Elias Salfati

All Publications

• GWAS of epigenetic aging rates in blood reveals a critical role for TERT NATURE COMMUNICATIONS Lu, A. T., Xue, L., Salfati, E. L., Chen, B. H., Ferrucci, L., Levy, D., Joehanes, R., Murabito, J. M., Kiel, D. P., Tsai, P., Yet, I., Bell, J. T., Mangino, M., Tanaka, T., McRae, A. F., Marioni, R. E., Visscher, P. M., Wray, N. R., Deary, I. J., Levine, M. E., Quach, A., Assimes, T., Tsao, P. S., Absher, D., Stewart, J. D., Li, Y., Reiner, A. P., Hou, L., Baccarelli, A. A., Whitsel, E. A., Aviv, A., Cardona, A., Day, F. R., Wareham, N. J., Perry, J. B., Ong, K. K., Raj, K., Lunetta, K. L., Horvath, S. 2018; 9: 387

  Abstract

  DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9907 individuals, we find gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in three loci associated with extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggests causal influences of menarche and menopause on IEAA and lipoproteins on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene (TERT) paradoxically confer higher IEAA (P < 2.7 × 10-11). Causal modeling indicates TERT-specific and independent effects on LTL and IEAA. Experimental hTERT-expression in primary human fibroblasts engenders a linear increase in DNA methylation age with cell population doubling number. Together, these findings indicate a critical role for hTERT in regulating the epigenetic clock, in addition to its established role of compensating for cell replication-dependent telomere shortening.

  View details for PubMedID 29374233

• DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation AMERICAN JOURNAL OF HUMAN GENETICS Richard, M. A., Huan, T., Ligthart, S., Gondalia, R., Jhun, M. A., Brody, J. A., Irvin, M. R., Marioni, R., Shen, J., Tsai, P., Montasser, M. E., Jia, Y., Syme, C., Salfati, E. L., Boerwinkle, E., Guan, W., Mosley, T. H., Bressler, J., Morrison, A. C., Liu, C., Mendelson, M. M., Uitterlinden, A. G., van Meurs, J. B., Franco, O. H., Zhang, G., Li, Y., Stewart, J. D., Bis, J. C., Psaty, B. M., Chen, Y., Kardia, S. R., Zhao, W., Turner, S. T., Absher, D., Aslibekyan, S., Starr, J. M., Mcrae, A. F., Hou, L., Just, A. C., Schwartz, J. D., Vokonas, P. S., Menni, C., Spector, T. D., Shuldiner, A., Damcott, C. M., Rotter, J. I., Palmas, W., Liu, Y., Paus, T., Horvath, S., O'Connell, J. R., Guo, X., Pausova, Z., Assimes, T. L., Sotoodehnia, N., Smith, J. A., Arnett, D. K., Deary, I. J., Baccarelli, A. A., Bell, J. T., Whitsel, E., Dehghan, A., Levy, D., Fornage, M., BIOS Consortium 2017; 101 (6): 888–902

  Abstract

  Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0 × 10-7; replication: N = 7,182, p < 1.6 × 10-3). The replicated methylation sites are heritable (h2 > 30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

  View details for PubMedID 29198723

  View details for PubMedCentralID PMC5812919

• Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms. Nature genetics Howson, J. M., Zhao, W., Barnes, D. R., Ho, W., Young, R., Paul, D. S., Waite, L. L., Freitag, D. F., Fauman, E. B., Salfati, E. L., Sun, B. B., Eicher, J. D., Johnson, A. D., Sheu, W. H., Nielsen, S. F., Lin, W., Surendran, P., Malarstig, A., Wilk, J. B., Tybjærg-Hansen, A., Rasmussen, K. L., Kamstrup, P. R., Deloukas, P., Erdmann, J., Kathiresan, S., Samani, N. J., Schunkert, H., Watkins, H., Do, R., Rader, D. J., Johnson, J. A., Hazen, S. L., Quyyumi, A. A., Spertus, J. A., Pepine, C. J., Franceschini, N., Justice, A., Reiner, A. P., Buyske, S., Hindorff, L. A., Carty, C. L., North, K. E., Kooperberg, C., Boerwinkle, E., Young, K., Graff, M., Peters, U., Absher, D., Hsiung, C. A., Lee, W., Taylor, K. D., Chen, Y., Lee, I., Guo, X., Chung, R., Hung, Y., Rotter, J. I., Juang, J. J., Quertermous, T., Wang, T., Rasheed, A., Frossard, P., Alam, D. S., Majumder, A. A., Di Angelantonio, E., Chowdhury, R., Chen, Y. I., Nordestgaard, B. G., Assimes, T. L., Danesh, J., Butterworth, A. S., Saleheen, D. 2017

  Abstract

  Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.

  View details for DOI 10.1038/ng.3874

  View details for PubMedID 28530674

• Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels HUMAN MOLECULAR GENETICS Spracklen, C. N., Chen, P., Kim, Y. J., Wang, X., Cai, H., Li, S., Long, J., Wu, Y., Wang, Y. X., Takeuchi, F., Wu, J., Jung, K., Hu, C., Akiyama, K., Zhang, Y., Moon, S., Johnson, T. A., Li, H., Dorajoo, R., He, M., Cannon, M. E., Roman, T. S., Salfati, E., Lin, K., Guo, X., Sheu, W. H., Absher, D., Adair, L. S., Assimes, T. L., Aung, T., Cai, Q., Chang, L., Chen, C., Chien, L., Chuang, L., Chuang, S., Du, S., Fan, Q., Fann, C. S., Feranil, A. B., Friedlander, Y., Gordon-Larsen, P., Gu, D., Gui, L., Guo, Z., Heng, C., Hixson, J., Hou, X., Hsiung, C. A., Hu, Y., Hwang, M. Y., Hwu, C., Isono, M., Juang, J. J., Khor, C., Kim, Y. K., Koh, W., Kubo, M., Lee, I., Lee, S., Lee, W., Liang, K., Lim, B., Lim, S., Liu, J., Nabika, T., Pan, W., Peng, H., Quertermous, T., Sabanayagam, C., Sandow, K., Shi, J., Sun, L., Tan, P. C., Tan, S., Taylor, K. D., Teo, Y., Toh, S., Tsunoda, T., van Dam, R. M., Wang, A., Wang, F., Wang, J., Wei, W. B., Xiang, Y., Yao, J., Yuan, J., Zhang, R., Zhao, W., Chen, Y. I., Rich, S. S., Rotter, J. I., Wang, T., Wu, T., Lin, X., Han, B., Tanaka, T., Cho, Y. S., Katsuya, T., Jia, W., Jee, S., Chen, Y., Kato, N., Jonas, J. B., Cheng, C., Shu, X., He, J., Zheng, W., Wong, T., Huang, W., Kim, B., Tai, E., Mohlke, K. L., Sim, X. 2017; 26 (9): 1770-1784

  Abstract

  Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets.

  View details for DOI 10.1093/hmg/ddx062

  View details for PubMedID 28334899

• Leveraging information from genetic risk scores of coronary atherosclerosis. Current opinion in lipidology Assimes, T. L., Salfati, E. L., Del Gobbo, L. C. 2017; 28 (2): 104-112

  Abstract

  Genome-wide association studies (GWAS) have identified ∼60 loci for coronary artery disease (CAD). Through genetic risk scores (GRSs), investigators are leveraging this genomic information to gain insights on both the fundamental mechanisms driving these associations as well as their utility in improving risk prediction.GRSs of CAD track with the earliest atherosclerosis lesions in the coronary including fatty streaks and uncomplicated raised lesions. In multiple cohort studies, they predict incident CAD events independent of all traditional and lifestyle risk factors. The incorporation of SNPs with suggestive but not genome-wide association in GWAS into GRSs often increases the strength of these associations. GRS may also predict recurrent events and identify patients most likely to respond to statins. The effect of the GRS on discrimination metrics remains modest but the minimal degree of improvement needed for clinical utility is unknown.Most novel loci for CAD identified through GWAS facilitate the formation of coronary atherosclerosis and stratify individuals based on their underlying burden of coronary atherosclerosis. GRSs may one day be routinely used in clinical practice to not only assess the risk of incident events but also to predict who will respond best to established prevention strategies.

  View details for DOI 10.1097/MOL.0000000000000400

  View details for PubMedID 28207434

• DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases GENOME BIOLOGY Ligthart, S., Marzi, C., Aslibekyan, S., Mendelson, M. M., Conneely, K. N., Tanaka, T., Colicino, E., Waite, L. L., Joehanes, R., Guan, W., Brody, J. A., Elks, C., Marioni, R., Jhun, M. A., Agha, G., Bressler, J., Ward-Caviness, C. K., Chen, B. H., Huan, T., Bakulski, K., Salfati, E. L., Wahl, S., Schramm, K., Sha, J., Hernandez, D. G., Just, A. C., Smith, J. A., Sotoodehnia, N., Pilling, L. C., Pankow, J. S., Tsao, P. S., Liu, C., Zhao, W., Guarrera, S., Michopoulos, V. J., Smith, A. K., Peters, M. J., Melzer, D., Vokonas, P., Fornage, M., Prokisch, H., Bis, J. C., Chu, A. Y., Herder, C., Grallert, H., Yao, C., Shah, S., McRae, A. F., Lin, H., Horvath, S., Fallin, D., Hofman, A., Wareham, N. J., Wiggins, K. L., Feinberg, A. P., Starr, J. M., Visscher, P. M., Murabito, J. M., Kardia, S. L., Absher, D. M., Binder, E. B., Singleton, A. B., Bandinelli, S., Peters, A., Waldenberger, M., Matullo, G., Schwartz, J. D., Demerath, E. W., Uitterlinden, A. G., van Meurs, J. B., Franco, O. H., Chen, Y. I., Levy, D., Turner, S. T., Deary, I. J., Ressler, K. J., Dupuis, J., Ferrucci, L., Ong, K. K., Assimes, T. L., Boerwinkle, E., Koenig, W., Arnett, D. K., Baccarelli, A. A., Benjamin, E. J., Dehghan, A. 2016; 17

  Abstract

  Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation.We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10(-7)) in the discovery panel of European ancestry and replicated (P < 2.29 × 10(-4)) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10(-5)), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10(-3)), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10(-5)). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants.We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.

  View details for DOI 10.1186/s13059-016-1119-5

  View details for PubMedID 27955697

• No Association of Coronary Artery Disease with X-Chromosomal Variants in Comprehensive International Meta-Analysis SCIENTIFIC REPORTS Loley, C., Alver, M., Assimes, T. L., Bjonnes, A., Goel, A., Gustafsson, S., Hernesniemi, J., Hopewell, J. C., Kanoni, S., Kleber, M. E., Lau, K. W., Lu, Y., Lyytikainen, L., Nelson, C. P., Nikpay, M., Qu, L., Salfati, E., Scholz, M., Tukiainen, T., Willenborg, C., Won, H., Zeng, L., Zhang, W., Anand, S. S., Beutner, F., Bottinger, E. P., Clarke, R., Dedoussis, G., Do, R., Esko, T., Eskola, M., Farrall, M., Gauguier, D., Giedraitis, V., Granger, C. B., Hall, A. S., Hamsten, A., Hazen, S. L., Huang, J., Kahonen, M., Kyriakou, T., Laaksonen, R., Lind, L., Lindgren, C., Magnusson, P. K., Marouli, E., Mihailov, E., Morris, A. P., Nikus, K., Pedersen, N., Rallidis, L., Salomaa, V., Shah, S. H., Stewart, A. F., Thompson, J. R., Zalloua, P. A., Chambers, J. C., Collins, R., Ingelsson, E., Iribarren, C., Karhunen, P. J., Kooner, J. S., Lehtimaki, T., Loos, R. J., Maerz, W., McPherson, R., Metspalu, A., Reilly, M. P., Ripatti, S., Sanghera, D. K., Thiery, J., Watkins, H., Deloukas, P., Kathiresan, S., Samani, N. J., Schunkert, H., Erdmann, J., Koenig, I. R. 2016; 6

  Abstract

  In recent years, genome-wide association studies have identified 58 independent risk loci for coronary artery disease (CAD) on the autosome. However, due to the sex-specific data structure of the X chromosome, it has been excluded from most of these analyses. While females have 2 copies of chromosome X, males have only one. Also, one of the female X chromosomes may be inactivated. Therefore, special test statistics and quality control procedures are required. Thus, little is known about the role of X-chromosomal variants in CAD. To fill this gap, we conducted a comprehensive X-chromosome-wide meta-analysis including more than 43,000 CAD cases and 58,000 controls from 35 international study cohorts. For quality control, sex-specific filters were used to adequately take the special structure of X-chromosomal data into account. For single study analyses, several logistic regression models were calculated allowing for inactivation of one female X-chromosome, adjusting for sex and investigating interactions between sex and genetic variants. Then, meta-analyses including all 35 studies were conducted using random effects models. None of the investigated models revealed genome-wide significant associations for any variant. Although we analyzed the largest-to-date sample, currently available methods were not able to detect any associations of X-chromosomal variants with CAD.

  View details for DOI 10.1038/srep35278

  View details for PubMedID 27731410

• The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals. Nature genetics Ehret, G. B., Ferreira, T., Chasman, D. I., Jackson, A. U., Schmidt, E. M., Johnson, T., Thorleifsson, G., Luan, J., Donnelly, L. A., Kanoni, S., Petersen, A., Pihur, V., Strawbridge, R. J., Shungin, D., Hughes, M. F., Meirelles, O., Kaakinen, M., Bouatia-Naji, N., Kristiansson, K., Shah, S., Kleber, M. E., Guo, X., Lyytikäinen, L., Fava, C., Eriksson, N., Nolte, I. M., Magnusson, P. K., Salfati, E. L., Rallidis, L. S., Theusch, E., Smith, A. J., Folkersen, L., Witkowska, K., Pers, T. H., Joehanes, R., Kim, S. K., Lataniotis, L., Jansen, R., Johnson, A. D., Warren, H., Kim, Y. J., Zhao, W., Wu, Y., Tayo, B. O., Bochud, M., Absher, D., Adair, L. S., Amin, N., Arking, D. E., Axelsson, T., Baldassarre, D., Balkau, B., Bandinelli, S., Barnes, M. R., Barroso, I., Bevan, S., Bis, J. C., Bjornsdottir, G., Boehnke, M., Boerwinkle, E., Bonnycastle, L. L., Boomsma, D. I., Bornstein, S. R., Brown, M. J., Burnier, M., Cabrera, C. P., Chambers, J. C., Chang, I., Cheng, C., Chines, P. S., Chung, R., Collins, F. S., Connell, J. M., Döring, A., Dallongeville, J., Danesh, J., de Faire, U., Delgado, G., Dominiczak, A. F., Doney, A. S., Drenos, F., Edkins, S., Eicher, J. D., Elosua, R., Enroth, S., Erdmann, J., Eriksson, P., Esko, T., Evangelou, E., Evans, A., Fall, T., Farrall, M., Felix, J. F., Ferrières, J., Ferrucci, L., Fornage, M., Forrester, T., Franceschini, N., Franco, O. H., Franco-Cereceda, A., Fraser, R. M., Ganesh, S. K., Gao, H., Gertow, K., Gianfagna, F., Gigante, B., Giulianini, F., Goel, A., Goodall, A. H., Goodarzi, M. O., Gorski, M., Gräßler, J., Groves, C. J., Gudnason, V., Gyllensten, U., Hallmans, G., Hartikainen, A., Hassinen, M., Havulinna, A. S., Hayward, C., Hercberg, S., Herzig, K., Hicks, A. A., Hingorani, A. D., Hirschhorn, J. N., Hofman, A., Holmen, J., Holmen, O. L., Hottenga, J., Howard, P., Hsiung, C. A., Hunt, S. C., Ikram, M. A., Illig, T., Iribarren, C., Jensen, R. A., Kähönen, M., Kang, H. M., Kathiresan, S., Keating, B. J., Khaw, K., Kim, Y. K., Kim, E., Kivimaki, M., Klopp, N., Kolovou, G., Komulainen, P., Kooner, J. S., Kosova, G., Krauss, R. M., Kuh, D., Kutalik, Z., Kuusisto, J., Kvaløy, K., Lakka, T. A., Lee, N. R., Lee, I., Lee, W., Levy, D., Li, X., Liang, K., Lin, H., Lin, L., Lindström, J., Lobbens, S., Männistö, S., Müller, G., Müller-Nurasyid, M., Mach, F., Markus, H. S., Marouli, E., McCarthy, M. I., McKenzie, C. A., Meneton, P., Menni, C., Metspalu, A., Mijatovic, V., Moilanen, L., Montasser, M. E., Morris, A. D., Morrison, A. C., Mulas, A., Nagaraja, R., Narisu, N., Nikus, K., O'Donnell, C. J., O'Reilly, P. F., Ong, K. K., Paccaud, F., Palmer, C. D., Parsa, A., Pedersen, N. L., Penninx, B. W., Perola, M., Peters, A., Poulter, N., Pramstaller, P. P., Psaty, B. M., Quertermous, T., Rao, D. C., Rasheed, A., Rayner, N. W., Renström, F., Rettig, R., Rice, K. M., Roberts, R., Rose, L. M., Rossouw, J., Samani, N. J., Sanna, S., Saramies, J., Schunkert, H., Sebert, S., Sheu, W. H., Shin, Y., Sim, X., Smit, J. H., Smith, A. V., Sosa, M. X., Spector, T. D., Stancáková, A., Stanton, A. V., Stirrups, K. E., Stringham, H. M., Sundstrom, J., Swift, A. J., Syvänen, A., Tai, E., Tanaka, T., Tarasov, K. V., Teumer, A., Thorsteinsdottir, U., Tobin, M. D., Tremoli, E., Uitterlinden, A. G., Uusitupa, M., Vaez, A., Vaidya, D., van Duijn, C. M., van Iperen, E. P., Vasan, R. S., Verwoert, G. C., Virtamo, J., Vitart, V., Voight, B. F., Vollenweider, P., Wagner, A., Wain, L. V., Wareham, N. J., Watkins, H., Weder, A. B., Westra, H., Wilks, R., Wilsgaard, T., Wilson, J. F., Wong, T. Y., Yang, T., Yao, J., Yengo, L., Zhang, W., Zhao, J. H., Zhu, X., Bovet, P., Cooper, R. S., Mohlke, K. L., Saleheen, D., Lee, J., Elliott, P., Gierman, H. J., Willer, C. J., Franke, L., Hovingh, G. K., Taylor, K. D., Dedoussis, G., Sever, P., Wong, A., Lind, L., Assimes, T. L., Njølstad, I., Schwarz, P. E., Langenberg, C., Snieder, H., Caulfield, M. J., Melander, O., Laakso, M., Saltevo, J., Rauramaa, R., Tuomilehto, J., Ingelsson, E., Lehtimäki, T., Hveem, K., Palmas, W., März, W., Kumari, M., Salomaa, V., Chen, Y. I., Rotter, J. I., Froguel, P., Jarvelin, M., Lakatta, E. G., Kuulasmaa, K., Franks, P. W., Hamsten, A., Wichmann, H., Palmer, C. N., Stefansson, K., Ridker, P. M., Loos, R. J., Chakravarti, A., Deloukas, P., Morris, A. P., Newton-Cheh, C., Munroe, P. B. 2016; 48 (10): 1171-1184

  Abstract

  To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.

  View details for DOI 10.1038/ng.3667

  View details for PubMedID 27618452

• The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals NATURE GENETICS Ehret, G. B., Ferreira, T., Chasman, D. I., Jackson, A. U., Schmidt, E. M., Johnson, T., Thorleifsson, G., Luan, J., Donnelly, L. A., Kanoni, S., Petersen, A. -., Pihurl, V., Strawbridge, R. J., Shungin, D., Hughes, M. F., Meirelles, O., Kaakinen, M., Bouatia-Naji, N., Kristiansson, K., Shah, S., Kleber, M. E., Guo, X., Lyytikainen, L., Fava, C., Eriksson, N., Nolte, I. M., Magnusson, P. K., Salfati, E. L., Rallidis, L. S., Theusch, E., Smith, A. J., Folkersen, L., Witkowska, K., Pers, T. H., Joehanes, R., Kim, S. K., Lataniotis, L., Jansen, R., Johnson, A. D., Warren, H., Kim, Y. J., Zhao, W., Wu, Y., Tayo, B. O., Bochud, M., Absher, D., Adair, L. S., Amin, N., Arkingl, D. E., Axelsson, T., Baldassarre, D., Balkau, B., Bandinelli, S., Barnes, M. R., Barroso, I., Bevan, S., Bis, J. C., Bjornsdottir, G., Boehnke, M., Boerwinkle, E., Bonnycastle, L. L., Boomsma, D. I., Bornstein, S. R., Brown, M. J., Burnier, M., Cabrera, C. P., Chambers, J. C., Chang, I., Cheng, C., Chines, P. S., Chung, R., Collins, F. S., Connell, J. M., Doring, A., Dallongeville, J., Danesh, J., de Faire, U., Delgado, G., Dominiczak, A. F., Doney, A. S., Drenos, F., Edkins, S., Eicher, J. D., Elosua, R., Enroth, S., Erdmann, J., Eriksson, P., Esko, T., Evangelou, E., Evans, A., Fai, T., Farra, M., Felixl, J. F., Ferrieres, J., Ferrucci, L., Fornage, M., Forrester, T., Franceschinil, N., Franco, O. H., Franco-Cereceda, A., Fraser, R. M., Ganesh, S. K., Gao, H., Gertow, K., Gianfagna, F., Gigante, B., Giulianini, F., Goe, A., Goodall, A. H., Goodarzi, M., Gorski, M., Grassler, J., Groves, C. J., Gudnason, V., Gyllensten, U., Hallmans, G., Hartikainen, A., Hassinen, M., Havulinna, A. S., Hayward, C., Hercberg, S., Herzig, K., Hicks, A. A., Hingorani, A. D., Hirschhorn, J. N., Hofmanl, A., Holmen, J., Holmen, O. L., Hottenga, J., Howard, P., Hsiung, C. A., Hunt, S. C., Ikram, M. A., Illig, T., Iribarren, C., Jensen, R. A., Kahonen, M., Kang, H. M., Kathiresan, S., Keating, B. J., Khaw, K., Kim, Y. K., Kim, E., Kivimaki, M., Klopp, N., Kolovou, G., Komulainen, P., Kooner, J. S., Kosova, G., Krauss, R. M., Kuh, D., Kutalik, Z., Kuusisto, J., Kvaloy, K., Lakka, T. A., Lee, N. R., Lee, I., Lee, W., Levy, D., Li, X., Liang, K., Lin, H., Lin, L., Lindstrom, J., Lobbens, S., Mannisto, S., Muller, G., Muller-Nurasyid, M., Mach, F., Markus, H. S., Marouli, E., McCarthy, M. I., McKenzie, C. A., Meneton, P., Menni, C., Metspalu, A., Mijatovic, V., Moilanen, L., Montasser, M. E., Morris, A. D., Morrison, A. C., Mulas, A., Nagaraja, R., Narisu, N., Nikus, K., O'Donnell, C. J., O'Reilly, P. F., Ong, K. K., Paccaud, F., Palmer, C. D., Parsa, A., Pedersen, N. L., Penninx, B. W., Perola, M., Peters, A., Poulter, N., Pramstaller, P. P., Psaty, B. M., Quertermous, T., Rao, D. C., Rasheed, A., Rayner, N. W., Renstrom, F., Rettig, R., Rice, K. M., Roberts, R., Rose, L. M., Rossouw, J., Samani, N. J., Sanna, S., Saramies, J., Schunkert, H., Sebert, S., Sheu, W. H., Shin, Y., Sim, X., Smit, J. H., Smith, A. V., Sosa, M. X., Spector, T. D., Stancakova, A., Stanton, A. V., Stirrups, K. E., Stringham, H. M., Sundstrom, J., Swift, A. J., Syvanen, A., Tai, E., Tanaka, T., Tarasov, K. V., Teumer, A., Thorsteinsdottir, U., Tobin, M. D., Tremoli, E., Uitterlinden, A. G., Uusitupa, M., Vaez, A., Vaidya, D., van Duijn, C. M., van Iperen, E. P., Vasan, R. S., Verwoert, G. C., Virtamo, J., Vitart, V., Voight, B. F., Vollenweider, P., Wagner, A., Wain, L. V., Wareham, N. J., Watldns, H., Weder, A. B., Westra, H. J., Wilks, R., Wilsgaard, T., Wilson, J. F., Wong, T. Y., Yang, T., Yao, J., Yengo, L., Zhang, W., Zhao, J. H., Zhu, X., Bovet, P., Cooper, R. S., Mohlke, K. L., Saleheen, D., Lee, J., Elliott, P., Gierman, H. J., Willer, C. J., Franke, L., Hovingh, G. K., Taylor, K. D., Dedoussis, G., Sever, P., Wong, A., Lind, L., Assimes, T. L., Njolstad, I., Schwarz, P. E., Langenberg, C., Snieder, H., Caulfield, M. J., Melander, E., Laakso, M., Saltevo, J., Rauramaa, R., Tuomilehto, J., Ingelsson, E., Lehtimaki, T., Hveem, K., Palmas, W., Marz, W., Kumar, M., Salomaa, V., Chen, Y. I., Rotter, J. I., Froguel, P., Jarvelin, M., Lakatta, E. G., Kuulasmaa, K., Franks, P. W., Hamsten, A., Wichmann, H., Palmer, C. N., Stefansson, K., Ridker, P. M., Loos, R. J., Chalcravarti, A., Deloukas, P., Morris, A. P., Newton-Cheh, C., Munroe, P. B. 2016; 48 (10): 1171-1184

  Abstract

  To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.

  View details for DOI 10.1038/ng.3667

  View details for Web of Science ID 000384391600012

  View details for PubMedCentralID PMC5042863

• Menopause accelerates biological aging. Proceedings of the National Academy of Sciences of the United States of America Levine, M. E., Lu, A. T., Chen, B. H., Hernandez, D. G., Singleton, A. B., Ferrucci, L., Bandinelli, S., Salfati, E., Manson, J. E., Quach, A., Kusters, C. D., Kuh, D., Wong, A., Teschendorff, A. E., Widschwendter, M., Ritz, B. R., Absher, D., Assimes, T. L., Horvath, S. 2016; 113 (33): 9327-9332

  Abstract

  Although epigenetic processes have been linked to aging and disease in other systems, it is not yet known whether they relate to reproductive aging. Recently, we developed a highly accurate epigenetic biomarker of age (known as the "epigenetic clock"), which is based on DNA methylation levels. Here we carry out an epigenetic clock analysis of blood, saliva, and buccal epithelium using data from four large studies: the Women's Health Initiative (n = 1,864); Invecchiare nel Chianti (n = 200); Parkinson's disease, Environment, and Genes (n = 256); and the United Kingdom Medical Research Council National Survey of Health and Development (n = 790). We find that increased epigenetic age acceleration in blood is significantly associated with earlier menopause (P = 0.00091), bilateral oophorectomy (P = 0.0018), and a longer time since menopause (P = 0.017). Conversely, epigenetic age acceleration in buccal epithelium and saliva do not relate to age at menopause; however, a higher epigenetic age in saliva is exhibited in women who undergo bilateral oophorectomy (P = 0.0079), while a lower epigenetic age in buccal epithelium was found for women who underwent menopausal hormone therapy (P = 0.00078). Using genetic data, we find evidence of coheritability between age at menopause and epigenetic age acceleration in blood. Using Mendelian randomization analysis, we find that two SNPs that are highly associated with age at menopause exhibit a significant association with epigenetic age acceleration. Overall, our Mendelian randomization approach and other lines of evidence suggest that menopause accelerates epigenetic aging of blood, but mechanistic studies will be needed to dissect cause-and-effect relationships further.

  View details for DOI 10.1073/pnas.1604558113

  View details for PubMedID 27457926

• Susceptibility Loci for Clinical Coronary Artery Disease and Subclinical Coronary Atherosclerosis Throughout the Life-Course. Circulation. Cardiovascular genetics Salfati, E., Nandkeolyar, S., Fortmann, S. P., Sidney, S., Hlatky, M. A., Quertermous, T., Go, A. S., Iribarren, C., Herrington, D. M., Goldstein, B. A., Assimes, T. L. 2015; 8 (6): 803-811

  Abstract

  -Recent genome wide association studies (GWAS) have identified 49 single nucleotide polymorphisms (SNPs) associated with clinical CAD. The mechanism by which these loci influence risk remains largely unclear.-We examined the association between a genetic risk score (GRS) composed of high-risk alleles at the 49 SNPs and the degree of subclinical coronary atherosclerosis in 7,798 participants from six studies stratified into four age groups at the time of assessment (15-34, 35-54, 55-74, >75 years). Atherosclerosis was quantified by staining and direct visual inspection of the right coronary artery in the youngest group, and by scanning for coronary artery calcification in the remaining groups. We defined cases as subjects within the top quartile of degree of atherosclerosis in three groups and as subjects with a CAC>0 in the fourth (35-54 years) where less than one quarter had any CAC. In our meta-analysis of all strata, we found one SD increase in the GRS increased the risk of advanced subclinical coronary atherosclerosis by 36% (p=8.3×10(-25)). This increase in risk was significant in all four age groups including the youngest group where atherosclerosis consisted primarily of raised lesions without macroscopic evidence of plaque rupture or thrombosis. Results were similar when we restricted the GRS to 32 SNPs not associated with traditional risk factors (TRFs) and/or when we adjusted for TRFs.-A GRS for clinical CAD is associated with advanced subclinical coronary atherosclerosis throughout the life-course. This association is apparent even at the earliest, uncomplicated stages of atherosclerosis.

  View details for DOI 10.1161/CIRCGENETICS.114.001071

  View details for PubMedID 26417035

• Susceptibility Loci for Clinical Coronary Artery Disease and Subclinical Coronary Atherosclerosis Throughout the Life-Course CIRCULATION-CARDIOVASCULAR GENETICS Salfati, E., Nandkeolyar, S., Fortmann, S. P., Sidney, S., Hlatky, M. A., Quertermous, T., Go, A. S., Iribarren, C., Herrington, D. M., Goldstein, B. A., Assimes, T. L. 2015; 8 (6): 803-811

  Abstract

  -Recent genome wide association studies (GWAS) have identified 49 single nucleotide polymorphisms (SNPs) associated with clinical CAD. The mechanism by which these loci influence risk remains largely unclear.-We examined the association between a genetic risk score (GRS) composed of high-risk alleles at the 49 SNPs and the degree of subclinical coronary atherosclerosis in 7,798 participants from six studies stratified into four age groups at the time of assessment (15-34, 35-54, 55-74, >75 years). Atherosclerosis was quantified by staining and direct visual inspection of the right coronary artery in the youngest group, and by scanning for coronary artery calcification in the remaining groups. We defined cases as subjects within the top quartile of degree of atherosclerosis in three groups and as subjects with a CAC>0 in the fourth (35-54 years) where less than one quarter had any CAC. In our meta-analysis of all strata, we found one SD increase in the GRS increased the risk of advanced subclinical coronary atherosclerosis by 36% (p=8.3×10(-25)). This increase in risk was significant in all four age groups including the youngest group where atherosclerosis consisted primarily of raised lesions without macroscopic evidence of plaque rupture or thrombosis. Results were similar when we restricted the GRS to 32 SNPs not associated with traditional risk factors (TRFs) and/or when we adjusted for TRFs.-A GRS for clinical CAD is associated with advanced subclinical coronary atherosclerosis throughout the life-course. This association is apparent even at the earliest, uncomplicated stages of atherosclerosis.

  View details for DOI 10.1161/CIRCGENETICS.114.001071

  View details for Web of Science ID 000366604900007

  View details for PubMedID 26417035

• A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease NATURE GENETICS Nikpay, M., Goel, A., Won, H., Hall, L. M., Willenborg, C., Kanoni, S., Saleheen, D., Kyriakou, T., Nelson, C. P., Hopewell, J. C., Webb, T. R., Zeng, L., Dehghan, A., Alver, M., Armasu, S. M., Auro, K., Bjonnes, A., Chasman, D. I., Chen, S., Ford, I., Franceschini, N., Gieger, C., Grace, C., Gustafsson, S., Huang, J., Hwang, S., Kim, Y. K., Kleber, M. E., Lau, K. W., Lu, X., Lu, Y., Lyytikainen, L., Mihailov, E., Morrison, A. C., Pervjakova, N., Qu, L., Rose, L. M., Salfati, E., Saxena, R., Scholz, M., Smith, A. V., Tikkanen, E., Uitterlinden, A., Yang, X., Zhang, W., Zhao, W., de Andrade, M., de Vries, P. S., Van Zuydam, N. R., Anand, S. S., Bertram, L., Beutner, F., Dedoussis, G., Frossard, P., Gauguier, D., Goodall, A. H., Gottesman, O., Haber, M., Han, B., Huang, J., Jalilzadeh, S., Kessler, T., Koenig, I. R., Lannfelt, L., Lieb, W., Lind, L., Lindgren, C. M., Lokki, M., Magnusson, P. K., Mallick, N. H., Mehra, N., Meitinger, T., Memon, F., Morris, A. P., Nieminen, M. S., Pedersen, N. L., Peters, A., Rallidis, L. S., Rasheed, A., Samuel, M., Shah, S. H., Sinisalo, J., Stirrups, K. E., Trompet, S., Wang, L., Zaman, K. S., Ardissino, D., Boerwinkle, E., Borecki, I. B., Bottinger, E. P., Buring, J. E., Chambers, J. C., Collins, R., Cupples, L. A., Danesh, J., Demuth, I., Elosua, R., Epstein, S. E., Esko, T., Feitosa, M. F., Franco, O. H., Franzosi, M. G., Granger, C. B., Gu, D., Gudnason, V., Hall, A. S., Hamsten, A., Harris, T. B., Hazen, S. L., Hengstenberg, C., Hofman, A., Ingelsson, E., Iribarren, C., Jukema, J. W., Karhunen, P. J., Kim, B., Kooner, J. S., Kullo, I. J., Lehtimaki, T., Loos, R. J., Melander, O., Metspalu, A., Maerz, W., Palmer, C. N., Perola, M., Quertermous, T., Rader, D. J., Ridker, P. M., Ripatti, S., Roberts, R., Salomaa, V., Sanghera, D. K., Schwartz, S. M., Seedorf, U., Stewart, A. F., Stott, D. J., Thiery, J., Zalloua, P. A., O'Donnell, C. J., Reilly, M. P., Assimes, T. L., Thompson, J. R., Erdmann, J., Clarke, R., Watkins, H., Kathiresan, S., McPherson, R., Deloukas, P., Schunkert, H., Samani, N. J., Farrall, M. 2015; 47 (10): 1121-?

  Abstract

  Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ∼185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.

  View details for DOI 10.1038/ng.3396

  View details for PubMedID 26343387

• Contemporary Considerations for Constructing a Genetic Risk Score: An Empirical Approach. Genetic epidemiology Goldstein, B. A., Yang, L., Salfati, E., Assimes, T. L. 2015; 39 (6): 439-445

  Abstract

  Genetic risk scores are an increasingly popular tool for summarizing the cumulative risk of a set of Single Nucleotide Polymorphisms (SNPs) with disease. Typically only the set of the SNPs that have reached genome-wide significance compose these scores. However recent work suggests that including additional SNPs may aid risk assessment. In this paper, we used the Atherosclerosis Risk in Communities (ARIC) Study cohort to illustrate how one can choose the optimal set of SNPs for a genetic risk score (GRS). In addition to P-value threshold, we also examined linkage disequilibrium, imputation quality, and imputation type. We provide a variety of evaluation metrics. Results suggest that P-value threshold had the greatest impact on GRS quality for the outcome of coronary heart disease, with an optimal threshold around 0.001. However, GRSs are relatively robust to both linkage disequilibrium and imputation quality. We also show that the optimal GRS partially depends on the evaluation metric and consequently the way one intends to use the GRS. Overall the implications highlight both the robustness of GRS and a means to empirically choose the best set of GRSs.

  View details for DOI 10.1002/gepi.21912

  View details for PubMedID 26198599

• Contemporary Considerations for Constructing a Genetic Risk Score: An Empirical Approach GENETIC EPIDEMIOLOGY Goldstein, B. A., Yang, L., Salfati, E., Assimes, T. L. 2015; 39 (6): 439-445

  Abstract

  Genetic risk scores are an increasingly popular tool for summarizing the cumulative risk of a set of Single Nucleotide Polymorphisms (SNPs) with disease. Typically only the set of the SNPs that have reached genome-wide significance compose these scores. However recent work suggests that including additional SNPs may aid risk assessment. In this paper, we used the Atherosclerosis Risk in Communities (ARIC) Study cohort to illustrate how one can choose the optimal set of SNPs for a genetic risk score (GRS). In addition to P-value threshold, we also examined linkage disequilibrium, imputation quality, and imputation type. We provide a variety of evaluation metrics. Results suggest that P-value threshold had the greatest impact on GRS quality for the outcome of coronary heart disease, with an optimal threshold around 0.001. However, GRSs are relatively robust to both linkage disequilibrium and imputation quality. We also show that the optimal GRS partially depends on the evaluation metric and consequently the way one intends to use the GRS. Overall the implications highlight both the robustness of GRS and a means to empirically choose the best set of GRSs.

  View details for DOI 10.1002/gepi.21912

  View details for Web of Science ID 000360008100005

• Direct Estimates of the Genomic Contributions to Blood Pressure Heritability within a Population-Based Cohort (ARIC) PLOS ONE Salfati, E., Morrison, A. C., Boerwinkle, E., Chakravarti, A. 2015; 10 (7)

  Abstract

  Blood pressure (BP) is a heritable trait with multiple environmental and genetic contributions, with current heritability estimates from twin and family studies being ~ 40%. Here, we use genome-wide polymorphism data from the Atherosclerosis Risk in Communities (ARIC) study to estimate BP heritability from genomic relatedness among cohort members. We utilized data on 6,365,596 and 9,578,528 genotyped and imputed common single nucleotide polymorphisms (SNPs), in 8,901 European ancestry (EA) and 2,860 African Ancestry (AA) ARIC participants, respectively, and a mixed linear model for analyses, to make four observations. First, for BP measurements, the heritability is ~20%/~50% and ~27%/~39% for systolic (SBP)/diastolic (DBP) blood pressure in European and African ancestry individuals, respectively, consistent with prior studies. Second, common variants with allele frequency >10% recapitulate most of the BP heritability in these data. Third, the vast majority of BP heritability varies by chromosome, depending on its length, and is largely concentrated in noncoding genomic regions annotated as DNaseI hypersensitive sites (DHSs). Fourth, the majority of this heritability arises from loci not harboring currently known cardiovascular and renal genes. Recent meta-analyses of large-scale genome-wide association studies (GWASs) and admixture mapping have identified ~50 loci associated with BP and hypertension (HTN), and yet they account for only a small fraction (~2%) of the heritability.

  View details for DOI 10.1371/journal.pone.0133031

  View details for PubMedID 26162070

• Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci PLOS GENETICS Sazonova, O., Zhao, Y., Nuernberg, S., Miller, C., Pjanic, M., Castano, V. G., Kim, J. B., Salfati, E. L., Kundaje, A. B., Bejerano, G., Assimes, T., Yang, X., Quertermous, T. 2015; 11 (5)

  Abstract

  To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including "growth factor binding," "matrix interaction," and "smooth muscle contraction." We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low P-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology.

  View details for DOI 10.1371/journal.pgen.1005202

  View details for Web of Science ID 000355305200022

  View details for PubMedID 26020271

• Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci. PLoS genetics Sazonova, O., Zhao, Y., Nürnberg, S., Miller, C., Pjanic, M., Castano, V. G., Kim, J. B., Salfati, E. L., Kundaje, A. B., Bejerano, G., Assimes, T., Yang, X., Quertermous, T. 2015; 11 (5)

  Abstract

  To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including "growth factor binding," "matrix interaction," and "smooth muscle contraction." We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low P-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology.

  View details for DOI 10.1371/journal.pgen.1005202

  View details for PubMedID 26020271

• Corrigendum: Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example. Frontiers in genetics Goldstein, B. A., Knowles, J. W., Salfati, E., Ioannidis, J. P., Assimes, T. L. 2015; 6: 231-?

  Abstract

  [This corrects the article on p. 254 in vol. 5, PMID: 25136350.].

  View details for DOI 10.3389/fgene.2015.00231

  View details for PubMedID 26217377

• Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example FRONTIERS IN GENETICS Goldstein, B. A., Knowles, J. W., Salfati, E., Ioannidis, J. P., Assimes, T. L. 2014; 5

  Abstract

  Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers.We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD) in the Atherosclerosis Risk in Communities (ARIC) cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration.The addition of a GRS to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC. RESULTS are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor single nucleotide polymorphisms (SNPs) are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider.The proposed method facilitates the standardized incorporation of a GRS in risk assessment.

  View details for DOI 10.3389/fgene.2014.00254

  View details for Web of Science ID 000347445200001

• Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example. Frontiers in genetics Goldstein, B. A., Knowles, J. W., Salfati, E., Ioannidis, J. P., Assimes, T. L. 2014; 5: 254-?

  Abstract

  Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers.We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD) in the Atherosclerosis Risk in Communities (ARIC) cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration.The addition of a GRS to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC. RESULTS are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor single nucleotide polymorphisms (SNPs) are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider.The proposed method facilitates the standardized incorporation of a GRS in risk assessment.

  View details for DOI 10.3389/fgene.2014.00254

  View details for PubMedID 25136350