 397-404
Abstract
Genomewide association studies (GWAs) initially investigate hundreds of thousands of single-nucleotide polymorphisms (SNPs), and the most promising SNPs are further evaluated with additional subjects, for replication or a joint analysis. Deciding which SNPs merit follow-up is one of the most crucial aspects of these studies. We present here an approach for selecting the most-promising SNPs that incorporates into a hierarchical model both conventional results and other existing information about the SNPs. The model is developed for general use, its potential value is shown by application, and tools are provided for undertaking hierarchical modeling. By quantitatively harnessing all available information in GWAs, hierarchical modeling may more clearly distinguish true causal variants from noise.
View details for DOI 10.1086/519794
View details for Web of Science ID 000248540400019
View details for PubMedID 17668389
View details for PubMedCentralID PMC1950795
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MIC1 and IL1RN genetic variation and advanced prostate cancer risk
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2007; 16 (6): 1309-1311
View details for DOI 10.1158/1055-9965.EPI-07-0165
View details for Web of Science ID 000247163100045
View details for PubMedID 17548705
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<i>trans</i>-Fatty acid intake and increased risk of advanced prostate cancer:: modification by <i>RNASEL</i> R462Q variant
CARCINOGENESIS
2007; 28 (6): 1232-1236
Abstract
Previous studies have examined the role of higher trans-fatty acid consumption on prostate cancer risk, but the results remain unclear. Any potential association may be modified by variants in genes involved with immune and inflammatory responses. To investigate this, we undertook a case-control study (N = 1012) of the association between trans-fatty acid intake and advanced prostate cancer, and evaluated whether this effect was modified by a functional polymorphism in the RNASEL gene (R462Q). Among Caucasians (N = 834), we observed that each type of trans-fatty acid and total trans-fatty acid intake showed a statistically significant positive association with prostate cancer, but only weakly increased risk for the isomers of cis-fatty acids. Compared with the lowest quartile of total trans-fatty acid consumption, the higher quartiles gave odds ratios (ORs) equal to 1.58 [95% confidence interval (CI): 1.00, 2.48], 1.95 (95% CI: 1.20, 3.19) and 2.77 (95% CI: 1.60, 4.79) (P-trend = 0.0003); this effect was modified by the RNASEL R462Q polymorphism (P(interaction) = 0.01). Among men with the QQ/RQ genotype, the association between total trans-fatty acid intake and prostate cancer was substantially stronger [ORs of higher quartiles equal to 2.93 (95% CI: 1.62, 5.30), 3.13 (95% CI: 1.64, 5.98) and 4.80 (95% CI: 2.29, 10.08), respectively]. For men with the RR genotype, total trans-fatty acid intake was not associated with disease. This suggests that among Caucasians, positive association between higher trans-fatty acid consumption and prostate cancer may be modified by the functional RNASEL variant R462Q.
View details for DOI 10.1093/carcin/bgm002
View details for Web of Science ID 000247999700014
View details for PubMedID 17234723
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Association of testis derived transcript gene variants and prostate cancer risk
JOURNAL OF UROLOGY
2007; 177 (3): 894-898
Abstract
The testis derived transcript gene has been suggested as a tumor suppressor gene for prostate cancer at 7q31. To investigate this concept we evaluated the effects of 7 tagging single nucleotide polymorphisms that comprehensively captured the common genetic variants in TES on aggressive prostate cancer in a case-control study.A total of 506 cases diagnosed with aggressive prostate cancer, and an equal number of age, institute and ethnicity matched controls, were recruited from the major medical institutions in Cleveland, Ohio. A logistic regression model was used to evaluate the association between SNPs/multimarker haplotypes and prostate cancer.When looking at all study subjects and white men only, no statistically significant associations were observed between any variants and more aggressive disease. However, 3 variants showed inverse associations with disease in black men (178), including 2 intronic SNPs (rs2402056, rs1004109) and 1 SNP close to the 3' untranslated region (rs4730721) with ORs of 0.57 (95% CI 0.36-0.90, under an additive mode of inheritance), 0.57 (95% CI 0.36-0.91, under an additive mode of inheritance) and 0.45 (95% CI 0.21-0.98, under a dominant mode of inheritance), respectively. Variants rs2402056 and rs1004109 are in tight linkage disequilibrium (r2=0.8) and the reconstructed haplotype did not provide any additional evidence for association than their genotype level results.Our findings suggest that the variants in TES, or in a nearby gene, may be associated with prostate cancer in black men.
View details for DOI 10.1016/j.juro.2006.10.057
View details for Web of Science ID 000244211600022
View details for PubMedID 17296370
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Dissecting effects of complex mixtures: who's afraid of informative priors?
Epidemiology (Cambridge, Mass.)
2007; 18 (2): 186-90
Abstract
Epidemiologic studies commonly investigate multiple correlated exposures, which are difficult to analyze appropriately. Hierarchical modeling provides a promising approach for analyzing such data by adding a higher-level structure or prior model for the exposure effects. This prior model can incorporate additional information on similarities among the correlated exposures and can be parametric, semiparametric, or nonparametric. We discuss the implications of applying these models and argue for their expanded use in epidemiology. While a prior model adds assumptions to the conventional (first-stage) model, all statistical methods (including conventional methods) make strong intrinsic assumptions about the processes that generated the data. One should thus balance prior modeling assumptions against assumptions of validity, and use sensitivity analyses to understand their implications. In doing so - and by directly incorporating into our analyses information from other studies or allied fields - we can improve our ability to distinguish true causes of disease from noise and bias.
View details for DOI 10.1097/01.ede.0000254682.47697.70
View details for PubMedID 17301703
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Plasminogen activator inhibitor type-I (<i>PAI-I</i>) polymorphism 4G/5G is associated with prostate cancer among men with a positive family history
PROSTATE
2007; 67 (2): 172-177
Abstract
Variation in the expression of plasminogen activator inhibitor type-1 (PAI-1) is associated with many human diseases, including several types of cancer. In particular, tumor cell overexpression of PAI-1 has been found to inhibit prostate cancer tumor growth, angiogenesis, and metastasis in mouse models. Normal host cell expression of PAI-1 is influenced by the 4G/5G insertion/deletion polymorphism in the promoter region of the PAI-1 gene. To evaluate the effect of PAI-1 expression on cancer development, we examined the association of the 4G/5G polymorphism in a sibling-based case-control study of prostate cancer.One thousand one hundred thirty seven subjects, 655 cases, and 482 sibling controls from 526 families, were recruited from the major medical institutions in the greater Cleveland, OH area and from the Henry Ford Health System, Detroit, MI. A Cox age-of-onset model with robust variance estimation was used to evaluate the association between the PAI-1 4G/5G polymorphism and prostate cancer.No association was observed between the PAI-1 4G/5G polymorphism and prostate cancer in the entire sample. We did, however, identify a statistically significant association between the PAI-1 4G/5G polymorphism and prostate cancer in subjects with a family history of this disease (OR = 1.28, 95% CI 1.02-1.61, P-value = 0.036). The PAI-1 5G/5G genotype, associated with lower PAI-1 expression, appears to drive this result as it was associated with an increased risk of prostate cancer and an earlier mean age of onset compared to those with the 4G/4G genotype (OR = 1.83, 95% CI 1.12-2.99) while the 4G/5G genotype group did not show a significant difference in prostate cancer risk compared to the 4G/4G genotype group (OR = 0.98, 95% CI 0.75-1.28).These observations suggest that the 4G/5G polymorphism in PAI-1 may explain some of the increased risk and earlier mean age of onset of prostate cancer due to a positive family history.
View details for DOI 10.1002/pros.20512
View details for Web of Science ID 000243765400007
View details for PubMedID 17044080
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An empirical evaluation of the common disease-common variant hypothesis.
BMC proceedings
2007; 1 Suppl 1: S5
Abstract
While genome-wide linkage studies have been successful in mapping variants underlying rare monogenic disorders, genome-wide association studies may be more appropriate for detecting common variants of modest effects that underlie common disorders. To this end, we were interested in determining whether genetic variants associated with a phenotype differed depending on whether they were within or outside of regions linked to the phenotype. In particular, we compared allele frequencies and effect sizes between associated single-nucleotide polymorphisms within and outside of linkage regions using the Genetic Analysis Workshop 15 Problem 1. We did not find any statistically significant differences between these two sets. However, our power calculations show that these results may be inconclusive.
View details for PubMedID 18466549
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Nonsteroidal antiinflammatory drugs and decreased risk of advanced prostate cancer: Modification by lymphotoxin alpha
AMERICAN JOURNAL OF EPIDEMIOLOGY
2006; 164 (10): 984-989
Abstract
The potentially protective effect of nonsteroidal antiinflammatory drugs (NSAIDs) on prostate cancer may only exist among certain subgroups of men, such as those with particular variants in inflammatory response genes. To investigate this, the authors undertook a case-control study (n = 1,012) of the association between NSAIDs and more advanced prostate cancer in Ohio men recruited between 2001 and 2004 and evaluated whether this association was modified by a functional polymorphism in the lymphotoxin alpha (LTA) gene (LTA C+80A, where the CC genotype results in higher LTA production). The authors observed an inverse association between aspirin or ibuprofen use and disease (odds ratio = 0.67, 95% confidence interval: 0.52, 0.87). This was modified by the LTA C+80A variant (p for interaction = 0.03): Among men with the CC genotype, the inverse association between NSAIDs and prostate cancer was substantially stronger (odds ratio = 0.43, 95% confidence interval: 0.28, 0.67). For men without the CC genotype, NSAID use was not associated with disease (p = 0.30). The authors observed similar associations when examining dose/duration of NSAID use. This suggests that any potential chemoprevention of prostate cancer by NSAIDs may be most appropriate for men with the LTA +80CC genotype.
View details for DOI 10.1093/aje/kwj294
View details for Web of Science ID 000241958900009
View details for PubMedID 16931544
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A gene-centric approach to genome-wide association studies
NATURE REVIEWS GENETICS
2006; 7 (11): 885-891
Abstract
Genic variants are more likely to alter gene function and affect disease risk than those that occur outside genes. Variants in genes, however, might not be sufficiently covered by the existing approaches to genome-wide association studies. Our analysis of the HapMap ENCODE data indicates that this concern is valid, and that an alternative approach that focuses on genic variants provides a more complete coverage of functionally important regions and a greater genotyping efficiency. We therefore argue that resources should be developed to make gene-centric genome-wide association studies feasible.
View details for DOI 10.1038/nrg1962
View details for Web of Science ID 000241384100016
View details for PubMedID 17047687
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Polymorphisms in estrogen bioactivation, detoxification and oxidative DNA base excision repair genes and prostate cancer risk
CARCINOGENESIS
2006; 27 (9): 1842-1848
Abstract
To date, the potential impact of hormones on prostate cancer has predominantly focused on receptor-mediated events. However, catechol estrogens, if not inactivated by catechol-O-methyltransferase (COMT), can generate large quantities of reactive oxygen species (ROS). ROS may cause a spectrum of damage including oxidative DNA base lesions, which can lead to irreversible mutation(s) if they are not repaired by base excision repair (BER) systems. hOGG1 is a key enzyme in short patch BER because it recognizes and performs initial excision of the most common form of oxidative DNA base damage, 8-hydroxyguanine (8-oxo-dG). To investigate potential non-receptor-mediated estrogen effects, we evaluated the association between COMT Val158Met and hOGG1 Ser326Cys polymorphisms and prostate cancer in a family-based case-control study (439 prostate cancer cases, 479 brother controls). We observed no noteworthy associations between these polymorphisms and prostate cancer risk in the total study population. However, among men with more aggressive prostate cancer, the hOGG1 326 Cys/Cys genotype was inversely associated with disease (OR=0.30; 95% CI=0.09-0.98). Combining the lower activity CYP1B1 432 Leu/Leu or Leu/Val genotypes (which may decrease the level of catechol estrogens and ROS generated) with the hOGG1 326 Cys/Cys genotype and the XRCC1 399 Arg/Arg or Arg/Gln genotypes (which may enhance BER) resulted in an even further reduced risk in Caucasians with more aggressive disease (OR=0.09; 95% CI=0.01-0.56). Including the high-activity COMT 158Val allele to this combination also lowered aggressive prostate cancer risk but the effect was not as strong (OR=0.20; 95% CI=0.05-0.88). The decreased risk we observed with the hOGG1 326 Cys/Cys genotype confirms an earlier report and the further reduced risk found with the CYP1B1 (432 Leu/Leu or Leu/Val)-hOGG1 (326 Cys/Cys)-XRCC1 (Arg/Arg or Arg/Gln) genotype combination may lend new insights to the importance of ROS generated from non-receptor-mediated estrogenic mechanisms in more aggressive prostate cancer.
View details for DOI 10.1093/carcin/bgl022
View details for Web of Science ID 000239901000013
View details for PubMedID 16569655
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Novel missense mutations of the Deleted-in-AZoospermia-Like (DAZL) gene in infertile women and men
REPRODUCTIVE BIOLOGY AND ENDOCRINOLOGY
2006; 4
Abstract
The Deleted-in-AZoospermia-Like (DAZL) gene has homologs required for germ cell development in many organisms. Recently, we showed that there are several common polymorphisms within the DAZL gene that are associated with age at ovarian failure/menopause and sperm count.Here we sought to identify rare mutations in DAZL and examine their phenotypes in men and women. We sequenced the DAZL gene in 519 individuals; sequences spanned the entire coding region of the gene.We report the identification of four putative missense mutations in DAZL. Three individuals that were heterozygous for a DAZL mutation reported having children, while two individuals that were homozygous reported no children. These mutations were found only in infertile men and women.Given the strong data associating DAZL polymorphisms and deletions with fertility in humans and model organisms, we suggest that these mutations may be associated with age at menopause and/or sperm count and warrant further biochemical and genetic investigation.
View details for DOI 10.1186/1477-7827-4-40
View details for Web of Science ID 000240146900001
View details for PubMedID 16884537
View details for PubMedCentralID PMC1557510
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Coverage and power in genomewide association studies
AMERICAN JOURNAL OF HUMAN GENETICS
2006; 78 (5): 884-888
Abstract
The ability of genomewide association studies to decipher genetic traits is driven in part by how well the measured single-nucleotide polymorphisms "cover" the unmeasured causal variants. Estimates of coverage based on standard linkage-disequilibrium measures, such as the average maximum squared correlation coefficient (r2), can lead to inaccurate and inflated estimates of the power of genomewide association studies. In contrast, use of the "cumulative r2 adjusted power" measure presented here gives more-accurate estimates of power for genomewide association studies.
View details for DOI 10.1086/503751
View details for Web of Science ID 000236756200014
View details for PubMedID 16642443
View details for PubMedCentralID PMC1474045
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Polymorphisms in polycyclic aromatic hydrocarbon metabolism and conjugation genes, interactions with smoking and prostate cancer risk
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2006; 15 (4): 756-761
Abstract
The relationship between cigarette smoking and prostate cancer remains unclear. Any potential association may depend on the individuals' ability to metabolize and detoxify cigarette carcinogens--such as polycyclic aromatic hydrocarbons. To investigate this, we studied the association between prostate cancer and smoking, as well as the main and modifying effects of functional polymorphisms in genes that metabolize polycyclic aromatic hydrocarbons (CYP1A1 Ile(462)Val, microsomal epoxide hydrolase His(139)Arg) and detoxify reactive derivatives (GSTM1 null deletion, GSTT1 null deletion, GSTP1 Ile(105)Val and Ala(114)Val) using a family-based case-control design (439 prostate cancer cases and 479 brother controls). Within the entire study population, there were no main effects for smoking or any of the polymorphisms. However, the nondeleted GSTM1 allele was inversely associated with prostate cancer [odds ratio (OR), 0.50; 95% confidence interval (95% CI), 0.26-0.94] among men with less aggressive disease (Gleason score < 7 and clinical tumor stage < T2c) and positively associated (OR, 1.68; 95% CI, 1.01-2.79) with prostate cancer in men with more aggressive disease (Gleason score > or = 7 or clinical tumor stage > or = T2c). We also found a statistically significant negative multiplicative interaction between the GSTM1 nondeleted allele and heavy smoking (> 20 pack-years) in the total study population (P = 0.01) and in Caucasians (P = 0.01). Among Caucasians, heavy smoking increased prostate cancer risk nearly 2-fold in those with the GSTM1 null genotype (OR, 1.73; 95% CI, 0.99-3.05) but this increased risk was not observed in heavy smokers who carried the GSTM1 nondeleted allele (OR, 0.95; 95% CI, 0.53-1.71). Our results highlight the importance of considering genetic modifiers of carcinogens when evaluating smoking in prostate cancer.
View details for DOI 10.1158/1055-9965.EPI-05-0826
View details for Web of Science ID 000237045100025
View details for PubMedID 16614120
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Hierarchical modeling in association studies of multiple phenotypes
BIOMED CENTRAL LTD. 2005: S104
Abstract
The genetic study of disease-associated phenotypes has become common because such phenotypes are often easier to measure and in many cases are under greater genetic control than the complex disease itself. Some disease-associated phenotypes are rare, however, making it difficult to evaluate their effects due to small informative sample sizes. In addition, analyzing numerous phenotypes introduces the issue of multiple comparisons. To address these issues, we have developed a hierarchical model (HM) for multiple phenotypes that provides more accurate effect estimates with a lower false-positive rate. We evaluated the validity and power of HM in association studies of multiple phenotypes using randomly selected cases and controls from the simulated data set in the Genetic Analysis Workshop 14. In particular, we first analyzed the association between each of the 12 subclinical phenotypes and single-nucleotide polymorphisms within the known causal loci using a conventional logistic regression model (LRM). Then we added a second-stage model by regressing all of the logistic coefficients of the phenotypes obtained from LRM on a Z matrix that incorporates the clinical correlation of the phenotypes. Specially, the 12 phenotypes were grouped into 3 clusters: 1) communally shared emotions; 2) behavioral related; and 3) anxiety related. A semi-Bayes HM effect estimate for each phenotype was calculated and compared with those from LRM. We observed that using HM to evaluate the association between SNPs and multiple related phenotypes slightly increased power for detecting the true associations and also led to fewer false-positive results.
View details for DOI 10.1186/1471-2156-6-S1-S104
View details for Web of Science ID 000236103400104
View details for PubMedID 16451560
View details for PubMedCentralID PMC1866835
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Relationship between body size and prostate cancer in a sibling based case-control study
JOURNAL OF UROLOGY
2005; 174 (6): 2169-2173
Abstract
Body size has been hypothesized to affect the risk of prostate cancer (PCa). However, previous studies have provided conflicting results, in that some show positive associations, whereas others indicate inverse associations or null findings. To further understand this we examined the effects of weight, height, body mass index and lean body mass (LBM) on PCa risk and aggressiveness in a sibling based case-control study.A total of 439 cases were recruited at major medical institutions in Cleveland, Ohio and Detroit, Michigan, and 479 unaffected brothers were recruited as controls. Conditional logistic regression with robust variance estimation was used to evaluate the association between body size and PCa.Higher LBM was inversely associated with PCa, especially in men with more aggressive disease or a later age at onset. Comparing those above and below the 25th percentile showed an OR of 0.49 (95% CI 0.28 to 0.84) and 0.28 (95% CI 0.14, 0.56), respectively. Similar inverse patterns were observed for weight. No noteworthy associations were observed between PCa and height or body mass index.These observations suggest that PCa may be affected by LBM.
View details for DOI 10.1097/01.ju.0000181207.02213.06
View details for Web of Science ID 000233293700026
View details for PubMedID 16280757
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No association between genetic polymorphisms in insulin and insulin receptor substrate-1 and prostate cancer
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2005; 14 (10): 2462-2463
View details for DOI 10.1158/1055-9965.EPI-05-0531
View details for Web of Science ID 000232473400031
View details for PubMedID 16214935
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No association between a tetranucleotide repeat polymorphism of CYP19 and prostate cancer
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2004; 13 (12): 2280-2281
View details for Web of Science ID 000226077100045
View details for PubMedID 15598794
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Relationship between methylenetetrahydrofolate reductase C677T and A1298C genotypes and haplotypes and prostate cancer risk and aggressiveness
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2004; 13 (8): 1331-1336
Abstract
Previous reports indicate that polymorphisms in the MTHFR gene play a role in cancer development, but their potential impact on prostate cancer has not been well studied. Here, we evaluate the association between two MTHFR polymorphisms, C677T and A1298C, and prostate cancer risk and aggressiveness in a moderately large family-based case-control study (439 cases and 479 sibling controls). Among all study subjects, we observed no association between the C677T variant and prostate cancer but a slight positive association between the A1298C variant and risk of this disease [odds ratio (OR) 1.41, 95% confidence interval (CI) 0.96-2.06; P = 0.08]. When stratifying the study population by disease aggressiveness at diagnosis, the C677T variant was positively associated with risk among men with less advanced disease (OR 1.86, 95% CI 1.00-3.46; P = 0.05). In contrast, when looking at men with more advanced disease, the C677T variant was inversely associated with risk (OR 0.51, 95% CI 0.32-0.82; P = 0.01), whereas the A1298C variant was positively associated with risk (OR 1.79, 95% CI 1.06-3.02; P = 0.03). Furthermore, the 677T-1298A haplotype was positively associated with prostate cancer among men with less advanced disease (OR 1.84, 95% CI 1.07-3.16; P = 0.03) and inversely associated with risk of more advanced disease (OR 0.47, 95% CI 0.29-0.76; P = 0.002). Our findings suggest that 677T and 1298A, or another variant on their haplotype, may be associated with a reduced risk of progression to more advanced prostate cancer.
View details for Web of Science ID 000223155500011
View details for PubMedID 15298954
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Genetic dissection of complex traits with chromosome substitution strains of mice
SCIENCE
2004; 304 (5669): 445-448
Abstract
Chromosome substitution strains (CSSs) have been proposed as a simple and powerful way to identify quantitative trait loci (QTLs) affecting developmental, physiological, and behavioral processes. Here, we report the construction of a complete CSS panel for a vertebrate species. The CSS panel consists of 22 mouse strains, each of which carries a single chromosome substituted from a donor strain (A/J) onto a common host background (C57BL/6J). A survey of 53 traits revealed evidence for 150 QTLs affecting serum levels of sterols and amino acids, diet-induced obesity, and anxiety. These results demonstrate that CSSs greatly facilitate the detection and identification of genes that control the wide diversity of naturally occurring phenotypic variation in the A/J and C57BL/6J inbred strains.
View details for DOI 10.1126/science.1093139
View details for Web of Science ID 000220845400050
View details for PubMedID 15031436
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Comprehensive evaluation of the association between prostate cancer and genotypes/haplotypes in CYP17A1, CYP3A4, and SRD5A2
EUROPEAN JOURNAL OF HUMAN GENETICS
2004; 12 (4): 321-332
Abstract
Genes involved in the testosterone biosynthetic pathway - such as CYP17A1, CYP3A4, and SRD5A2 - represent strong candidates for affecting prostate cancer. Previous work has detected associations between individual variants in these three genes and prostate cancer risk and aggressiveness. To more comprehensively evaluate CYP17A1, CYP3A4, and SRD5A2, we undertook a two-phase study of the relationship between their genotypes/haplotypes and prostate cancer. Phase I of the study first searched for single-nucleotide polymorphisms (SNPs) in these genes by resequencing 24 individuals from the Coriell Polymorphism Discovery Resource, 92-110 men from prostate cancer case-control sibships, and by leveraging public databases. In all, 87 SNPs were discovered and genotyped in 276 men from case-control sibships. Those SNPs exhibiting preliminary case-control allele frequency differences, or distinguishing (ie, 'tagging') common haplotypes across the genes, were identified for further study (24 SNPs in total). In Phase II of the study, the 24 SNPs were genotyped in an additional 841 men from case-control sibships. Finally, associations between genotypes/haplotypes in CYP17A1, CYP3A4, and SRD5A2 and prostate cancer were evaluated in the total case-control sample of 1117 brothers from 506 sibships. Family-based analyses detected associations between prostate cancer risk or aggressiveness and a number of CYP3A4 SNPs (P-values between 0.006 and 0.05), a CYP3A4 haplotype (P-values 0.05 and 0.009 in nonstratified and stratified analysis, respectively), and two SRD5A2 SNPs in strong linkage disequilibrium (P=0.02). Undertaking a two-phase study comprising SNP discovery, haplotype tagging, and association analyses allowed us to more fully decipher the relation between CYP17A1, CYP3A4, and SRD5A2 and prostate cancer.
View details for DOI 10.1038/sj.ejhg.5201101
View details for Web of Science ID 000220879300010
View details for PubMedID 14560315
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Association of prostate cancer risk and aggressiveness to androgen pathway genes:: <i>SRD5A2,</i> <i>CYP17</i>, and the <i>AR</i>
PROSTATE
2004; 59 (1): 69-76
Abstract
The prostate is an androgen-regulated organ and polymorphisms in genes involved in testosterone synthesis, in particular, SRD5A2 (A49T and V89L variants), CYP17 (MspAI variant), and the AR (CAG, GGC repeats), represent candidate risk factors for prostate cancer incidence and aggressiveness.We evaluated the relationship between these five polymorphisms and prostate cancer risk in a family-based case-control study (N = 920). Cases were diagnosed at major medical institutions in Cleveland Ohio, and Detroit Michigan, and their unaffected brothers were used as controls. Associations were investigated with regard to prostate cancer risk, and clinical characteristics at diagnosis (i.e., tumor stage/grade, age, family history).The SRD5A2 V89L variant was associated with an increased risk of prostate cancer (OR = 1.56, P = 0.02). This association was driven primarily by men diagnosed at an earlier age (OR = 2.35, P = 0.001), or with more aggressive disease (OR = 1.63, P = 0.06). None of the other variants exhibited noteworthy associations with disease.These findings suggest that the SRD5A2 V89L variant may influence risk of developing prostate cancer, especially among men with a younger age of diagnosis or more aggressive disease.
View details for DOI 10.1002/pros.10358
View details for Web of Science ID 000220392400007
View details for PubMedID 14991867
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No association between genetic Polymorphisms in 1GF-1 and IGFBP-3 and prostate cancer
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2004; 13 (3): 497-498
View details for Web of Science ID 000220081000026
View details for PubMedID 15006930
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DNA repair gene XRCC1 and XPD polymorphisms and risk of prostate cancer
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2004; 13 (1): 23-29
Abstract
The X-ray repair cross-complementing group 1 (XRCC1) and xeroderma pigmentosum group D (XPD) genes are involved in base excision repair and nucleotide excision repair of DNA repair pathways, respectively. A growing body of evidence suggests that XRCC1 and XPD are important in environmentally induced cancers, and polymorphisms in both genes have been identified. To determine whether the XRCC1 (codon Arg399Gln) and XPD (codon Asp312Asn and codon Lys751Gln) polymorphisms are associated with prostate cancer susceptibility, we genotyped these polymorphisms in a primarily Caucasian sample of 506 sibships (n = 1,117) ascertained through a brother with prostate cancer. Sibships were analyzed with a Cox proportional hazards model with age at prostate cancer diagnosis as the outcome. Of the three polymorphisms investigated, only the XPD codon 312 Asn/Asn genotype had an odds ratio (OR) significantly different from one (OR, 1.61; 95% CI, 1.03-2.53). Analyses stratified by the clinical characteristics of affected brothers in the sibship did not reveal any significant heterogeneity in risk. In exploring two-way gene interactions, we found a markedly elevated risk for the combination of the XPD codon 312 Asn/Asn and XRCC1 codon 399 Gln/Gln genotypes (OR, 4.81; 95% CI, 1.66-13.97). In summary, our results suggest that the XPD codon 312 Asn allele may exert a modest positive effect on prostate cancer risk when two copies of the allele are present, and this effect is enhanced by the XRCC codon 399 Gln allele in its recessive state.
View details for DOI 10.1158/1055-9965.EPI-03-0053
View details for Web of Science ID 000188438300006
View details for PubMedID 14744728
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Comparison of missing data approaches in linkage analysis
BIOMED CENTRAL LTD. 2003: S44
Abstract
Observational cohort studies have been little used in linkage analyses due to their general lack of large, disease-specific pedigrees. Nevertheless, the longitudinal nature of such studies makes them potentially valuable for assessing the linkage between genotypes and temporal trends in phenotypes. The repeated phenotype measures in cohort studies (i.e., across time), however, can have extensive missing information. Existing methods for handling missing data in observational studies may decrease efficiency, introduce biases, and give spurious results. The impact of such methods when undertaking linkage analysis of cohort studies is unclear. Therefore, we compare here six methods of imputing missing repeated phenotypes on results from genome-wide linkage analyses of four quantitative traits from the Framingham Heart Study cohort.We found that simply deleting observations with missing values gave many more nominally statistically significant linkages than the other five approaches. Among the latter, those with similar underlying methodology (i.e., imputation- versus model-based) gave the most consistent results, although some discrepancies remained.Different methods for addressing missing values in linkage analyses of cohort studies can give substantially diverse results, and must be carefully considered to protect against biases and spurious findings.
View details for DOI 10.1186/1471-2156-4-S1-S44
View details for Web of Science ID 000188320900044
View details for PubMedID 14975112
View details for PubMedCentralID PMC1866480
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Genome-wide scan of brothers: Replication and fine mapping of prostate cancer susceptibility and aggressiveness loci
PROSTATE
2003; 57 (4): 298-308
Abstract
Substantial evidence suggests that genetic factors play an important role in both the risk of prostate cancer and its biologic aggressiveness. Here we investigate prostate cancer susceptibility and aggressiveness with genome-wide linkage analyses of affected brothers.We first undertook a new genome-wide linkage study of 259 brothers with prostate cancer. Our analyses tested whether the proportion of marker alleles shared by brothers was correlated with disease status or Gleason score. To further clarify 11 linkage regions observed here or previously, we genotyped and analyzed an additional 101 finely spaced markers in the 259 men, and in 594 previously studied brothers, allowing for a pooled genome-wide analysis of 853 affected brothers.In the new study, we detected linkage to prostate cancer on chromosome 16q23 (P = 0.009), replicating previous results, and to chromosome 11q24 (P = 0.001). In the pooled analysis, the 16q23 linkage was strengthened (P = 0.0005), as was our previous linkage to chromosome 16p (P = 0.0001), and we detected linkage to chromosome 2q32 (P = 0.009). When evaluating Gleason score, our new study detected linkage to chromosome 7q32 (P = 0.0009), again replicating previous results, and to chromosomes 5p15 (P = 0.003), 9q34 (P = 0.009), 10q26 (P = 0.03), and 18p11 (P = 0.02). In the pooled analysis of Gleason score, we observed stronger linkage to chromosome 7q32 (P = 0.0002), but slightly weaker linkage to chromosomes 5q33 (P = 0.005) and 19q13 (P = 0.009) than previously reported. In addition, the new linkages to chromosomes 10q26 and 18p11 were strengthened (P = 0.0002 and P = 0.002, respectively).Our results provide compelling evidence for loci harboring prostate cancer susceptibility and tumor aggressiveness genes, especially on chromosomes 16q23 and 7q32.
View details for DOI 10.1002/pros.10304
View details for Web of Science ID 000186871700006
View details for PubMedID 14601026
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Relation of serum insulin-like growth factor-I (IGF-I) and IGF binding protein-3 to risk of prostate cancer (United States)
CANCER CAUSES & CONTROL
2003; 14 (8): 721-726
Abstract
Insulin-like growth factor I (IGF-I) exerts potent mitogenic and antiapoptotic effects on prostatic epithelial cells. Insulin-like growth factor binding protein-3 (IGFBP-3) modulates the effects of IGF-I, and independently induces apoptosis and inhibits cell growth. Previous studies have inconsistently associated IGF-I and IGFBP-3 with prostate cancer. To try and further clarify these potential associations, we undertook a sibling-matched case-control study.Serum IGF-I and IGFBP-3 were determined for 845 men (408 cases and 437 sibling controls). Conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between the serum IGF levels and prostate cancer.Among all study subjects, only the molar ratio of IGF-I to IGFBP-3 was associated with prostate cancer: comparing those in the highest to lowest quartiles gave an OR = 1.62 (95% CI = 1.02-2.57, trend-p = 0.04). Among men with clinically less aggressive disease, we observed positive associations between prostate cancer and high levels of IGF-I (OR = 2.78, 95% CI = 1.06-6.80, trend-p = 0.03), and IGFBP-3 (OR = 2.68, 95% CI = 1.08-6.80, trend-p = 0.04). Simultaneously modeling both left the IGF-I result essentially unchanged, while substantially weakening the IGFBP-3 association.We found that a high IGF-I to IGFBP-3 molar ratio was associated with an increased risk of prostate cancer. Furthermore, high IGF-I was associated with increased risk of prostate cancer among men with less advanced disease at diagnosis. These results lend support to the hypothesis that IGF-I, or the IGF-I to IGFBP-3 molar ratio, is an important risk factor for prostate cancer.
View details for DOI 10.1023/A:1026383824791
View details for Web of Science ID 000186272300004
View details for PubMedID 14674736
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CYP3A4 and CYP3A5 genotypes, haplotypes, and risk of prostate cancer
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2003; 12 (9): 928-932
Abstract
Previous case-only studies have shown that men with the CYP3A4*1B promoter variant are at an increased risk of developing more aggressive forms of prostate cancer. However, no changes in CYP3A4 activity have been found in CYP3A4*1B carriers, suggesting that its association with disease may simply reflect linkage disequilibrium with another functional variant. CYP3A5 is located within 200 kb of CYP3A4, and a variant in CYP3A5 (*1/*3) correlates with function of the CYP3A5 enzyme. In this study, the potential effect of CYP3A4*1B and CYP3A5*1 on prostate cancer risk and aggressiveness were evaluated in a family-based case-control population. The CYP3A4*1B variant was positively associated with prostate cancer among Caucasians with more aggressive disease [odds ratio (OR), 1.91; 95% confidence interval (CI), 1.02-3.57; P=0.04], and inversely associated with risk among Caucasians with less aggressive disease (OR, 0.08; 95% CI, 0.01-0.49; P=0.006) and men with an age of diagnosis <63 (OR, 0.51; 95% CI, 0.26-1.00; P=0.05). The CYP3A5*1 variant was inversely associated with prostate cancer, especially among Caucasians with less aggressive disease (OR, 0.42; 95% CI, 0.22-0.78; P=0.006). As expected based on these genotype-level results, the CYP3A4*1B/CYP3A5*3 haplotype was positively associated with disease (OR, 2.91; 95% CI, 1.36-6.23; P=0.006), and the CYP3A4*1B/CYP3A5*1 haplotype was inversely associated with risk among Caucasians with less aggressive disease (OR, 0.07; 95% CI, 0.01-0.51; P=0.009). These findings suggest that the CYP3A4 and CYP3A5 variants, or other alleles on the haplotypes they help distinguish, are associated with prostate cancer risk and aggressiveness.
View details for Web of Science ID 000185467900019
View details for PubMedID 14504207
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Prostate cancer aggressiveness locus on chromosome segment 19q12-q13.1 identified by linkage and allelic imbalance studies
GENES CHROMOSOMES & CANCER
2003; 36 (4): 332-339
Abstract
Whole-genome scan studies recently identified a locus on chromosome segments 19q12-q13.11 linked to prostate tumor aggressiveness by use of the Gleason score as a quantitative trait. We have now completed finer-scale linkage mapping across this region that confirmed and narrowed the candidate region to 2 cM, with a peak between markers D19S875 and D19S433. We also performed allelic imbalance (AI) studies across this region in primary prostate tumors from 52 patients unselected for family history or disease status. A high level of AI was observed, with the highest rates at markers D19S875 (56%) and D19S433 (60%). Furthermore, these two markers defined a smallest common region of AI of 0.8 Mb, with 15 (29%) prostate tumors displaying interstitial AI involving one or both markers. In addition, we noted a positive association between AI at marker D19S875 and extension of tumor beyond the margin (P = 0.02) as well as a higher Gleason score (P = 0.06). These data provide strong evidence that we have mapped a prostate tumor aggressiveness locus to chromosome segments 19q12-q13.11 that may play a role in both familial and non-familial forms of prostate cancer.
View details for DOI 10.1002/gcc.10165
View details for Web of Science ID 000181479000002
View details for PubMedID 12619157
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Hierarchical modeling of linkage disequilibrum: Genetic structure and spatial relations
AMERICAN JOURNAL OF HUMAN GENETICS
2003; 72 (2): 351-363
Abstract
Linkage disequilibrium (LD) mapping offers much promise for the positional cloning of disease-causing genes. However, conventional estimates of LD may fluctuate substantially across contiguous genomic regions, because of population-specific phenomena such as mutation, genetic drift, population structure, and variations in allele frequencies. This fluctuation makes it difficult to interpret patterns of LD and distinguish where a causal gene is located. To address this issue, we propose hierarchical modeling of LD (HLD) for fine-scale mapping. This approach incorporates information on haplotype block structure and chromosomal spatial relations to refine the pattern of LD, increasing the ability to localize disease genes. Here, we present a framework for HLD, a simulation study assessing the performance of HLD under various scenarios, and an application of HLD to existing data. This work demonstrates that hierarchical modeling of linkage disequilibrium is a valuable and flexible approach for fine-scale mapping.
View details for DOI 10.1086/346117
View details for Web of Science ID 000180680000015
View details for PubMedID 12525994
View details for PubMedCentralID PMC379228
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Prostate cancer aggressiveness locus on chromosome 7q32-q33 identified by linkage and allelic imbalance studies
NEOPLASIA
2002; 4 (5): 424-431
Abstract
The biologic aggressiveness of prostate tumors is an important indicator of prognosis. Chromosome 7q32-q33 was recently reported to show linkage to more aggressive prostate cancer, based on Gleason score, in a large sibling pair study. We report confirmation and narrowing of the linked region using finer-scale genotyping. We also report a high frequency of allelic imbalance (AI) defined within this locus in a series of 48 primary prostate tumors from men unselected for family history or disease status. The highest frequency of AI was observed with adjacent markers D7S2531 (52%) and D7S1804 (36%). These two markers delineated a common region of AI, with 24 tumors exhibiting interstitial AI involving one or both markers. The 1.1-Mb candidate region contains relatively few transcripts. Additionally, we observed positive associations between interstitial AI at D7S1804 and early age at diagnosis (P=.03) as well as a high combined Gleason score and tumor stage (P=.06). Interstitial AI at D7S2531 was associated with a positive family history of prostate cancer (P=.05). These data imply that we have localized a prostate cancer tumor aggressiveness loci to chromosome 7q32-q33 that is involved in familial and nonfamilial forms of prostate cancer.
View details for DOI 10.1038/sj.neo.7900254
View details for Web of Science ID 000177749500007
View details for PubMedID 12192601
View details for PubMedCentralID PMC1564121
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Analysis of mutational spectra: locating hotspots and clusters of mutations using recursive segmentation
STATISTICS IN MEDICINE
2002; 21 (13): 1867-1885
Abstract
Mutations within different regions of disease-causing genes can vary in their impact on disease initiation and progression. Determining how individual mutations within such genes affect disease risk and progression can improve the accuracy of prognoses and help guide treatment selection. Estimates of mutation-specific risks can be poor, however, when genes have a large number of distinct mutations, and data for any given mutation is sparse. To address this problem, we present here a method of analysing the spectrum of mutations observed across a gene that pools together mutations that appear to have similar effects on disease. One of the assumptions underlying the analysis of mutational spectra created in this manner is that the frequency of the mutation in the sample reflects the degree of its effect on disease development. Additionally, mutations that disrupt the same functionally important region of the gene are expected to have a similar impact on disease development. These mutations tend to form a cluster within the spectrum. Therefore, we developed an algorithm that segments a spectrum into regions containing sites with similar mutational frequencies, and have derived by simulation equations that allow one to evaluate whether segmentation is needed. We used this approach to investigate the spectrum of mutations observed in the p53 tumour suppressor gene in colorectal cancer tumours. Here, recursive segmentation identified the boundaries of apparent clusters better than did other methods, and this approach could identify clusters of mutations which corresponded to biologically important regions of the p53 protein.
View details for DOI 10.1002/sim.1145
View details for Web of Science ID 000176642000004
View details for PubMedID 12111894
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Point: Population stratification: A problem for case-control studies of candidate-gene associations?
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
2002; 11 (6): 505-512
View details for Web of Science ID 000176142600001
View details for PubMedID 12050090
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Androgen receptor CAG repeats and prostate cancer
AMERICAN JOURNAL OF EPIDEMIOLOGY
2002; 155 (10): 883-890
Abstract
Prostate cancer is the most common nonskin malignancy and the second leading cause of cancer deaths among men in the United States. Prostate cancer ([Mendelian Inheritance in Man 176807]) has a complex etiology; presently, age, ethnicity, and family history are the most consistently reported risk factors associated with disease. Other potential risk and protective factors have also been suggested. Androgen, acting through the androgen receptor (AR) is helpful in preserving the normal function and structure of the prostate. The AR ([Mendelian Inheritance in Man 313700]) is a structurally conserved member of the nuclear receptor superfamily of ligand-activated transcription factors. Androgens, such as testosterone, are strong tumor promoters, and work with the AR to augment the effect of any carcinogens present and stimulate cell division. The CAG repeats encode long glutamine homopolymeric amino acid chains in the amino-terminal domain of the AR gene. The authors focus on CAG repeat length because recent research suggests that men with shorter AR CAG lengths (e.g., < or =22 repeats) are at a greater risk of developing prostate cancer than are those with longer variants. Among populations studied to date, African Americans appear to have the highest frequency of short CAG repeats. Several potential interactions have also been explored, including molecular interactions, androgen deprivation therapy, and prostate-specific antigen expression. CAG repeat length can be determined with high sensitivity and specificity. Presently, there is no recommended population screening for AR CAG repeat length.
View details for DOI 10.1093/aje/155.10.883
View details for Web of Science ID 000175628800001
View details for PubMedID 11994226
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Relation between tumour necrosis factor polymorphism TNF alpha-308 and risk of asthma
EUROPEAN JOURNAL OF HUMAN GENETICS
2002; 10 (1): 82-85
Abstract
Tumour necrosis factor (TNF) alpha affects immune response and airway inflammation, which are characteristics of asthma. Genetic factors may impact TNFalpha levels, and several polymorphisms in the TNF gene cluster on chromosome 6p21 have been associated with TNFalpha production and potential increased risk of asthma. The present paper evaluates the relation between two single nucleotide polymorphisms (SNPs) in the TNF gene cluster and asthma risk. The SNPs investigated here are guanine (G) to adenosine (A) substitutions in the TNFalpha and lymphotoxin alpha (LTalpha) genes. The TNFalpha SNP is at position -308 in the promoter region (TNFalpha-308), while the LTalpha SNP is in the first intron NcoI recognition sequence (LTalpha-NcoI). (For both SNPs the G allele is denoted as 1, and the A allele 2.) We determined TNFalpha-308 and LTalpha-NcoI genotypes in 511 individuals: 236 asthma cases and 275 non-asthmatic controls. Data were analysed by logistic regression of asthma status on the genotypes and potential confounders. TNFalpha-308*2 was positively associated with asthma, and this relation was strengthened when restricting cases to individuals reporting acute asthma: the adjusted odds ratio (OR) comparing carriers of one or two TNFalpha-308*2 alleles versus none was 1.86 (95% confidence interval (CI)=1.03-3.34, P=0.04). Further restricting the subjects to those with a family history of asthma, and those of European-American ancestry strengthened the association even more: adjusted OR=3.16 (95% CI=1.04-9.66; P=0.04). LTalpha-NcoI*1 was weakly associated with asthma, and analysis of both genes suggests that only the TNFalpha-308*2 allele increases risk of asthma.
View details for DOI 10.1038/sj.ejhg.5200746
View details for Web of Science ID 000174655700012
View details for PubMedID 11896460
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Model-free linkage analysis with covariates confirms linkage of prostate cancer to chromosomes 1 and 4
AMERICAN JOURNAL OF HUMAN GENETICS
2001; 68 (5): 1197-1206
Abstract
As with many complex genetic diseases, genome scans for prostate cancer have given conflicting results, often failing to provide replication of previous findings. One factor contributing to the lack of consistency across studies is locus heterogeneity, which can weaken or even eliminate evidence for linkage that is present only in a subset of families. Currently, most analyses either fail to account for locus heterogeneity or attempt to account for it only by partitioning data sets into smaller and smaller portions. In the present study, we model locus heterogeneity among affected sib pairs with prostate cancer by including covariates in the linkage analysis that serve as surrogate measures of between-family linkage differences. The model is a modification of the Olson conditional logistic model for affected relative pairs. By including Gleason score, age at onset, male-to-male transmission, and/or number of affected first-degree family members as covariates, we detected linkage near three locations that were previously identified by linkage (1q24-25 [HPC1; LOD score 3.25, P=.00012], 1q42.2-43 [PCAP; LOD score 2.84, P=.0030], and 4q [LOD score 2.80, P=.00038]), near the androgen-receptor locus on Xq12-13 (AR; LOD score 3.06, P=.00053), and at five new locations (LOD score > 2.5). Without covariates, only a few weak-to-moderate linkage signals were found, none of which replicate findings of previous genome scans. We conclude that covariate-based linkage analysis greatly improves the likelihood that linked regions will be found by incorporation of information about heterogeneity within the sample.
View details for DOI 10.1086/320103
View details for Web of Science ID 000168171200013
View details for PubMedID 11309685
View details for PubMedCentralID PMC1226100
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Impact of preadjusting a quantitative phenotype prior to sib-pair linkage analysis when gene(x)environment interaction exists
WILEY-LISS. 2001: S837-S842
Abstract
The investigation of potential gene x environment (G x E) interactions is an important facet in the study of complex diseases. When G x E interaction exists, linkage analyses of the interacting gene must treat the environmental factor appropriately. Specifically, the common approach of regressing out an environmental factor prior to linkage analysis may be inappropriate if that factor has an interaction with the gene. This is explored here in the Genetic Analysis Workshop 12 simulated data set using the G x E interaction between major gene four (MG4) and environmental factor two (E2). The analysis shows that preadjusting the quantitative trait three (Q3) phenotype for the main effects of several environmental variables, including one (E2) that interacts with MG4, affects the results of a Haseman-Elston linkage analysis. In particular, the agreement in detecting linkage between preadjusting versus not preadjusting was only 78% and 66% using alpha levels of 0.05 and 0.10, respectively. For both approaches, incorporating an interaction term in the regression models enabled linkage to be detected where the evidence was either minimal or not present in an identical-by-descent main effects-only model. Furthermore, preadjustment for E2 did not appear to account for the major discrepancies between the approaches.
View details for DOI 10.1002/gepi.2001.21.s1.s837
View details for Web of Science ID 000171462700155
View details for PubMedID 11793789
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Introduction: Analysis of sequence data and population structure
GENETIC EPIDEMIOLOGY
2001; 21: S600-S601
View details for DOI 10.1002/gepi.2001.21.s1.s600
View details for Web of Science ID 000171462700111
View details for PubMedID 11793745
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Predicting quantitative trait levels by modeling SNP interaction
WILEY-LISS. 2001: S608-S613
Abstract
Predicting phenotype from genotype is difficult when the phenotype is affected by a gene with numerous weakly penetrant alleles that differ only in the pattern of their single nucleotide polymorphisms (SNPs). While it is probable that SNP interactions affect phenotype, to our knowledge no one has determined the most effective way of evaluating whether SNPs interact and of modeling the interaction. Therefore, to explore this issue, we investigate here three methods of modeling SNP interaction using data from Genetic Analysis Workshop 12. Since major gene 5 (MG5) has sequence information and explains 37% of the variation in quantitative trait 5 (Q5), we focus on using SNPs within MG5 to predict Q5 among individuals who married into the pedigree. As a preliminary screening step, we reduced the number of SNPs from 269 to 34 based on their association with Q5. In our first models we assumed that SNPs affected Q5 in a simple additive manner. These models explained 34% and 15% of the variation in Q5 in women and men, respectively. Our second model was a linear model, which used individual SNPs and simple interaction terms as predictors. These models explained 36% and 16% of the variation in Q5 levels for women and men, respectively. Our last model was a "hit"-based model which was motivated by the hypothesis that disequilibrium between SNPs may reflect the fact that SNPs affect phenotype by acting in concert with other SNPs within their "disequilibrium set." Thus, the number of hits within the disequilibrium sets were used as predictors. These models explained 35% and 19% of the variation in Q5 for women and men, respectively. Our results suggest that phenotype can be predicted from complex patterns of weakly penetrant SNPs using relatively simple models. We concluded that SNP interaction either was not included in the simulation model, or had only a weak impact on Q5 levels.
View details for DOI 10.1002/gepi.2001.21.s1.s608
View details for Web of Science ID 000171462700113
View details for PubMedID 11793747
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Hierarchical modeling of the relation between sequence variants and a quantitative trait: Addressing multiple comparison and population stratification issues
WILEY-LISS. 2001: S668-S673
Abstract
When analyzing the relation between genetic sequence information and disease traits, false-positive associations can arise due to multiple comparisons and population stratification. In an attempt to address these issues, we incorporate into a conventional analytic model higher-level--or "prior"--models that use additional information to improve estimates while allowing for differing population structures. We apply this hierarchical model to simulated data from the Genetic Analysis Workshop 12. We focus on the effects of common candidate gene sequence variants on quantitative risk factor 5 (Q5) levels. In particular, we compare the regression coefficients (and 95% confidence intervals) obtained from conventional (one-stage) analyses versus the corresponding results from the hierarchical analyses. When examining either the marry-ins or all subjects in the general and isolate populations, the conventional model detected numerous sites in candidate genes 1-5 and 7 that had statistically significant regression coefficients (alpha level = 0.05). In contrast, our hierarchical model primarily only detected associations for variants in candidate gene 2, which is the casual gene for Q5.
View details for DOI 10.1002/gepi.2001.21.s1.s668
View details for Web of Science ID 000171462700124
View details for PubMedID 11793759
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Replication linkage study for prostate cancer susceptibility genes
PROSTATE
2000; 45 (2): 106-114
Abstract
Since the publication of the first genome screen for prostate cancer (CaP) 5 years ago, over a dozen linkage studies have appeared. Most attention has been directed to chromosome 1, where two separate regions have been identified as harboring a prostate cancer susceptibility locus: HPC1 in the 1q24-25 interval and PCaP in the 1q42.2-43 interval. Linkage analysis of chromosome 16 has also provided evidence of harboring two loci predisposing to CaP.We report on a replication linkage study of chromosomes 1 and 16 in 45 new and 4 expanded multiplex CaP families. Multipoint Z-scores were obtained for 30 highly polymorphic short-sequence tandem repeat markers spanning chromosome 1, and 22 markers spanning chromosome 16.The replication sample gave no evidence for a CaP susceptibility locus in the 1q24-25 interval and equivocal evidence for such a locus at 1q42.2-43. With respect to chromosome 16, positive Z-scores were obtained over a contiguous interval covering the entire p arm and the proximal half of the q arm.The linkage analysis of our replication sample does not support the existence of HPC1, and the evidence for the existence of PCaP remains equivocal. Evidence of a susceptibility locus on 16p remains strong, but the evidence for a susceptibility locus on 16q is weakened.
View details for DOI 10.1002/1097-0045(20001001)45:2<106::AID-PROS4>3.0.CO;2-H
View details for Web of Science ID 000089614600004
View details for PubMedID 11027409
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Re: "Asymptotic bias and efficiency in case-control studies of candidate genes and gene-environment interactions: Basic family designs" - Reply
AMERICAN JOURNAL OF EPIDEMIOLOGY
2000; 152 (7): 690-691
View details for Web of Science ID 000089560800016
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Testing drug response in the presence of genetic information: sampling issues for clinical trials
PHARMACOGENETICS
2000; 10 (6): 503-510
Abstract
Progress towards construction of a dense map of di-allelic markers across the human genome has generated considerable enthusiasm for pharmacogenomic applications. To date, however, nearly all of the effort on single nucleotide polymorphism (SNP) projects has been focused on marker identification and screening, not on how the SNP genotype data actually can be used in clinical trials to advance medical practice. Here, we explore how different properties of SNPs impact the size, scope and design of clinical trials using a simple trial design. We evaluate the clinical trial sampling requirements under different allele frequencies, gene action, gene effect size and number of markers in a genome screen. Power and sample size calculations suggest that allele frequency and type of gene action can have a dramatic impact on trial sample sizes, in that under some conditions the required sample sizes are too large to be applicable in a costly clinical trial setting. In other situations, however, pharmacogenomic clinical trials can yield significant sampling/cost savings over traditional trials. These properties are discussed with regard to the general usage of genetic information in clinical trial settings.
View details for DOI 10.1097/00008571-200008000-00003
View details for Web of Science ID 000088986400003
View details for PubMedID 10975604
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Genomewide scan for prostate cancer-aggressiveness loci
AMERICAN JOURNAL OF HUMAN GENETICS
2000; 67 (1): 92-99
Abstract
The aggressiveness of prostate cancer (PCa) varies widely: some tumors progress to invasive, potentially life-threatening disease, whereas others stay latent for the remainder of an individual's lifetime. The mechanisms resulting in this variability are not yet understood, but they are likely to involve both genetic and environmental influences. To investigate genetic factors, we conducted a genomewide linkage analysis of 513 brothers with PCa, using the Gleason score, which reflects tumor histology, as a quantitative measure of PCa aggressiveness. To our knowledge, this is the first time that a measure of PCa aggressiveness has been directly investigated as a quantitative trait in a genomewide scan. We employed a generalized multipoint Haseman-Elston linkage-analysis approach that regresses the mean-corrected cross product between the brothers' Gleason scores on the estimated proportion of alleles shared by brothers identical by descent at each marker location. Our results suggest that candidate regions on chromosomes 5q, 7q, and 19q give evidence for linkage to PCa-aggressiveness genes. In particular, the strongest signals detected in these regions were at the following markers (with corresponding P values): for chromosome 5q31-33, between markers D5S1480 and D5S820 (P=.0002); for chromosome 7q32, between markers D7S3061 and D7S1804 (P=.0007); and, for chromosome 19q12, at D19S433 (P=.0004). This indicates that one or more of these candidate regions may contain genes that influence the progression of PCa from latent to invasive disease. Identification of such genes would be extremely valuable for elucidation of the mechanism underlying PCa progression and for determination of treatment in men in whom this disease has been diagnosed.
View details for DOI 10.1086/302960
View details for Web of Science ID 000088926900012
View details for PubMedID 10825281
View details for PubMedCentralID PMC1287106
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Identification and pine mapping of a region showing a high frequency of allelic imbalance on chromosome 16q23.2 that corresponds to a prostate cancer susceptibility locus
CANCER RESEARCH
2000; 60 (13): 3645-3649
Abstract
Linkage to a prostate cancer susceptibility locus was recently reported on chromosome 16q23. We now report a region exhibiting a high frequency of allelic imbalance (AI) corresponding to this locus in tumors from 51 men diagnosed with prostate cancer using the same linked markers. The highest frequency of AI was found at markers D16S3096 (45%) and D16S516 (53%) that map to chromosome 16q23.2. In addition, 19 of the 51 (37%) prostate tumors showed interstitial AI involving one or both of these markers. This result strongly suggests that a candidate prostate cancer tumor suppressor gene maps between markers D16S3096 and D16S516. We estimate that the distance between these markers is approximately 118 kb using a Stanford radiation hybrid panel. We observed a positive association with family history (P = 0.048) when comparing those men showing interstitial AI at markers D16S3096 and/or D16S516 with those without any imbalance at these two markers. Taken together, these data suggest that we have precisely localized a region of chromosome 16q23.2 that may harbor a prostate cancer tumor suppressor gene implicated in the development of non-familial and possibly familial forms of prostate cancer.
View details for Web of Science ID 000088162400051
View details for PubMedID 10910080
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Correlations of individual plasma carotenoid concentrations in free-living older adults
NUTRITION RESEARCH
2000; 20 (7): 955-965
View details for DOI 10.1016/S0271-5317(00)00186-X
View details for Web of Science ID 000087722300005
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CYP3A activity in African American and European American men: Population differences and functional effect of the CYP3A4*1B 5 '-promoter region polymorphism
CLINICAL PHARMACOLOGY & THERAPEUTICS
2000; 68 (1): 82-+
Abstract
Cytochrome P4503A (CYP3A) activity exhibits considerable interindividual variability. Possible differences in CYP3A activity were investigated in European American and African American men with the use of midazolam as an in vivo probe.Midazolam was simultaneously administered intravenously (1 mg, [15N3]-labeled) and orally (2 mg, unlabeled in capsule form) to 15 young healthy European American men and a similar group of men of African American descent. Plasma concentration-time curves were measured. The subjects were subsequently genotyped with respect to the CYP3A4*B1 polymorphism (A-290G) in the 5'-promoter (nifedipine-specific element) region.The oral bioavailability of midazolam was about equally determined by intestinal and hepatic extraction with CYP3A activity at the former site exhibiting greater variability. Oral bioavailability was related to intestinal metabolism (r = 0.98), whereas hepatic CYP3A activity contributed little to the interindividual variability (r = 0.03). A lower systemic clearance (265+/-54 versus 310+/-56 mL/min; P = .04), but not oral clearance, was observed in African Americans. With one exception, the African Americans possessed a variant CYP3A4*1B allele (4 heterozygotes A/G and 10 homozygote G/G), whereas all of the European Americans were wild-type homozygotes (A/A). Hepatic CYP3A activity and the systemic clearance of midazolam were about 30% lower in G/G homozygotes than in A/A homozygotes (252+/-53 versus 310+/-54 mL/min; P = .02), and a gene-dose effect was present (P = .01). There was no genotype/phenotype relationship with respect to the oral clearance of midazolam.Comparison of CYP3A activity between populations is complicated by frequency distribution differences in the regulatory CYP3A4*1B polymorphism and lower hepatic CYP3A activity associated with the variant allele. However, this reduction is modest; therefore no major and clinically important difference in CYP3A activity is present between Americans of African or European descent.
View details for DOI 10.1067/mcp.2000.108506
View details for Web of Science ID 000088387100012
View details for PubMedID 10945319
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A genome screen of multiplex sibships with prostate cancer
AMERICAN JOURNAL OF HUMAN GENETICS
2000; 66 (3): 933-944
Abstract
Analysis of a genome screen of 504 brothers with prostate cancer (CaP) who were from 230 multiplex sibships identified five regions with nominally positive linkage signals, on chromosomes 2q, 12p, 15q, 16p, and 16q. The strongest signal in these data is found on chromosome 16q, between markers D16S515 and D16S3040, a region suspected to contain a tumor-suppressor gene. On the basis of findings from previous genome screens of families with CaP, three preplanned subanalyses were carried out, in the hope of increasing the subgroup homogeneity. Subgroups were formed by dividing the sibships into a group with a positive family history (FH+) that met criteria for "hereditary" CaP (n=111) versus those which did not meet the criteria (n=119) and by dividing the families into those with a mean onset age below the median (n=115) versus those with a mean onset age above the median (n=115). A separate subanalysis was carried out for families with a history of breast cancer (CaB+ [n=53]). Analyses of these subgroups revealed a number of potentially important differences in regions that were nonsignificant when all the families were analyzed together. In particular, the subgroup without a positive family history (FH-) had a signal in a region that is proximal to the putative site of the HPC1 locus on chromosome 1, whereas the late-age-at-onset group had a signal on 4q. The CaB+ subgroup revealed a strong linkage signal at 1p35.1.
View details for DOI 10.1086/302818
View details for Web of Science ID 000088373200016
View details for PubMedID 10712208
View details for PubMedCentralID PMC1288174
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On the relative sample size required for multiple comparisons
STATISTICS IN MEDICINE
2000; 19 (3): 369-372
Abstract
Multiple comparisons are commonly made in epidemiologic and genetic research. How to appropriately adjust for multiple comparisons remains a controversial issue. This note demonstrates, however, that large increases in the number of comparisons has a limited effect on the sample size required to maintain an experimentwise alpha-level. In particular, the relative sample size required increases only linearly with the logarithm of the number of comparisons made.
View details for DOI 10.1002/(SICI)1097-0258(20000215)19:3<369::AID-SIM335>3.0.CO;2-N
View details for Web of Science ID 000084997000007
View details for PubMedID 10649302
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Clinical trials in the genomic era: Effects of protective genotypes on sample size and duration of trial
CONTROLLED CLINICAL TRIALS
2000; 21 (1): 7-20
Abstract
It is well known that individuals can vary widely in their disease susceptibilities. One potential source of this variation is the genetic makeup of individuals, which can confer either protection or susceptibility to disease. Here we examine the effects of protective genotypes on the sample sizes and time required to detect differences between clinical trial arms. We show that including individuals with protective genotypes in a clinical trial can increase required sample sizes and trial duration. One can deal with this issue by pregenotyping subjects and selectively enrolling them based on their genotype. Thus we also calculate the number of individuals that must be recruited and pregenotyped to fulfill sample size requirements. The benefits of genotypically screening study subjects will depend on numerous factors, including ease of patient recruitment, cost of genotyping, long-term costs of study (or long-term cost per subject), and the strength of the protective effect. We present several examples that show the potential value of incorporating information about protective genotypes into a clinical trial.
View details for DOI 10.1016/S0197-2456(99)00039-2
View details for Web of Science ID 000084911500002
View details for PubMedID 10660000
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Linkage disequilibrium and allele-frequency distributions for 114 single-nucleotide polymorphisms in five populations
AMERICAN JOURNAL OF HUMAN GENETICS
2000; 66 (1): 216-234
Abstract
Single-nucleotide polymorphisms (SNPs) may be extremely important for deciphering the impact of genetic variation on complex human diseases. The ultimate value of SNPs for linkage and association mapping studies depends in part on the distribution of SNP allele frequencies and intermarker linkage disequilibrium (LD) across populations. Limited information is available about these distributions on a genomewide scale, particularly for LD. Using 114 SNPs from 33 genes, we compared these distributions in five American populations (727 individuals) of African, European, Chinese, Hispanic, and Japanese descent. The allele frequencies were highly correlated across populations but differed by >20% for at least one pair of populations in 35% of SNPs. The correlation in LD was high for some pairs of populations but not for others (e.g., Chinese American or Japanese American vs. any other population). Regardless of population, average minor-allele frequencies were significantly higher for SNPs in noncoding regions (20%-25%) than for SNPs in coding regions (12%-16%). Interestingly, we found that intermarker LD may be strongest with pairs of SNPs in which both markers are nonconservative substitutions, compared to pairs of SNPs where at least one marker is a conservative substitution. These results suggest that population differences and marker location within the gene may be important factors in the selection of SNPs for use in the study of complex disease with linkage or association mapping methods.
View details for DOI 10.1086/302727
View details for Web of Science ID 000085033600024
View details for PubMedID 10631153
View details for PubMedCentralID PMC1288328
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Tutorial in biostatistics genetic mapping of complex traits
STATISTICS IN MEDICINE
1999; 18 (21): 2961-2981
Abstract
Statistical genetic mapping methods are powerful tools for finding genes that contribute to complex human traits. Mapping methods combine knowledge of the biological mechanisms of inheritance and the randomness inherent in those mechanisms to locate, with increasing precision, trait genes on the human genome. We provide an overview of the two major classes of mapping methods, genetic linkage analysis and linkage disequilibrium analysis, and related concepts of genetic inheritance.
View details for DOI 10.1002/(SICI)1097-0258(19991115)18:21<2961::AID-SIM206>3.3.CO;2-L
View details for Web of Science ID 000083386700010
View details for PubMedID 10523753
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Association between a CYP3A4 genetic variant and clinical presentation in African-American prostate cancer patients
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
1999; 8 (10): 901-905
Abstract
Prostate cancer incidence, clinical presentation, and mortality rates vary among different ethnic groups. A genetic variant of CYP3A4, a gene involved in the oxidative deactivation of testosterone, has been associated recently with prostate cancer development in Caucasians. To further investigate this variant, we evaluated its genotype frequencies in different ethnic groups and its association with clinical presentation of prostate cancer in African Americans. CYP3A4 genotypes were assayed in healthy male Caucasian (n = 117), Hispanic (n = 121), African-American (n = 116), Chinese (n = 46), and Japanese (n = 34) volunteers using the TaqMan assay. The association between CYP3A4 genotype and prostate cancer presentation was determined in 174 affected African-American men. Genotype frequency of the CYP3A4 variant differed substantially across ethnic groups, with African Americans much more likely to carry one or two copies than any other group (two-sided P < 0.0001). Among African Americans, 46% (80 of 174) of men with prostate cancer were homozygous for the CYP3A4 variant, whereas only 28% (32 of 116) of African-American healthy volunteers were homozygous (two-sided P < 0.005). A consistent positive association was observed between being homozygous for the CYP3A4 variant in African-American prostate cancer patients and clinical characteristics. Men homozygous for the CYP3A4 variant were more likely to present with higher grade and stage of prostate cancer in a recessive model [odds ratio (OR), 1.7; 95% confidence interval (CI), 0.9-3.4]. This association was even stronger for men who were >65 years of age at diagnosis (n = 103; OR, 2.4; 95% CI, 1.1-5.4). In summary, the CYP3A4 genotype frequency in different ethnic groups broadly followed trends in prostate cancer incidence, presentation, and mortality in the United States. African-American prostate cancer patients had a higher frequency of being homozygous for the CYP3A4 variant than healthy African-American volunteers who were matched solely based on ethnicity. Among the patients, those who were homozygous for the CYP3A4 variant were more likely to present with clinically more advanced prostate cancer.
View details for Web of Science ID 000083352400009
View details for PubMedID 10548319
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Asymptotic bias and efficiency in case-control studies of candidate genes and gene-environment interactions: Basic family designs
AMERICAN JOURNAL OF EPIDEMIOLOGY
1999; 149 (8): 693-705
Abstract
Case-control designs that use population controls are compared with those that use controls selected from their relatives (i.e., siblings, cousins, or "pseudosibs" based on parental alleles) for estimating the effect of candidate genes and gene-environment interactions. The authors first evaluate the asymptotic bias in relative risk estimates resulting from using population controls when there is confounding due to population stratification. Using siblings or pseudosibs as controls completely addresses this issue, whereas cousins provide only partial protection from population stratification. Next, they show that the conventional conditional likelihood for matched case-control studies can give asymptotically biased effect estimates when applied to the pseudosib approach; the asymptotic bias is toward the null and disappears with disease rarity. They show how to reparameterize the pseudosib likelihood so this approach gives consistent effect estimates. They then show that the designs using population or pseudosib controls are generally the most efficient for estimating the main effect of a candidate gene, followed in efficiency by the design using cousins. Finally, they show that the design using sibling controls can be quite efficient when studying gene-environment interactions. In addition to asymptotic bias and efficiency issues, family-based designs might benefit from a higher motivation to participate among cases' relatives, but these designs have the disadvantage that many potential cases will be excluded from study by having no available controls.
View details for Web of Science ID 000079671500002
View details for PubMedID 10206618
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Likelihood-based approach to estimating twin concordance for dichotomous traits
GENETIC EPIDEMIOLOGY
1999; 16 (3): 290-304
Abstract
Genetic epidemiologists are well aware that the casewise and pairwise twin concordances are two different measures. In determining appropriate estimators for each of these measures, the method of ascertainment must be considered. Here, we derive expressions for the concordance estimators and their asymptotic variances appropriate to different twin ascertainment schemes using a likelihood framework, and apply these formulas to existing data. We emphasize the distinction between concordance measures (i.e., the parameters of interest) and the concordance estimators based on the number of pairs observed. Under random or complete ascertainment the casewise estimator is asymptotically unbiased for the casewise concordance, and the pairwise estimator is asymptotically unbiased for the pairwise concordance. Under incomplete ascertainment, the casewise estimator is biased for the casewise concordance, the pairwise estimator is biased for the pairwise concordance, but the probandwise estimator is asymptotically unbiased for the casewise concordance. One can extend the likelihood equations presented here to allow the concordance parameter of interest to depend on zygosity and, if measured, other factors such as cohabitation status and similarity for genetic markers, while concurrently allowing the disease prevalence to depend on measured covariates.
View details for DOI 10.1002/(SICI)1098-2272(1999)16:3<290::AID-GEPI5>3.0.CO;2-8
View details for Web of Science ID 000078966600005
View details for PubMedID 10096691
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Model-based and model-free multipoint genome-wide linkage analysis of alcoholism
WILEY-LISS. 1999: S175-S180
Abstract
We analyzed a subset of the Collaborative Study on the Genetics of Alcoholism (COGA) data set as provided by the 11th Genetic Analysis Workshop (GAW11). Linkage analyses were performed using each of the diagnostic criteria for alcoholism included in the data: the COGA criteria (DSM-III-R plus the Feighner criteria) and the narrower World Health Organization diagnosis ICD-10 criteria. Formal segregation analysis using these data was not attempted because only a subset of all the originally ascertained families was made available. Nevertheless, an attempt was made to estimate the best one-locus two-allele genetic model for these data. Model-based multipoint linkage analysis was performed using the results of our trait model fitting, and model-free multipoint linkage analysis was performed with an improved version of the Haseman and Elston linkage method for sib pairs.
View details for Web of Science ID 000083945800028
View details for PubMedID 10597432
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Glutathione transferase null genotype, broccoli, and lower prevalence of colorectal adenomas
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
1998; 7 (8): 647-652
Abstract
Cruciferous vegetables, especially broccoli, may prevent cancer through anticarcinogenic compounds. For example, broccoli contains isothiocyanates that induce carcinogen-detoxifying enzymes. Glutathione transferase enzymes conjugate isothiocyanates, leading to excretion. We hypothesized that broccoli consumption in combination with the glutathione transferase M1 (GSTM1) null genotype would be associated with a lower prevalence of colorectal adenomas because of higher isothiocyanate levels. We used a case-control study of mainly asymptomatic subjects aged 50-74 years who underwent a screening sigmoidoscopy at either of two Southern California Kaiser Permanente Medical Centers during 1991-1993. Cases (n = 459) had a first-time diagnosis of histologically confirmed adenomas detected by flexible sigmoidoscopy. Controls (n = 507) had no polyp detected. Subjects had a 45-min in-person interview for information on various risk factors and basic demographic data and completed a 126-item, semiquantitative food frequency questionnaire. Blood samples were used for GSTM1 genotyping. Subjects with the highest quartile of broccoli intake (an average of 3.7 servings per week) had an odds ratio of 0.47 (95% confidence interval, 0.30-0.73) for colorectal adenomas, compared with subjects who reportedly never ate broccoli. When stratified by GSTM1 genotype, a protective effect of broccoli was observed only among subjects with the GSTM1 null genotype (P for trend, 0.001; P for interaction, 0.01). The observed broccoli-GSTM1 interaction is compatible with an isothiocyanate mechanism.
View details for Web of Science ID 000075283700002
View details for PubMedID 9718215
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Familial prostate cancer: A different disease?
JOURNAL OF UROLOGY
1997; 158 (6): 2197-2201
Abstract
We analyzed the outcome after radical prostatectomy of patients with familial prostate cancer versus patients with sporadic prostate cancer.The study included 720 patients with prostate carcinoma who were treated with prostatectomy between 1987 and 1996. Patients were excluded from the study if they had received adjuvant or neoadjuvant treatment, or had no available pretreatment prostatic specific antigen (PSA) level, no available biopsy Gleason score, incomplete pathological information or no available followup PSA levels. The analysis was performed on 529 cases. Patients were considered to have a positive family history for prostate cancer when the index patient confirmed the diagnosis of prostate cancer in a first degree relative (brother or father). The outcomes of interest were biochemical relapse-free survival, local failure and distant metastases. Proportional hazards were used to analyze the effect of family history and confounding variables (that is age, stage, biopsy Gleason score, initial PSA levels, surgical specimen Gleason score, extracapsular extension, lymph node metastasis, seminal vesicle invasion and surgical margin involvement) on treatment outcome.Median followup was 30 months. Of all cases 12% had a positive family history. Younger age was the only factor associated with positive family history, with 18% of patients younger than 65 years having a positive family history versus 6% of older patients (chi-square p <0.001). The 5-year biochemical relapse-free survival rate for the entire group was 64%. The 5-year biochemical relapse-free survival rates for patients with negative family history versus positive history were 66% and 46%, respectively (p = 0.001). A multivariate time-to-failure analysis using the proportional hazards model was performed based on family history, age (less than 65 versus 65 to 69 versus 70 or greater, initial PSA (10 or less versus greater than 10), biopsy Gleason score (6 or less versus 7 or greater), clinical T stage (T1-T2A versus T2B-C), prostatectomy specimen Gleason score (6 or less versus 7 or greater), extracapsular extension, seminal vesicle involvement, surgical margin involvement and lymph node involvement. After adjusting for the potential confounding factors, positive family history remained strongly associated with biochemical failure. The clinical failure rate for the entire group was 14%. The 5-year local failure rate was 7%, with positive surgical margins being the only independent predictor of local failure. The 5-year distant metastasis rate was 8%, with family history and initial PSA levels being independent predictors of distant relapse.Our study suggests that patients with a familial prostate cancer have a higher likelihood of biochemical failure after radical prostatectomy than patients with sporadic cancer. This effect is independent of pretreatment or pathological factors. Our results suggest that the higher failure rates associated with familial prostate cancer are mainly secondary to higher distant relapse rates, and that familial prostate cancer may be more biologically aggressive than sporadic cancers.
View details for DOI 10.1016/S0022-5347(01)68194-1
View details for Web of Science ID A1997YE61700046
View details for PubMedID 9366343
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A sigmoidoscopy-based case-control study of polyps: Macronutrients, fiber and meat consumption
INTERNATIONAL JOURNAL OF CANCER
1997; 73 (4): 497-502
Abstract
We conducted a large, sigmoidoscopy-based case-control study to examine the relation of intake of macronutrients, meat, and fiber to occurrence of adenomas of the large bowel. Cases were subjects diagnosed for the first time with one or more histologically confirmed adenomas. Controls had no polyps of any type at sigmoidoscopy, had no history of polyps, and were individually matched to cases by gender, age, date of sigmoidoscopy, and Kaiser Center. The response rate was 84% for cases and 82% for controls. Complete dietary data for 488 matched pairs were available. All odds ratios are from matched analyses adjusted for energy. We observed positive associations with risk of adenomas for calories, animal fat, saturated fat, red meat, and the ratio of red meat to poultry and fish. Protective effects were observed for vegetable protein, carbohydrates, and dietary fiber. The fiber effects diminished after adjusting for fruits and vegetables. Results after mutually adjusting for the effects of saturated fat, fiber and the ratio of red meat to chicken and fish suggest that each of these variables has an effect on risk of adenomas that is independent of the other 2 exposures.
View details for Web of Science ID A1997YG99200007
View details for PubMedID 9389562
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Family history of prostate cancer in patients with localized prostate cancer: An independent predictor of treatment outcome
JOURNAL OF CLINICAL ONCOLOGY
1997; 15 (4): 1478-1480
Abstract
To determine if familial prostate cancer patients have a less favorable prognosis than patients with sporadic prostate cancer after treatment for localized disease with either radiotherapy (RT) or radical prostatectomy (RP).One thousand thirty-eight patients treated with either RT (n = 583) or RP (n = 455) were included in this analysis. These patients were noted as having a positive family history if they confirmed the diagnosis of prostate cancer in a first-degree relative. The outcome of interest was biochemical relapse-free survival (bRFS). We used proportional hazards to analyze the effect of the presence of family history and other potential confounding variables (ie, age, treatment modality, stage, biopsy Gleason sum [GS], and initial prostate-specific antigen [iPSA] levels) on treatment outcome.Eleven percent of all patients had a positive family history. The 5-year bRFS rates for patients with negative and positive family histories were 52% and 29%, respectively (P < .001). The potential confounders with bRFS rates were iPSA levels, biopsy GS, and clinical tumor stage; treatment modality and age did not appear to be associated with outcome. After adjusting for potential confounders, family history of prostate cancer remained strongly associated with biochemical failure.This is the first study to demonstrate that the presence of a family history of prostate cancer correlates with treatment outcome in a large unselected series of patients. Our findings suggest that familial prostate cancer may have a more aggressive course than nonfamilial prostate cancer, and that clinical and/or pathologic parameters may not adequately predict this course.
View details for DOI 10.1200/JCO.1997.15.4.1478
View details for Web of Science ID A1997WX65100026
View details for PubMedID 9193343
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A nested approach to evaluating dose-response and trend
ANNALS OF EPIDEMIOLOGY
1997; 7 (3): 188-193
Abstract
Conventional dose-response and trend analysis fits either a linear or categorical logistic model and tests the resulting coefficients. These analyses, however, are based on implausible assumptions.We present an alternative approach that uses likelihood ratio tests to compare nested regression models and determine when a model is rich enough to capture the data trends.For illustration, we apply this approach to data on diet and colorectal polyps.Comparison of linear and quadratic spline logistic models indicates that the conventional approach of using only a linear logistic model would not appropriately describe the association between intake of fruits and vegetables and colorectal polyps in our data. Graphical checking further supports this conclusion.
View details for DOI 10.1016/S1047-2797(96)00159-7
View details for Web of Science ID A1997WX57800005
View details for PubMedID 9141641
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Meat preparation and colorectal adenomas in a large sigmoidoscopy-based case-control study in California (United States)
CANCER CAUSES & CONTROL
1997; 8 (2): 175-183
Abstract
The often observed association between red meat and colorectal cancer could be due in part to mutagens, such as heterocyclic amines (HCA), that are present in cooked meat. HCAs are highly mutagenic and cause intestinal tumors in animals. The hypothesis that HCAs are also carcinogenic to humans remains to be substantiated in epidemiologic studies. We determined the associations of meat preparation and frequency of intake (proxy variables for HCA exposure, since HCA concentration depends on the type of meat and the way it is cooked) with the prevalence of distal colorectal adenomas in a sigmoidoscopy-based case-control study of 488 matched pairs of subjects from two California (United States) Kaiser Permanente Medical Centers. A more than twofold difference in adenoma prevalence between subjects at extreme ends of estimated HCA intake was observed. For subjects who ate red meat more than once per week, fried it more than 10 percent of the time, and ate it with a darkly browned surface, compared with subjects who ate red meat one time or less per week, fried it 10 or less percent of the time, and ate it with a lightly browned surface, the odds ratio was 2.2 (95 percent confidence interval = 1.1-4.3). Adenoma prevalence also increased with frequency of frying red meat (P trend = 0.004). These results are consistent with a carcinogenic effect of HCA.
View details for Web of Science ID A1997WU35100008
View details for PubMedID 9134241
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Diet and premenopausal bilateral breast cancer: A case-control study
BREAST CANCER RESEARCH AND TREATMENT
1997; 42 (3): 243-251
Abstract
We investigated associations between diet and premenopausal bilateral breast cancer in a familial matched case-control study. We studied 140 cases from population-based registries in Los Angeles County (California) and Connecticut, and from the major hospitals in the southern parts of the Province of Quebec. Unaffected sisters of the cases served as matched controls (222 total). Dietary intake were assessed with a food frequency questionnaire. Total fat, monounsaturated fat, polyunsaturated fat, oleic acid, and linoleic acid intake was inversely associated with premenopausal bilateral breast cancer risk. Consumption of carbohydrates (and sweetened beverages) was associated with an increased risk. We observed no associations for dietary fiber, antioxidants, or major food groupings, but we did observe inverse associations for intake of low fat dairy products and tofu. These findings suggest that monounsaturated and polyunsaturated fats, as well as soy foods, might reduce the risk of premenopausal bilateral breast cancer.
View details for Web of Science ID A1997WM10800006
View details for PubMedID 9065608
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Modeling age of onset and residual familial correlations for the linkage analysis of bipolar disorder
WILEY-LISS. 1997: 675-680
Abstract
We applied regressive modeling to the data described by Stine et al. [1995] and further explored the possible linkage of bipolar disorder to marker D18S41 on chromosome 18. We performed analyses to determine age-dependent penetrance functions that best fit the data and that allow for residual familial correlations. Specifically, we introduce here a simple method to allow for a sibling correlations. that is not due to segregation at the linked locus, and then extend the results of Stine et al. [1995] by using the best fitting "regressive" model of this kind as input into a lod score linkage analysis. Although a formal segregation analysis was not attempted, a surprising finding was that, except for doubtful linkage to D18S41, there is little evidence for genetic transmission of bipolar disorder in these families.
View details for DOI 10.1002/(SICI)1098-2272(1997)14:6<675::AID-GEPI21>3.3.CO;2-V
View details for Web of Science ID 000071121800022
View details for PubMedID 9433562
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Relation of vegetable, fruit, and grain consumption to colorectal adenomatous polyps
AMERICAN JOURNAL OF EPIDEMIOLOGY
1996; 144 (11): 1015-1025
Abstract
Previous studies suggest that colorectal cancer risk decreases with higher intake of vegetables, fruits, and grains. Few studies, however, have examined these factors in relation to occurrence of colorectal polyps. The authors used case-control data from 488 matched pairs to evaluate associations of vegetables, fruits, and grains with polyps. Subjects were southern Californians aged 50-74 years who had a sigmoidoscopy in 1991-1993. Diet in the year before sigmoidoscopy was measured with a food frequency questionnaire. Frequent consumption of vegetables, fruits, and grains was associated with decreased polyp prevalence. Specifically, the adjusted odds ratio comparing the highest with the lowest quintile of intake for vegetables was 0.47 (95% confidence interval (CI) 0.29-0.76), for fruits was 0.65 (95% CI 0.40-1.05), and for grains was 0.55 (95% CI 0.33-0.91). The authors also found inverse associations for high carotenoid vegetables, cruciferae, high vitamin C fruits, garlic, and tofu (or soybeans). After further adjusting for potentially anticarcinogenic constituents of these foods, high carotenoid vegetables, cruciferous vegetables, garlic, and tofu (or soybeans) remained inversely associated with polyps. These findings support the hypothesis that high intake of vegetables, fruits, or grains decreases the risk of polyps and suggest that any protective effects might reflect unmeasured constituents in these foods.
View details for Web of Science ID A1996VV53500002
View details for PubMedID 8942431
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Agreement in alcohol consumption levels as measured by two different questionnaires
JOURNAL OF STUDIES ON ALCOHOL
1996; 57 (4): 406-409
Abstract
We evaluated the agreement in reported alcohol consumption between a standard food frequency questionnaire (FFQ) and a risk factor questionnaire (RFQ) developed for a genetic epidemiologic study of breast cancer.The FFQ measured intake of alcoholic beverages by asking which of nine levels were consumed during a single time period. In contrast, the RFQ used open-ended questions to measure intake of alcoholic beverages during numerous time periods. Subjects (N = 765) completed both questionnaires at home.Mean daily alcohol consumption levels were consistently higher in the FFQ than in the RFQ; for example, the mean alcohol consumption for all subjects was 7.0 g/day in the FFQ versus 5.3 g/day in the RFQ. Moreover, the RFQ overestimated the number of nondrinkers relative to the FFQ. Nonetheless, the Spearman correlation coefficients between daily alcohol consumption levels as measured by the two questionnaires were relatively high: total alcohol, r = 0.72; beer, r = 0.69; wine, r = 0.69; and distilled spirits, r = 0.54.The reasonable agreement between these questionnaires supports the validity of historical alcohol consumption levels measured by the RFQ.
View details for Web of Science ID A1996UR80200011
View details for PubMedID 8776682
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Simulation study of hierarchical regression
STATISTICS IN MEDICINE
1996; 15 (11): 1161-1170
Abstract
Hierarchical regression - which attempts to improve standard regression estimates by adding a second-stage 'prior' regression to an ordinary model - provides a practical approach to evaluating multiple exposures. We present here a simulation study of logistic regression in which we compare hierarchical regression fitted by a two-stage procedure to ordinary maximum likelihood. The simulations were based on case-control data on diet and breast cancer, where the hierarchical model uses a second-stage regression to pull conventional dietary-item estimates toward each other when they have similar levels of food constituents. Our results indicate that hierarchical modelling of continuous covariates offers worthwhile improvement over ordinary maximum-likelihood, provided one does not underspecify the second-stage standard deviations.
View details for DOI 10.1002/(SICI)1097-0258(19960615)15:11<1161::AID-SIM221>3.0.CO;2-7
View details for Web of Science ID A1996UR76800006
View details for PubMedID 8804145
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Association within twin pairs for a dichotomous trait
GENETIC EPIDEMIOLOGY
1996; 13 (5): 489-499
Abstract
We propose an odds-ratio measure of twin association for a dichotomous trait. This odds ratio can be estimated without arbitrarily specifying an index twin and without estimating additional nuisance parameters. Tests of association and confidence intervals may be computed easily, in contrast to those proposed previously [Donner et al. (1995) Genet Epidemiol 12:267-277] for a correlation measure of association. For testing homogeneity of association in two samples of twins, monozygotic and dizygotic, we propose a large-sample test and an exact test, both based on the odds-ratio parameterization. Large-sample tests of homogeneity are slightly anticonservative when some cell counts are small, and the exact test may be preferred in these situations. We also propose a long-linear parameterization useful for modeling more complex data sets.
View details for DOI 10.1002/(SICI)1098-2272(1996)13:5<489::AID-GEPI5>3.0.CO;2-Y
View details for Web of Science ID A1996VN71900005
View details for PubMedID 8905395