Large-Scale Association Analysis Identifies 13 New Susceptibility Loci for Coronary Artery Disease

HomeCirculation: Cardiovascular GeneticsVol. 4, No. 3Large-Scale Association Analysis Identifies 13 New Susceptibility Loci for Coronary Artery Disease Free AccessResearch ArticlePDF/EPUBAboutView PDFSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessResearch ArticlePDF/EPUBLarge-Scale Association Analysis Identifies 13 New Susceptibility Loci for Coronary Artery Disease Nehal N. Mehta Nehal N. MehtaNehal N. Mehta From the Cardiovascular Institute, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA. Search for more papers by this author Originally published1 Jun 2011https://doi.org/10.1161/CIRCGENETICS.111.960443Circulation: Cardiovascular Genetics. 2011;4:327–329The CARDIoGRAM Consortium. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nature Genetics. 2011;43:333–338.Study HypothesisRecently, genome-wide association studies (GWAS) have identified several common variants that are associated with risk of coronary artery disease (CAD) and myocardial infarction (MI). The authors state that the current loci discovered in CAD and MI GWAS explain only a small fraction of the heritability of this complex disease. The authors hypothesized that a larger study would provide more power to discover common variants with modest effect sizes. Therefore, they formed the Coronary ARtery DIsease Genome-wide Replication And Meta-analysis (CARDIoGRAM) consortium, which consisted of data from 14 GWAS of CAD and MI.1How Was the Hypothesis Tested?The authors performed a meta-analysis of 14 GWAS of CAD comprising 22 233 cases and 64 762 control subjects, all of European ancestry. CAD was defined angiographically in a subset (n=7364) and by history in the entire sample. Presence of MI ranged from 48.1% to 100% of each cohort. After the meta-analysis, they genotyped the lead single-nucleotide polymorphisms (SNPs) within the most promising (defined a priori as P<5×10−6) previously unidentified loci as well as a subset of previously reported CAD loci in up to 56 682 additional subjects (approximately half cases and half control subjects). Taking the number of loci into consideration, their replication study had >90% power to detect effect sizes observed in the GWAS meta-analysis. Finally, to understand potential mechanisms and intermediate pathways by which novel loci may mediate risk, the authors interrogated 3 genome-wide studies that also assessed gene expression in multiple tissues, using human cell lines, a genome-wide map of allelic expression imbalance, and other human disease traits.Principal FindingsThe analysis of approximately 135 000 individuals more than doubled the number of loci with CAD association, yielding 13 previously unidentified loci and confirming at least 10 previously reported loci. CARDIoGRAM also found that very few of the established and new loci appear to act through traditional risk factors. In fact, the majority of these loci reside in gene regions not previously thought to be involved in the pathogenesis of CAD. Finally, a substantial proportion of the CAD risk variants were also strongly associated with various other human disease traits in GWAS demonstrating a potential pleotropic effect of these gene regions.Ten of the 12 loci (PCSK9 and SHB3 did not achieve genome-wide significance on initial meta-analysis) previously associated with CAD at a genome-wide significance level surpassed the same threshold of significance in CARDIoGRAM in their initial meta-analysis (SORT1, MIA3, WDR12, MRAS, PHACTR1, LPA, 9p21, CXCL12, LDLR, MRPS6). Of note, at least 4 of these loci are related to low-density lipoprotein (LDL) cholesterol. Next, after meta-analysis, they selected 23 new loci with a significance level of P<5×10−6 for follow-up genotyping. Of these 23 loci, 13 replicated, using the a priori definition of a validated locus (showing independent replication after Bonferroni correction and achieving P<5×10−8 in the combined discovery and replication data). These 13 loci (PPAP2B, ANKS1A, TCF21, ZC3HC1, ABO, CYP17A1/CNNM2/NT5C2, ZNF259/APOA5–A4-C3–A1, COL4A1/COL4A2, HHIPL1, ADAMTS7, SMG6/SRR, RASD1/SMCR3/PEMT, and UBE2Z/GIP/ATP5G1/SNF8) had risk allele frequencies ranging from 0.13 to 0.91and moderate effect sizes, with odds ratios ranging from 1.06 to 1.17, demonstrating the power of their study. Interestingly, given that the consortium had access to angiography, they performed various subgroup analyses starting with age of onset of CAD as well as ascertainment of CAD, which yielded the following findings: (1) 20 of 22 loci with P<5×10−8 (known and new loci combined; for 1 locus, age subgroups were not available) had higher odds ratios for early-onset than for late-onset CAD (P=1.2×10−4 for observed versus expected); (2) the odds ratios for most individual SNPs tended to be slightly greater for cases with angiographically proven CAD than for cases with unknown angiographic status (P=0.019 for observed versus expected); and (3) analyses in male and female subjects revealed no sex-specific effects for any risk alleles (P=0.4 for observed versus expected).Next, to better understand the biology of these novel loci, the authors examined whether novel risk alleles were associated with traditional CAD risk factors, were coding variants, had functional significance, or were associated with other human disease traits. They found that 3 of the risk alleles on chromosome 11q23.3 (rs964184, ZNF259, APOA5-APOA4-APOC3-APOA1 gene region) were associated with increased LDL cholesterol and decreased high-density lipoprotein cholesterol, that the risk allele on chromosome 9q34.2 (rs579459, ABO) was associated with increased LDL and total cholesterol, and that variant rs12413409 on chromosome 10q24.32, representing the CYP17A1-CNNM2-NT5C2 gene region, was associated with hypertension.Furthermore, the lead SNP at 4 of the 13 new loci were either nonsynonymous coding variants or were in high linkage disequilibrium (LD) with such SNPs. Variants at 7q32.2 (rs11556924) and 15q25.1 (rs3825807) encoded changes in ZC3HC1 (p.Arg363His) and ADAMTS7 (p.Ser214Pro), respectively, whereas the lead SNP at 14q32.2 (rs2895811) was in strong LD (r2=0.82) with the p.Val691Ala variant in HHIPL1. Last, the lead SNP at 17q21.32 (rs46522) is in strong LD (r2=0.94) with 2 potential functional variants in GIP: p.Ser103Gly (rs2291725) and a variant influencing the splice site of intron 3 (rs2291726), leading to a truncated transcript.In terms of expression, 3 of the new CAD risk variants showed convincing association with regional gene expression (cis effect) by either representing the most significant expressed SNP in the region or by being in high LD (r2≥0.85) with the strongest expressed SNP in the region: rs12190287 at 6q23.2 (TCF21), rs12936587 at 17p11.2 (RASD1, SMCR3, and PEMT), and rs46522 at 17q21.32 (UBE2Z). They also interrogated new loci in a genome-wide map of allelic expression imbalance that provided further support for the expression quantitative trait locus findings at the 17q21.32 locus, which yielded strong evidence for cis effects for the 17p13.3 locus lead SNP (rs216172) on the expression of SMG6.Finally, the authors identified 5 new loci [9q34 (ABO), 10q24 (CYP17A1), 11q23 (ZNF259/APO A5–A4-C3–A1), 15q25 (ADAMTS7), and 17p13 (SMG6, SRR)] where the CAD risk variant was fully or strongly correlated (r2>0.8) with variants that have previously been associated with many other traits or diseases ranging from expected traits such as LDL cholesterol, high-density lipoprotein cholesterol, triglycerides to aneurysms, soluble levels of adhesion molecules, coagulation factor VIII, and von Willebrand factor (at P<5×10−8), demonstrating that a subset of the new CAD risk loci appear to have pleiotropic effects.The authors state that their study focused on common risk variants, and, by assuming a heritability of 40% for CAD, the lead SNPs of previously established loci combined with the loci discovered in their study explain approximately 10% of the additive genetic variance of CAD, suggesting that many other common susceptibility variants of similar or lower effects and/or rare variants contribute to the risk of CAD.ImplicationsThis study represents how larger sample sizes can potentially reveal common susceptibility variants with small effect sizes in complex traits. Furthermore, this study is noteworthy in that it also demonstrates the importance of multiple parallel approaches to dissect the potential biological relevance of newly discovered loci in CAD. The authors used availability of risk factor endophenotypes, gene expression, and human disease traits to understand potential pathways and cell lines involved in the relationship between these loci and CAD to place the discovery of these loci in context. Finally, the authors demonstrate the importance of disease ascertainment to avoid potential misclassification of a measured outcome (in this case, angiographic CAD compared with CAD by history). Their analysis, restricted to angiographically proven CAD, showed stronger findings compared with analyzing CAD in those with a reported history. This also suggests that loci may differentially behave, depending on the definition and background phenotype of CAD.Although the post hoc subgroup analysis in CARDIoGRAM suggested this nuance of a differential effect of novel loci on CAD, depending on the definition of phenotype, CARDIoGRAM was not designed to answer this question. This distinction of the phenotypic heterogeneity of CAD was recently demonstrated in a carefully designed study of CAD and MI in approximately 12 000 individuals,2 in which the authors found differential associations in those with angiographic CAD versus control subjects (ADAMTS7; P=4.98×10−13) compared with those with angiographic CAD who had MI versus those with angiographic CAD but no MI (ABO locus; P=7.62×10−9). These results, which complement findings from the CARDIoGRAM study, indicate that specific genetic predispositions may promote the development of coronary atherosclerosis, whereas others lead to MI in the presence of coronary atherosclerosis. We hope that more carefully designed studies such as this will improve understanding as to where novel loci fit into the spectrum of atherosclerosis and MI. These future studies should strive to improve phenotyping of CAD in large-scale studies as well as to use resequencing data to facilitate discovery of novel loci, which will continue to redefine the disease process of atherosclerosis and eventually inform novel therapeutic targeting.Sources of FundingDr Mehta is supported by National Institutes of Health (NIH) research grant NHLBI K23 HL97151-2.DisclosuresNone.FootnotesCorrespondence to Nehal N. Mehta, MD, MSCE, 6 Penn Tower, One Convention Center Blvd, Philadelphia, PA 19104. E-mail nehal.mehta@uphs.upenn.eduReferences1. Schunkert H, Konig IR, Kathiresan S, Reilly MP, Assimes TL, Holm H, Preuss M, Stewart AF, Barbalic M, Gieger C, Absher D, Aherrahrou Z, Allayee H, Altshuler D, Anand SS, Andersen K, Anderson JL, Ardissino D, Ball SG, Balmforth AJ, Barnes TA, Becker DM, Becker LC, Berger K, Bis JC, Boekholdt SM, Boerwinkle E, Braund PS, Brown MJ, Burnett MS, Buysschaert I, Carlquist JF, Chen L, Cichon S, Codd V, Davies RW, Dedoussis G, Dehghan A, Demissie S, Devaney JM, Diemert P, Do R, Doering A, Eifert S, Mokhtari NE, Ellis SG, Elosua R, Engert JC, Epstein SE, de Faire U, Fischer M, Folsom AR, Freyer J, Gigante B, Girelli D, Gretarsdottir S, Gudnason V, Gulcher JR, Halperin E, Hammond N, Hazen SL, Hofman A, Horne BD, Illig T, Iribarren C, Jones GT, Jukema JW, Kaiser MA, Kaplan LM, Kastelein JJ, Khaw KT, Knowles JW, Kolovou G, Kong A, Laaksonen R, Lambrechts D, Leander K, Lettre G, Li M, Lieb W, Loley C, Lotery AJ, Mannucci PM, Maouche S, Martinelli N, McKeown PP, Meisinger C, Meitinger T, Melander O, Merlini PA, Mooser V, Morgan T, Muhleisen TW, Muhlestein JB, Munzel T, Musunuru K, Nahrstaedt J, Nelson CP, Nothen MM, Olivieri O, Patel RS, Patterson CC, Peters A, Peyvandi F, Qu L, Quyyumi AA, Rader DJ, Rallidis LS, Rice C, Rosendaal FR, Rubin D, Salomaa V, Sampietro ML, Sandhu MS, Schadt E, Schafer A, Schillert A, Schreiber S, Schrezenmeir J, Schwartz SM, Siscovick DS, Sivananthan M, Sivapalaratnam S, Smith A, Smith TB, Snoep JD, Soranzo N, Spertus JA, Stark K, Stirrups K, Stoll M, Tang WH, Tennstedt S, Thorgeirsson G, Thorleifsson G, Tomaszewski M, Uitterlinden AG, van Rij AM, Voight BF, Wareham NJ, Wells GA, Wichmann HE, Wild PS, Willenborg C, Witteman JC, Wright BJ, Ye S, Zeller T, Ziegler A, Cambien F, Goodall AH, Cupples LA, Quertermous T, Marz W, Hengstenberg C, Blankenberg S, Ouwehand WH, Hall AS, Deloukas P, Thompson JR, Stefansson K, Roberts R, Thorsteinsdottir U, O'Donnell CJ, McPherson R, Erdmann J, Samani NJ. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet. 2011; 43:333–338.CrossrefMedlineGoogle Scholar2. Reilly MP, Li M, He J, Ferguson JF, Stylianou IM, Mehta NN, Burnett MS, Devaney JM, Knouff CW, Thompson JR, Horne BD, Stewart AF, Assimes TL, Wild PS, Allayee H, Nitschke PL, Patel RS, Martinelli N, Girelli D, Quyyumi AA, Anderson JL, Erdmann J, Hall AS, Schunkert H, Quertermous T, Blankenberg S, Hazen SL, Roberts R, Kathiresan S, Samani NJ, Epstein SE, Rader DJ. Identification of ADAMTS7 as a novel locus for coronary atherosclerosis and association of ABO with myocardial infarction in the presence of coronary atherosclerosis: two genome-wide association studies. Lancet. 2011; 377:383–392. CrossrefMedlineGoogle Scholar eLetters(0) eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate. Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page. Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetailsCited By Chen S, Loguercio S, Chen K, Lee S, Park J, Liu S, Sadaei H and Torkamani A (2023) Artificial Intelligence for Risk Assessment on Primary Prevention of Coronary Artery Disease, Current Cardiovascular Risk Reports, 10.1007/s12170-023-00731-4 Tomasoni M, Beyeler M, Vela S, Mounier N, Porcu E, Corre T, Krefl D, Button A, Abouzeid H, Lazaros K, Bochud M, Schlingemann R, Bergin C and Bergmann S (2023) Genome-wide Association Studies of Retinal Vessel Tortuosity Identify Numerous Novel Loci Revealing Genes and Pathways Associated With Ocular and Cardiometabolic Diseases, Ophthalmology Science, 10.1016/j.xops.2023.100288, 3:3, (100288), Online publication date: 1-Sep-2023. Tzveova R, Yaneva-Sirakova T, Naydenova G, Vandeva S, Pendicheva-Duhlenska D, Atanasov P, Mitev V and Kaneva R (2023) Polymorphic Variant rs11206510 in PCSK9 and Risk of Coronary Artery Disease in Bulgarians, Acta Medica Bulgarica, 10.2478/amb-2023-0003, 50:1, (19-26), Online publication date: 1-Apr-2023., Online publication date: 1-Apr-2023. Formicola D, Lasorsa V, Cantalupo S, Testori A, Cardinale A, Avitabile M, Diskin S, Iolascon A and Capasso M (2023) CFDP1 is a neuroblastoma susceptibility gene that regulates transcription factors of the noradrenergic cell identity, Human Genetics and Genomics Advances, 10.1016/j.xhgg.2022.100158, 4:1, (100158), Online publication date: 1-Jan-2023. Zhou G, Chen T and Zhao H (2023) SDPRX: A statistical method for cross-population prediction of complex traits, The American Journal of Human Genetics, 10.1016/j.ajhg.2022.11.007, 110:1, (13-22), Online publication date: 1-Jan-2023. Yaneva-Sirakova T, Kaneva R, Tzveova R, Bozhilova R, Popov I, Shumkova M, Hristova I and Vassilev D (2023) The Role of Certain Polymorphic Variants in Genes, Previously Associated with Blood Pressure Values, with Reference to the Risk of Development of Coronary Artery Disease, Acta Medica Bulgarica, 10.2478/amb-2022-0034, 49:4, (5-11), Online publication date: 1-Dec-2022., Online publication date: 1-Dec-2022. Barinda A, Arozal W and Yuasa S (2022) A review of pathobiological mechanisms and potential application of medicinal plants for vascular aging: focus on endothelial cell senescence, Medical Journal of Indonesia, 10.13181/mji.rev.226064, 31:2, (132-40) Kniazkova P and Viktoriia Yu. Harbuzova V (2022) ANALYSIS OF THE ASSOCIATION OF RS4977574-POLYMORPHIC VARIANTS OF THE ANRIL GENE WITH THE DEVELOPMENT OF ACUTE CORONARY SYNDROME IN INDIVIDUALS WITH DIFFERENT BODY MASS INDEX IN THE UKRAINIAN POPULATION, Eastern Ukrainian Medical Journal, 10.21272/eumj.2022;10(2):147-154, 10:2, (147-154), . Jiao H, Zhang M, Zhang Y, Wang Y and Li W (2021) Pathway Association Studies Reveal Gene Loci and Pathway Networks that Associated With Plasma Cystatin C Levels, Frontiers in Genetics, 10.3389/fgene.2021.711155, 12 Usova E, Alieva A, Yakovlev A, Alieva M, Prokhorikhin A, Konradi A, Shlyakhto E, Magni P, Catapano A and Baragetti A (2021) Integrative Analysis of Multi-Omics and Genetic Approaches—A New Level in Atherosclerotic Cardiovascular Risk Prediction, Biomolecules, 10.3390/biom11111597, 11:11, (1597) Zhou G, Zhao H and Speed D (2021) A fast and robust Bayesian nonparametric method for prediction of complex traits using summary statistics, PLOS Genetics, 10.1371/journal.pgen.1009697, 17:7, (e1009697) Bronić A, Ferenčak G, Bernat R, Leniček-Krleža J, Dumić J and Dabelić S (2021) Association of fibrinogen and plasmin inhibitor, but not coagulation factor XIII gene polymorphisms with coronary artery disease, Journal of Medical Biochemistry, 10.5937/jomb0-26839, 40:2, (138-149), . Shashkova T, Gorev D, Pakhomov E, Shadrina A, Sharapov S, Tsepilov Y, Karssen L and Aulchenko Y (2020) The GWAS-MAP platform for aggregation of results of genome-wide association studies and the GWAS-MAP|homo database of 70 billion genetic associations of human traits, Vavilov Journal of Genetics and Breeding, 10.18699/VJ20.686, 24:8, (876-884) AL-Eitan L, Elsaqa B, Almasri A, Aman H, Khasawneh R and Alghamdi M (2020) Influence of PSRC1, CELSR2, and SORT1 Gene Polymorphisms on the Variability of Warfarin Dosage and Susceptibility to Cardiovascular Disease, Pharmacogenomics and Personalized Medicine, 10.2147/PGPM.S274246, Volume 13, (619-632) Younes S, Shi Z and Zayed H (2020) Genetic variations associated with coronary artery disease and myocardial infarction in the Arab world: a systematic review and meta-analysis, Highlights in BioScience, 10.36462/H.BioSci.20213 Shafidelpour S, Foroughmand A, Zakerkish M and Pourmahdi Borujeni M (2019) Association study of the rs46522 polymorphism in UBE2Z and rs7903146 polymorphism in TCF7L2 gene with T2DM in Arab population of Khuzestan province: case-control study, Medical Journal of Tabriz University of Medical Sciences and Health Services, 10.34172/mj.2020.007, 41:6, (59-66) Song Y, Ma R and Zhang H (2019) The influence of MRAS gene variants on ischemic stroke and serum lipid levels in Chinese Han population, Medicine, 10.1097/MD.0000000000018065, 98:48, (e18065) Jia X, Yang Y, Chen Y, Xia Z, Zhang W, Feng Y, Li Y, Tan J, Xu C, Zhang Q, Deng H and Shi X (2019) Multivariate analysis of genome-wide data to identify potential pleiotropic genes for type 2 diabetes, obesity and coronary artery disease using MetaCCA, International Journal of Cardiology, 10.1016/j.ijcard.2018.10.102, 283, (144-150), Online publication date: 1-May-2019. Holdt L and Teupser D (2018) Long Noncoding RNA ANRIL: Lnc-ing Genetic Variation at the Chromosome 9p21 Locus to Molecular Mechanisms of Atherosclerosis, Frontiers in Cardiovascular Medicine, 10.3389/fcvm.2018.00145, 5 Makkar H, Reynolds M, Wadhawan A, Dagdag A, Merchant A and Postolache T (2018) Periodontal, metabolic, and cardiovascular disease: Exploring the role of inflammation and mental health, Pteridines, 10.1515/pteridines-2018-0013, 29:1, (124-163), Online publication date: 1-Nov-2018., Online publication date: 1-Nov-2018. Di J, Dai M and Zhang Z (2018) ENPP1 K121Q (rs1044498 C > A) genetic polymorphism confers a high risk of susceptibility to coronary heart disease, Medicine, 10.1097/MD.0000000000011236, 97:27, (e11236), Online publication date: 1-Jul-2018. Li H, Cai Y and Xu A (2017) Association study of polymorphisms in the ABO gene and their gene‐gene interactions with ischemic stroke in Chinese population , Journal of Clinical Laboratory Analysis, 10.1002/jcla.22329, 32:4, Online publication date: 1-May-2018. Ma X, Huang J, Lu D, Gu N, Lu R, Zhang J, Zhang H, Li J, Zhang J and Guo X (2018) Genetic Variability of the Glucose-Dependent Insulinotropic Peptide Gene Is Involved in the Premature Coronary Artery Disease in a Chinese Population with Type 2 Diabetes, Journal of Diabetes Research, 10.1155/2018/6820294, 2018, (1-7), Online publication date: 25-Mar-2018. Chen J, Li J, Zhao S, Wang D, Zhang W and Liang W (2017) Clinical significance of costimulatory molecules CD40/CD40L and CD134/CD134L in coronary heart disease, Medicine, 10.1097/MD.0000000000007634, 96:32, (e7634), Online publication date: 1-Aug-2017. Shahid S, Shabana , Cooper J, Beaney K, Li K, Rehman A and Humphries S (2017) Genetic risk analysis of coronary artery disease in Pakistani subjects using a genetic risk score of 21 variants, Atherosclerosis, 10.1016/j.atherosclerosis.2017.01.024, 258, (1-7), Online publication date: 1-Mar-2017. Jiang W and Yu W (2016) Power estimation and sample size determination for replication studies of genome-wide association studies, BMC Genomics, 10.1186/s12864-015-2296-4, 17:S1 Dai C, Xie X, Yang Y, Li X, Zheng Y, Fu Z, Liu F, Chen B, Gai M and Ma Y (2015) Relationship between CYP17A1 genetic polymorphism and coronary artery disease in a Chinese Han population, Lipids in Health and Disease, 10.1186/s12944-015-0007-4, 14:1, Online publication date: 1-Dec-2015. Yang W, Petit T, Thijs L, Zhang Z, Jacobs L, Hara A, Wei F, Salvi E, Citterio L, Delli Carpini S, Gu Y, Knez J, Cauwenberghs N, Barcella M, Barlassina C, Manunta P, Coppiello G, Aranguren X, Kuznetsova T, Cusi D, Verhamme P, Luttun A and Staessen J (2015) Coronary risk in relation to genetic variation in MEOX2 and TCF15 in a Flemish population, BMC Genetics, 10.1186/s12863-015-0272-2, 16:1, Online publication date: 1-Dec-2015. Jian K, Wang Q, Jiang L, Guo Z, Jiang N, Wang L and Liu J (2015) WITHDRAWN: Association between interleukin 8 −251 A/T and +781 C/T polymorphisms and coronary artery disease risk, Human Immunology, 10.1016/j.humimm.2015.09.052, Online publication date: 1-Sep-2015. Szpakowicz A, Kiliszek M, Pepinski W, Waszkiewicz E, Franaszczyk M, Skawronska M, Ploski R, Niemcunowicz-Janica A, Burzynska B, Tulacz D, Maciejak A, Kaminski M, Opolski G, Musial W, Kaminski K and Ahrens I (2015) The rs12526453 Polymorphism in an Intron of the PHACTR1 Gene and Its Association with 5-Year Mortality of Patients with Myocardial Infarction, PLOS ONE, 10.1371/journal.pone.0129820, 10:6, (e0129820) Dai C, Xie X, Ma Y, Yang Y, Li X, Fu Z, Liu F, Chen B and Gai M (2015) Haplotype analyses of CYP17A1 genetic polymorphisms and coronary artery disease in a Uygur population, Journal of the Renin-Angiotensin-Aldosterone System, 10.1177/1470320314565840, 16:2, (389-398), Online publication date: 1-Jun-2015. Cui F, Li K, Li Y, Zhang X and An C (2014) Apolipoprotein C3 genetic polymorphisms are associated with lipids and coronary artery disease in a Chinese population, Lipids in Health and Disease, 10.1186/1476-511X-13-170, 13:1, Online publication date: 1-Dec-2014. Dubé J and Hegele R (2017) The application of gene therapy in lipid disorders: where are we now?, Clinical Lipidology, 10.2217/clp.12.42, 7:4, (419-429), Online publication date: 1-Aug-2012. June 2011Vol 4, Issue 3 Advertisement Article Information Metrics © 2011 American Heart Association, Inc.https://doi.org/10.1161/CIRCGENETICS.111.960443 Manuscript receivedApril 25, 2011Manuscript acceptedApril 28, 2011Originally publishedJune 1, 2011 PDF download Advertisement Subjects Genetics Omics