Ryan Whaley

All Publications

• Advancing Clinical Pharmacogenomics Worldwide Through the Clinical Pharmacogenetics Implementation Consortium (CPIC). Clinical pharmacology and therapeutics Caudle, K. E., Whirl-Carrillo, M., Relling, M. V., Hoffman, J. M., Donnelly, R. S., Haidar, C. E., Bourque, M. S., Frear, S., Gong, L., Sangkuhl, K., Whaley, R., Klein, T. E. 2025

  Abstract

  The Clinical Pharmacogenetics Implementation Consortium (CPIC) has advanced clinical pharmacogenomics since 2009 by developing freely available, evidence-based gene/drug guidelines. Covering 34 genes and 164 drugs, CPIC guidelines have become the global standard for translating pharmacogenomic test results into actionable prescribing decisions. This paper summarizes data highlighting CPIC's pivotal role in accelerating the global adoption of pharmacogenomics and establishing itself as the leading resource for clinical implementation. To assess CPIC's growth and impact, we analyzed member demographics, guideline characteristics, author composition, bibliometric data, database/API usage, and real-world implementation using internal tracking, external databases (Scopus, iCite), website analytics, PubMed review (2019-2024), and CPIC member surveys (2012, 2024). CPIC has 28 active guidelines with international authorship and widespread adoption, garnering over 10,000 citations and 1.4 million views. Robust implementation is evident, with 85% of PubMed-indexed pharmacogenomic implementation studies referencing CPIC guidelines. Additionally, 128 healthcare institutions and 40 commercial laboratories report using CPIC content. The CPIC API supports over 80,000 monthly queries, increasingly integrated into EHRs, including Epic's foundational genomics module. Member surveys show a shift from scientific evidence concerns to practical barriers like clinician education, reimbursement, and EHR integration. CPIC has evolved from a guideline development initiative into a global leader in pharmacogenomics implementation, fostering collaboration, standardization, and sustainable integration into diverse healthcare settings.

  View details for DOI 10.1002/cpt.70005

  View details for PubMedID 40678821

• Towards an integrated resource for pharmacogenomics (PGx): Survey findings from the genomic medicine communities. Genetics in medicine : official journal of the American College of Medical Genetics Klein, C. J., Gong, L., Caudle, K. E., Naik, H., Empey, P. E., Hoffman, J. M., Scherer, S., Iwuchukwu, O. F., Gregornik, D., Monte, A. A., Swen, J. J., Scott, S. A., Whirl-Carrillo, M., Klein, T. E. 2025: 101529

  Abstract

  Pharmacogenomics (PGx) is a critical component of precision healthcare that aims to improve drug efficacy and reduce adverse events. Terminologies and standards have not always aligned between PGx and broader genomic medicine communities, which is a barrier to PGx implementation. An updated assessment of community barriers, needs, and perspectives is critical to enable more standardized terminologies and interpretation frameworks.The Clinical Genome Resource's (ClinGen) PGx Interpretation Committee (PGxIC, formerly referred to as the PGx Working Group, PGxWG) conducted two surveys targeting the PGx and genomic medicine communities (n=508) to evaluate perspectives on PGx clinical validity and actionability frameworks, as well as other barriers to PGx implementation. Surveys were tailored toward self-reported familiarity with PGx. Data primarily consisted of free text, which was analyzed using qualitative content analysis methods.Survey responses indicated conflation of terminology across disciplines including confusion around differing definitions of terms in PGx and non-PGx contexts. Data also indicated broad support for leveraging existing PGx guidelines and framework structures alongside the standardization of approaches and centralization of resources.These novel survey results demonstrate broad consensus on the importance of integrating PGx into clinical practice, including support for development of gene-drug response clinical validity and actionability frameworks aligned with ClinGen frameworks for gene-disease relationships.

  View details for DOI 10.1016/j.gim.2025.101529

  View details for PubMedID 40662343

• CLINPGX: A COMPREHENSIVE PHARMACOGENOMICS RE-SOURCE WITH TOOLS FOR ACCESSING CLINICAL GUIDANCE BY GENOTYPE Whirl-Carrillo, M., Sangkuhl, K., Gong, L., Whaley, R., Woon, M., Thorn, C., Keseler, I., Klein, C., Tsermpini, E., Caudle, K., Ritchie, M., Klein, T. WILEY. 2025

  View details for Web of Science ID 001639088700042

• From sample to star alleles: a long-read pharmacogenomics pipeline powered by Twist target enrichment and PacBio HiFi sequencing Holt, S., Harting, J., Han, T., Arbiza, L., Kingan, S., Souppe, A., Zhang, S., Baybayan, P., Lambert, C., Ferrao, H., Li, B., Sangkuhl, K., Woon, M., Whaley, R., Whirl-Carrillo, M., Yang, Y., Klein, T., Scott, S., Gonzaludo, N. SPRINGERNATURE. 2024: 701-702

  View details for Web of Science ID 001147414903359

• Highly Scalable Pharmacogenomic Panel Testing with Hybrid Capture and Long-Read Sequencing Gonzaludo, N., Kingan, S., Harting, J., Baybayan, P., Han, T., Arbiza, L., Li, B., Sangkuhl, K., Woon, M., Whaley, R., Whirl-Carrillo, M., Yang, Y., Klein, T. E., Hammond, N., Scott, S. A. LIPPINCOTT WILLIAMS & WILKINS. 2023: 183

  View details for Web of Science ID 001084789600005

• Frequencies of pharmacogenomic alleles across biogeographic groups in a large-scale biobank. American journal of human genetics Li, B., Sangkuhl, K., Whaley, R., Woon, M., Keat, K., Whirl-Carrillo, M., Ritchie, M. D., Klein, T. E. 2023

  Abstract

  Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate information on PGx allele frequencies improves the implementation of PGx. Nonetheless, curating such information from published allele data is time and resource intensive. The limited number of allelic variants in most studies leads to an underestimation of certain alleles. We applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200K UK Biobank genetic dataset (N = 200,044). Based on PharmCAT results, we estimated PGx frequencies (alleles, diplotypes, phenotypes, and activity scores) for 17 pharmacogenes in five biogeographic groups: European, Central/South Asian, East Asian, Afro-Caribbean, and Sub-Saharan African. PGx frequencies were distinct for each biogeographic group. Even biogeographic groups with similar proportions of phenotypes were driven by different sets of dominant PGx alleles. PharmCAT also identified "no-function" alleles that were rare or seldom tested in certain groups by previous studies, e.g., SLCO1B1∗31 in the Afro-Caribbean (3.0%) and Sub-Saharan African (3.9%) groups. Estimated PGx frequencies are disseminated via the PharmGKB (The Pharmacogenomics Knowledgebase: www.pharmgkb.org). We demonstrate that genetic biobanks such as the UK Biobank are a robust resource for estimating PGx frequencies. Improving our understanding of PGx allele and phenotype frequencies provides guidance for future PGx studies and clinical genetic test panel design, and better serves individuals from wider biogeographic backgrounds.

  View details for DOI 10.1016/j.ajhg.2023.09.001

  View details for PubMedID 37757824

• How to Run the Pharmacogenomics Clinical Annotation Tool (PharmCAT). Clinical pharmacology and therapeutics Li, B., Sangkuhl, K., Keat, K., Whaley, R. M., Woon, M., Verma, S., Dudek, S., Tuteja, S., Verma, A., Whirl-Carrillo, M., Ritchie, M. D., Klein, T. E. 2022

  Abstract

  Pharmacogenomics (PGx) investigates the genetic influence on drug response and is an integral part of precision medicine. While PGx testing is becoming more common in clinical practice and may be reimbursed by Medicare/Medicaid and commercial insurance, interpreting PGx testing results for clinical decision support is still a challenge. The Pharmacogenomics Clinical Annotation Tool (PharmCAT) has been designed to tackle the need for transparent, automatic interpretations of patient genetic data. PharmCAT incorporates a patient's genotypes, annotates PGx information (allele, genotype, and phenotype), and generates a report with PGx guideline recommendations from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and/or the Dutch Pharmacogenetics Working Group (DPWG). PharmCAT has introduced new features in the last two years, including a VCF preprocessor, the inclusion of DPWG guidelines, and functionalities for PGx research. For example, researchers can use the VCF preprocessor to prepare biobank-scale data for PharmCAT. In addition, PharmCAT enables the assessment of novel partial and combination alleles that are composed of known PGx variants and can call CYP2D6 genotypes based on SNPs and INDELs in the input VCF file. This tutorial provides materials and detailed step-by-step instructions for how to use PharmCAT in a versatile way that can be tailored to users' individual needs.

  View details for DOI 10.1002/cpt.2790

  View details for PubMedID 36350094

• An evidence-based framework for evaluating pharmacogenomics knowledge for personalized medicine. Clinical pharmacology and therapeutics Whirl-Carrillo, M., Huddart, R., Gong, L., Sangkuhl, K., Thorn, C. F., Whaley, R., Klein, T. E. 2021

  Abstract

  Clinical annotations are one of the most popular resources available on the Pharmacogenomics Knowledgebase (PharmGKB). Each clinical annotation summarizes the association between variant-drug pairs, shows relevant findings from the curated literature and is assigned a level of evidence (LOE) to indicate the strength of support for that association. Evidence from the pharmacogenomic literature is curated into PharmGKB as variant annotations, which can be used to create new clinical annotations or added to existing clinical annotations. This means that the same clinical annotation can be worked on by multiple curators over time. As more evidence is curated into PharmGKB, the task of maintaining consistency when assessing all the available evidence and assigning a level of evidence becomes increasingly difficult. To remedy this, a scoring system has been developed to automate LOE assignment to clinical annotations. Variant annotations are scored according to certain attributes including study size, reported p-value and whether the variant annotation supports or fails to find an association. Clinical guidelines or FDA-approved drug labels which give variant-specific prescribing guidance are also scored. The scores of all annotations attached to a clinical annotation are summed together to give a total score for the clinical annotation, which is used to calculate a LOE. Overall, the system increases transparency, consistency and reproducibility in LOE assignment to clinical annotations. In combination with increased standardization of how clinical annotations are written, use of this scoring system helps to ensure that PharmGKB clinical annotations continue to be a robust source of pharmacogenomic information.

  View details for DOI 10.1002/cpt.2350

  View details for PubMedID 34216021

• PGxMine: Text mining for curation of PharmGKB. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Lever, J. n., Barbarino, J. M., Gong, L. n., Huddart, R. n., Sangkuhl, K. n., Whaley, R. n., Whirl-Carrillo, M. n., Woon, M. n., Klein, T. E., Altman, R. B. 2020; 25: 611–22

  Abstract

  Precision medicine tailors treatment to individuals personal data including differences in their genome. The Pharmacogenomics Knowledgebase (PharmGKB) provides highly curated information on the effect of genetic variation on drug response and side effects for a wide range of drugs. PharmGKB's scientific curators triage, review and annotate a large number of papers each year but the task is challenging. We present the PGxMine resource, a text-mined resource of pharmacogenomic associations from all accessible published literature to assist in the curation of PharmGKB. We developed a supervised machine learning pipeline to extract associations between a variant (DNA and protein changes, star alleles and dbSNP identifiers) and a chemical. PGxMine covers 452 chemicals and 2,426 variants and contains 19,930 mentions of pharmacogenomic associations across 7,170 papers. An evaluation by PharmGKB curators found that 57 of the top 100 associations not found in PharmGKB led to 83 curatable papers and a further 24 associations would likely lead to curatable papers through citations. The results can be viewed at https://pgxmine.pharmgkb.org/ and code can be downloaded at https://github.com/jakelever/pgxmine.

  View details for PubMedID 31797632

• PGxMine: Text mining for curation of PharmGKB Lever, J., Barbarino, J. M., Gong, L., Huddart, R., Sangkuhl, K., Whaley, R., Whirl-Carrillo, M., Woon, M., Klein, T. E., Altman, R. B. edited by Altman, R. B., Dunker, A. K., Hunter, L., Ritchie, M. D., Murray, T., Klein, T. E. WORLD SCIENTIFIC PUBL CO PTE LTD. 2020: 611-622

  View details for Web of Science ID 000702064500054

• Genome-wide association study of platelet reactivity and cardiovascular response in patients treated with clopidogrel: a study by the International Clopidogrel Pharmacogenomics Consortium (ICPC). Clinical pharmacology and therapeutics Verma, S. S., Bergmeijer, T. O., Gong, L. n., Reny, J. L., Lewis, J. P., Mitchell, B. D., Alexopoulos, D. n., Aradi, D. n., Altman, R. B., Bliden, K. n., Bradford, Y. n., Campo, G. n., Chang, K. n., Cleator, J. H., Déry, J. P., Dridi, N. P., Fernandez-Cadenas, I. n., Fontana, P. n., Gawaz, M. n., Geisler, T. n., Gensini, G. F., Giusti, B. n., Gurbel, P. A., Hochholzer, W. n., Holmvang, L. n., Kim, E. Y., Kim, H. S., Marcucci, R. n., Montaner, J. n., Backman, J. D., Pakyz, R. E., Roden, D. M., Schaeffeler, E. n., Schwab, M. n., Shin, J. G., Siller-Matula, J. M., Ten Berg, J. M., Trenk, D. n., Valgimigli, M. n., Wallace, J. n., Wen, M. S., Kubo, M. n., Lee, M. T., Whaley, R. n., Winter, S. n., Klein, T. E., Shuldiner, A. R., Ritchie, M. D. 2020

  Abstract

  Antiplatelet response to clopidogrel shows wide variation, and poor response is correlated with adverse clinical outcomes. CYP2C19 loss-of-function alleles play an important role in this response, but account for only a small proportion of variability in response to clopidogrel. An aim of the International Clopidogrel Pharmacogenomics Consortium (ICPC) is to identify other genetic determinants of clopidogrel pharmacodynamics and clinical response. A genome-wide association study (GWAS) was performed using DNA from 2,750 European ancestry individuals, using adenosine diphosphate (ADP) induced platelet reactivity and major cardiovascular and cerebrovascular events as outcome parameters. GWAS for platelet reactivity revealed a strong signal for CYP2C19*2 (p-value=1.67e-33). After correction for CYP2C19*2 no other SNP reached genome-wide significance. GWAS for a combined clinical endpoint of cardiovascular death, myocardial infarction, or stroke (5.0% event rate) or a combined endpoint of cardiovascular death or myocardial infarction (4.7% event rate) showed no significant results, although in coronary artery disease, percutaneous coronary intervention, and acute coronary syndrome subgroups, mutations in SCOS5P1, CDC42BPA and CTRAC1 showed genome-wide significance (lowest p-values: 1.07e-09, 4.53e-08 and 2.60e-10, respectively). CYP2C19*2 is the strongest genetic determinant of on-clopidogrel platelet reactivity. We identified three novel associations in clinical outcome subgroups, suggestive for each of these outcomes.

  View details for DOI 10.1002/cpt.1911

  View details for PubMedID 32472697

• Pharmacogenomic Polygenic Response Score Predicts Ischemic Events and Cardiovascular Mortality in Clopidogrel-Treated Patients. European heart journal. Cardiovascular pharmacotherapy Lewis, J. P., Backman, J. D., Reny, J., Bergmeijer, T. O., Mitchell, B. D., Ritchie, M. D., Dery, J., Pakyz, R. E., Gong, L., Ryan, K., Kim, E., Aradi, D., Fernandez-Cadenas, I., Lee, M. T., Whaley, R. M., Montaner, J., Gensini, G. F., Cleator, J. H., Chang, K., Holmvang, L., Hochholzer, W., Roden, D. M., Winter, S., Altman, R., Alexopoulos, D., Kim, H., Gawaz, M., Bliden, K., Valgimigli, M., Marcucci, R., Campo, G., Schaeffeler, E., Dridi, N. P., Wen, M., Shin, J. G., Fontana, P., Giusti, B., Geisler, T., Kubo, M., Trenk, D., Siller-Matula, J. M., Ten Berg, J. M., Gurbel, P. A., Schwab, M., Klein, T. E., Shuldiner, A. R. 2019

  Abstract

  AIMS: Clopidogrel is prescribed for the prevention of atherothrombotic events. While investigations have identified genetic determinants of inter-individual variability in on-treatment platelet inhibition (e.g. CYP2C19*2), evidence that these variants have clinical utility to predict major adverse cardiovascular events remains controversial.METHODS AND RESULTS: We assessed the impact of 31 candidate gene polymorphisms on ADP-stimulated platelet reactivity in 3,391 clopidogrel-treated coronary artery disease patients of the International Clopidogrel Pharmacogenomics Consortium (ICPC). The influence of these polymorphisms on cardiovascular events (CVE) was tested in 2,134 ICPC patients (N=129 events) in whom clinical event data were available. Several variants were associated with on-treatment ADP-stimulated platelet reactivity (CYP2C19*2, P=8.8x10-54; CES1 G143E, P=1.3x10-16; CYP2C19*17, P=9.5x10-10; CYP2B6 1294+53C>T, P=3.0x10-4; CYP2B6 516G>T, P=1.0x10-3; CYP2C9*2, P=1.2x10-3; and CYP2C9*3, P=1.5x10-3). While no individual variant was associated with CVEs, generation of a pharmacogenomic polygenic response score (PgxRS) revealed that patients who carried a greater number of alleles that associated with increased on-treatment platelet reactivity were more likely to experience CVEs (beta=0.17, SE 0.06, P=0.01) and cardiovascular-related death (beta=0.43, SE 0.16, P=0.007). Patients who carried 8 or more risk alleles were significantly more likely to experience CVEs (OR=1.78, 95%CI 1.14-2.76, P=0.01) and cardiovascular death (OR=4.39, 95%CI 1.35-14.27, P=0.01) compared to patients who carried 6 or fewer of these alleles.CONCLUSION: Several polymorphisms impact clopidogrel response and PgxRS is a predictor of cardiovascular outcomes. Additional investigations that identify novel determinants of clopidogrel response and validating polygenic models may facilitate future precision medicine strategies.

  View details for DOI 10.1093/ehjcvp/pvz045

  View details for PubMedID 31504375

• Pharmacogenomics Clinical Annotation Tool (PharmCAT). Clinical pharmacology and therapeutics Sangkuhl, K., Whirl-Carrillo, M., Whaley, R. M., Woon, M., Lavertu, A., Altman, R. B., Carter, L., Verma, A., Ritchie, M. D., Klein, T. E. 2019

  Abstract

  Pharmacogenomics (PGx) decision support and return of results is an active area of precision medicine. One challenge of implementing PGx is extracting genomic variants and assigning haplotypes in order to apply prescribing recommendations and information from CPIC, FDA, PharmGKB, etc. PharmCAT (1) extracts variants specified in guidelines from a genetic dataset derived from sequencing or genotyping technologies; (2) infers haplotypes and diplotypes; and (3) generates a report containing genotype/diplotype-based annotations and guideline recommendations. We describe PharmCAT and a pilot validation project comparing results for 1000 Genomes sequences of Coriell samples with corresponding Genetic Testing Reference Materials Coordination Program (GeT-RM) sample characterization. PharmCAT was highly concordant with the GeT-RM data. PharmCAT is available in GitHub to evaluate, test and report results back to the community. As precision medicine becomes more prevalent, our ability to consistently, accurately, and clearly define and report PGx annotations and prescribing recommendations is critical. This article is protected by copyright. All rights reserved.

  View details for DOI 10.1002/cpt.1568

  View details for PubMedID 31306493

• The association of obesity and coronary artery disease genes with response to SSRIs treatment in major depression JOURNAL OF NEURAL TRANSMISSION Amare, A. T., Schubert, K., Tekola-Ayele, F., Hsu, Y., Sangkuhl, K., Jenkins, G., Whaley, R. M., Barman, P., Batzler, A., Altman, R. B., Arolt, V., Brockmoeller, J., Chen, C., Domschke, K., Hall-Flavin, D. K., Hong, C., Illi, A., Ji, Y., Kampman, O., Kinoshita, T., Leinonen, E., Liou, Y., Mushiroda, T., Nonen, S., Skime, M. K., Wang, L., Kato, M., Liu, Y., Praphanphoj, V., Stingl, J. C., Bobo, W. V., Tsai, S., Kubo, M., Klein, T. E., Weinshilboum, R. M., Biernacka, J. M., Baune, B. T. 2019; 126 (1): 35–45

  View details for DOI 10.1007/s00702-018-01966-x

  View details for Web of Science ID 000458148200005

• Genome-wide and candidate gene approaches of clopidogrel efficacy using pharmacodynamic and clinical end points-Rationale and design of the International Clopidogrel Pharmacogenomics Consortium (ICPC) AMERICAN HEART JOURNAL Bergmeijer, T. O., Reny, J., Pakyz, R. E., Gong, L., Lewis, J. P., Kim, E., Aradi, D., Fernandez-Cadenas, I., Horenstein, R. B., Lee, M., Whaley, R. M., Montaner, J., Franco Gensini, G., Cleator, J. H., Chang, K., Holmvang, L., Hochholzer, W., Roden, D. M., Winter, S., Altman, R. B., Alexopoulos, D., Kim, H., Dery, J., Gawaz, M., Bliden, K., Valgimigli, M., Marcucci, R., Campo, G., Schaeffeler, E., Dridi, N. P., Wen, M., Shin, J., Simon, T., Fontana, P., Giusti, B., Geisler, T., Kubo, M., Trenk, D., Siller-Matula, J. M., ten Berg, J. M., Gurbel, P. A., Hulot, J., Mitchell, B. D., Schwab, M., Ritchie, M., Klein, T. E., Shuldiner, A. R., ICPC Investigators 2018; 198: 152–59

  Abstract

  The P2Y12 receptor inhibitor clopidogrel is widely used in patients with acute coronary syndrome, percutaneous coronary intervention, or ischemic stroke. Platelet inhibition by clopidogrel shows wide interpatient variability, and high on-treatment platelet reactivity is a risk factor for atherothrombotic events, particularly in high-risk populations. CYP2C19 polymorphism plays an important role in this variability, but heritability estimates suggest that additional genetic variants remain unidentified. The aim of the International Clopidogrel Pharmacogenomics Consortium (ICPC) is to identify genetic determinants of clopidogrel pharmacodynamics and clinical response.Based on the data published on www.clinicaltrials.gov, clopidogrel intervention studies containing genetic and platelet function data were identified for participation. Lead investigators were invited to share DNA samples, platelet function test results, patient characteristics, and cardiovascular outcomes to perform candidate gene and genome-wide studies.In total, 17 study sites from 13 countries participate in the ICPC, contributing individual patient data from 8,829 patients. Available adenosine diphosphate-stimulated platelet function tests included vasodilator-stimulated phosphoprotein assay, light transmittance aggregometry, and the VerifyNow P2Y12 assay. A proof-of-principle analysis based on genotype data provided by each group showed a strong and consistent association between CYP2C19*2 and platelet reactivity (P value=5.1 × 10-40).The ICPC aims to identify new loci influencing clopidogrel efficacy by using state-of-the-art genetic approaches in a large cohort of clopidogrel-treated patients to better understand the genetic basis of on-treatment response variability.

  View details for PubMedID 29653637

• Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder FRONTIERS IN PSYCHIATRY Amare, A. T., Schubert, K., Tekola-Ayele, F., Hsu, Y., Sangkuhl, K., Jenkins, G., Whaley, R. M., Barman, P., Batzler, A., Altman, R. B., Arolt, V., Brockmoeller, J., Chen, C., Domschke, K., Hall-Flavin, D. K., Hong, C., Illi, A., Ji, Y., Kampman, O., Kinoshita, T., Leinonen, E., Liou, Y., Mushiroda, T., Nonen, S., Skime, M. K., Wang, L., Kato, M., Liu, Y., Praphanphoj, V., Stingl, J. C., Bobo, W. V., Tsai, S., Kubo, M., Klein, T. E., Weinshilboum, R. M., Biernacka, J. M., Baune, B. T. 2018; 9: 65

  Abstract

  Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across PT thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs.

  View details for PubMedID 29559929

• The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response. Translational psychiatry Biernacka, J. M., Sangkuhl, K., Jenkins, G., Whaley, R. M., Barman, P., Batzler, A., Altman, R. B., Arolt, V., Brockmöller, J., Chen, C. H., Domschke, K., Hall-Flavin, D. K., Hong, C. J., Illi, A., Ji, Y., Kampman, O., Kinoshita, T., Leinonen, E., Liou, Y. J., Mushiroda, T., Nonen, S., Skime, M. K., Wang, L., Baune, B. T., Kato, M., Liu, Y. L., Praphanphoj, V., Stingl, J. C., Tsai, S. J., Kubo, M., Klein, T. E., Weinshilboum, R. 2015; 5: e553

  Abstract

  Response to treatment with selective serotonin reuptake inhibitors (SSRIs) varies considerably between patients. The International SSRI Pharmacogenomics Consortium (ISPC) was formed with the primary goal of identifying genetic variation that may contribute to response to SSRI treatment of major depressive disorder. A genome-wide association study of 4-week treatment outcomes, measured using the 17-item Hamilton Rating Scale for Depression (HRSD-17), was performed using data from 865 subjects from seven sites. The primary outcomes were percent change in HRSD-17 score and response, defined as at least 50% reduction in HRSD-17. Data from two prior studies, the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study (PGRN-AMPS) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, were used for replication, and a meta-analysis of the three studies was performed (N=2394). Although many top association signals in the ISPC analysis map to interesting candidate genes, none were significant at the genome-wide level and the associations were not replicated using PGRN-AMPS and STAR*D data. The top association result in the meta-analysis of response represents SNPs 5′ upstream of the neuregulin-1 gene, NRG1 (P = 1.20E - 06). NRG1 is involved in many aspects of brain development, including neuronal maturation and variations in this gene have been shown to be associated with increased risk for mental disorders, particularly schizophrenia. Replication and functional studies of these findings are warranted.

  View details for DOI 10.1038/tp.2015.47

  View details for PubMedID 25897834

  View details for PubMedCentralID PMC4462610

• INTERACTIVE GENOTYPE-BASED DOSING GUIDELINES. Whirl-Carrillo, M., Whaley, R. M., Caudle, K. E., Relling, M. V., Altman, R. B., Klein, T. E. WILEY-BLACKWELL. 2015: S61

  View details for Web of Science ID 000348730500184

• CYP2D6 Genotype and Adjuvant Tamoxifen: Meta-Analysis of Heterogeneous Study Populations CLINICAL PHARMACOLOGY & THERAPEUTICS Province, M. A., Goetz, M. P., Brauch, H., Flockhare, D. A., Hebert, J. M., Whaley, R., Suman, V. J., Schroth, W., Winter, S., Zembutsu, H., Mushiroda, T., Newman, W. G., Lee, M. M., Ambrosone, C. B., Beckmann, M. W., Choi, J., Dieudonne, A., Fasching, P. A., Ferraldeschi, R., Gong, L., Haschke-Becher, E., Howel, A., Jordan, L. B., Hamann, U., Kiyotani, K., Krippl, P., Lambrechts, D., Latif, A., Langsenlehner, U., Lorizio, W., Neven, P., Nguyen, A. T., Park, B., Purdie, C. A., Quinlan, P., Renner, W., Schmidt, M., Schwab, M., Shin, J., Stingl, J. C., Wegman, P., Wingren, S., Wu, A. H., Ziv, E., ZIRPOLI, G., Thompson, A. M., Jordan, V. C., Nakamura, Y., Altman, R. B., Ames, M. M., Weinshilboum, R. M., Eichelbaum, M., Ingle, J. N., Klein, T. E. 2014; 95 (2): 216-227

  Abstract

  The International Tamoxifen Pharmacogenomics Consortium was established to address the controversy regarding cytochrome P450 2D6 (CYP2D6) status and clinical outcomes in tamoxifen therapy. We performed a meta-analysis on data from 4,973 tamoxifen-treated patients (12 globally distributed sites). Using strict eligibility requirements (postmenopausal women with estrogen receptor-positive breast cancer, receiving 20 mg/day tamoxifen for 5 years, criterion 1); CYP2D6 poor metabolizer status was associated with poorer invasive disease-free survival (IDFS: hazard ratio = 1.25; 95% confidence interval = 1.06, 1.47; P = 0.009). However, CYP2D6 status was not statistically significant when tamoxifen duration, menopausal status, and annual follow-up were not specified (criterion 2, n = 2,443; P = 0.25) or when no exclusions were applied (criterion 3, n = 4,935; P = 0.38). Although CYP2D6 is a strong predictor of IDFS using strict inclusion criteria, because the results are not robust to inclusion criteria (these were not defined a priori), prospective studies are necessary to fully establish the value of CYP2D6 genotyping in tamoxifen therapy.

  View details for DOI 10.1038/clpt.2013.186

  View details for PubMedID 24060820

• The BioPAX community standard for pathway data sharing NATURE BIOTECHNOLOGY Demir, E., Cary, M. P., Paley, S., Fukuda, K., Lemer, C., Vastrik, I., Wu, G., D'Eustachio, P., Schaefer, C., Luciano, J., Schacherer, F., Martinez-Flores, I., Hu, Z., Jimenez-Jacinto, V., Joshi-Tope, G., Kandasamy, K., Lopez-Fuentes, A. C., Mi, H., Pichler, E., Rodchenkov, I., Splendiani, A., Tkachev, S., Zucker, J., Gopinath, G., Rajasimha, H., Ramakrishnan, R., Shah, I., Syed, M., Anwar, N., Babur, O., Blinov, M., Brauner, E., Corwin, D., Donaldson, S., Gibbons, F., Goldberg, R., Hornbeck, P., Luna, A., Murray-Rust, P., Neumann, E., Reubenacker, O., Samwald, M., van Iersel, M., Wimalaratne, S., Allen, K., Braun, B., Whirl-Carrillo, M., Cheung, K., Dahlquist, K., Finney, A., Gillespie, M., Glass, E., Gong, L., Haw, R., Honig, M., Hubaut, O., Kane, D., Krupa, S., Kutmon, M., Leonard, J., Marks, D., Merberg, D., Petri, V., Pico, A., Ravenscroft, D., Ren, L., Shah, N., Sunshine, M., Tang, R., Whaley, R., Letovksy, S., Buetow, K. H., Rzhetsky, A., Schachter, V., Sobral, B. S., Dogrusoz, U., McWeeney, S., Aladjem, M., Birney, E., Collado-Vides, J., Goto, S., Hucka, M., Le Novere, N., Maltsev, N., Pandey, A., Thomas, P., Wingender, E., Karp, P. D., Sander, C., Bader, G. D. 2010; 28 (9): 935-942

  Abstract

  Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.

  View details for DOI 10.1038/nbt.1666

  View details for Web of Science ID 000281719100019

  View details for PubMedID 20829833

  View details for PubMedCentralID PMC3001121

• Clinical assessment incorporating a personal genome LANCET Ashley, E. A., Butte, A. J., Wheeler, M. T., Chen, R., Klein, T. E., Dewey, F. E., Dudley, J. T., Ormond, K. E., Pavlovic, A., Morgan, A. A., Pushkarev, D., Neff, N. F., Hudgins, L., Gong, L., Hodges, L. M., Berlin, D. S., Thorn, C. F., Sangkuhl, K., Hebert, J. M., Woon, M., Sagreiya, H., Whaley, R., Knowles, J. W., Chou, M. F., Thakuria, J. V., Rosenbaum, A. M., Zaranek, A. W., Church, G. M., Greely, H. T., Quake, S. R., Altman, R. B. 2010; 375 (9725): 1525-1535

  Abstract

  The cost of genomic information has fallen steeply, but the clinical translation of genetic risk estimates remains unclear. We aimed to undertake an integrated analysis of a complete human genome in a clinical context.We assessed a patient with a family history of vascular disease and early sudden death. Clinical assessment included analysis of this patient's full genome sequence, risk prediction for coronary artery disease, screening for causes of sudden cardiac death, and genetic counselling. Genetic analysis included the development of novel methods for the integration of whole genome and clinical risk. Disease and risk analysis focused on prediction of genetic risk of variants associated with mendelian disease, recognised drug responses, and pathogenicity for novel variants. We queried disease-specific mutation databases and pharmacogenomics databases to identify genes and mutations with known associations with disease and drug response. We estimated post-test probabilities of disease by applying likelihood ratios derived from integration of multiple common variants to age-appropriate and sex-appropriate pre-test probabilities. We also accounted for gene-environment interactions and conditionally dependent risks.Analysis of 2.6 million single nucleotide polymorphisms and 752 copy number variations showed increased genetic risk for myocardial infarction, type 2 diabetes, and some cancers. We discovered rare variants in three genes that are clinically associated with sudden cardiac death-TMEM43, DSP, and MYBPC3. A variant in LPA was consistent with a family history of coronary artery disease. The patient had a heterozygous null mutation in CYP2C19 suggesting probable clopidogrel resistance, several variants associated with a positive response to lipid-lowering therapy, and variants in CYP4F2 and VKORC1 that suggest he might have a low initial dosing requirement for warfarin. Many variants of uncertain importance were reported.Although challenges remain, our results suggest that whole-genome sequencing can yield useful and clinically relevant information for individual patients.National Institute of General Medical Sciences; National Heart, Lung And Blood Institute; National Human Genome Research Institute; Howard Hughes Medical Institute; National Library of Medicine, Lucile Packard Foundation for Children's Health; Hewlett Packard Foundation; Breetwor Family Foundation.

  View details for Web of Science ID 000277655100025

  View details for PubMedID 20435227

• The pharmacogenetics and pharmacogenomics knowledge base: accentuating the knowledge NUCLEIC ACIDS RESEARCH Hernandez-Boussard, T., Whirl-Carrillo, M., Hebert, J. M., Gong, L., Owen, R., Gong, M., Gor, W., Liu, F., Truong, C., Whaley, R., Woon, M., Zhou, T., Altman, R. B., Klein, T. E. 2008; 36: D913-D918

  Abstract

  PharmGKB is a knowledge base that captures the relationships between drugs, diseases/phenotypes and genes involved in pharmacokinetics (PK) and pharmacodynamics (PD). This information includes literature annotations, primary data sets, PK and PD pathways, and expert-generated summaries of PK/PD relationships between drugs, diseases/phenotypes and genes. PharmGKB's website is designed to effectively disseminate knowledge to meet the needs of our users. PharmGKB currently has literature annotations documenting the relationship of over 500 drugs, 450 diseases and 600 variant genes. In order to meet the needs of whole genome studies, PharmGKB has added new functionalities, including browsing the variant display by chromosome and cytogenetic locations, allowing the user to view variants not located within a gene. We have developed new infrastructure for handling whole genome data, including increased methods for quality control and tools for comparison across other data sources, such as dbSNP, JSNP and HapMap data. PharmGKB has also added functionality to accept, store, display and query high throughput SNP array data. These changes allow us to capture more structured information on phenotypes for better cataloging and comparison of data. PharmGKB is available at www.pharmgkb.org.

  View details for DOI 10.1093/nar/gkm1009

  View details for Web of Science ID 000252545400160

  View details for PubMedID 18032438

  View details for PubMedCentralID PMC2238877