A large-scale multi-ethnic genome-wide association study of coronary artery disease

Assimes, Themistocles L.; Tcheandjieu, Catherine; Zhu, Xiang; Hilliard, Austin; Clarke, Sue; Napolioni, Valerio; Ma, Shuping; Fang, Huaying; Gorman, Bryan R.; Lee, Kyung Min; Chen, Fei; Pyarajan, Saiju; Song, Rebecca J; Plomondon, Mary E.; Maddox, Thomas M.; Waldo, Stephen W.; Sinnott-Armstrong, Nasa; Ho, Yuk‐Lam; Wojcik, Genevieve L.; Buyske, Steven; Kooperberg, Charles; Haessler, Jeffrey; Loos, Ruth J. F.; Do, Ron; Verbanck, Marie; Chaudhary, Kumardeep; North, Kari; Avery, Christy L.; Haiman, Christopher; Marchand, Loı̈c Le; Wilkens, Lynne R.; Bis, J; Leonard, Hampton; Shen, Botong; Lange, Leslie A.; Giri, Ayush; Lu, Yingchang; Dikilitas, Ozan; Kullo, Iftikhar J.; Stanaway, Ian B.; Jarvik, Gail P.; Gordon, Adam J.; Hebbring, Scott J.; Namjou, Bahram; Kaufman, Kenneth M.; Koyama, Satoshi; Ito, Kei; Ishigaki, Kazuyoshi; Kamatani, Yoichiro; Tsao, Noah; Verma, Shefali S.; Ritchie, Marylyn D.; Kember, Rachel; Baras, Aris; Lotta, Luca A.; Natarajan, Pradeep; Levin, Michael; Hauser, E. R.; Miller, Donald R.; Vujkovic, Marijana; Huffman, Jennifer E.; Raghavan, Sridharan; Klarin, Derek; Lee, Jennifer; Voight, Benjamin F.; Rader, Daniel J.; Chang, Kyong–Mi; Damrauer, Scott M.; Lynch, Julie; Wilson, Peter W.F.; Tang, Hua; Sun, Yan; Tsao, Phil; O’Donnell, Christopher J; Kathiresan, Sekar; Saleheen, Danish; Gaziano, J. Michael; Reaven, Peter D.; Cho, Kelly; Bick, Alexander; Graff, Mariaelisa; Huang, Jie

doi:10.21203/rs.3.rs-275591/v1

Cited by 11 publications

(11 citation statements)

References 55 publications

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“…This shortcoming remains a barrier to more broadly studying polygenic risk for CAD in diverse populations. With recent efforts to improve representation in CAD GWAS, 7 we hope that future PRS research will expand to address this limitation. A second limitation of this work is that our methods do not allow for causal inference.…”

Section: Discussionmentioning

confidence: 99%

“…One approach to assessing the impact of polygenic risk for CAD has been to measure associations between a CAD PRS and biobank-derived phenotypes. 6,7 A primary advantage of this approach is the large number of participants in such biobanks. However, a limitation of this method is lack of precision for some outcomes, particularly those inferred from electronic health records.…”

Section: Introductionmentioning

confidence: 99%

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Broad Clinical Manifestations of Polygenic Risk for Coronary Artery Disease in the Women’s Health Initiative

Clarke

Parham

Shadyab

et al. 2021

Preprint

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Background: The genetic basis for coronary artery disease (CAD) risk is highly complex. Genome-wide polygenic risk scores (PRS) can help to quantify that risk, but the broader impacts of polygenic risk for CAD are not well characterized. Methods: We measured polygenic risk for CAD using the metaGRS, a previously validated genome-wide PRS, in a subset of genotyped participants from the Women′s Health Initiative (WHI) and applied a phenome-wide association study framework to assess associations between the PRS and broad range of blood biomarkers, clinical measurements, and outcomes. Results: Polygenic risk for CAD was associated with a variety of biomarkers, clinical measurements, behaviors, and diagnoses related to traditional risk factors, as well as risk-enhancing factors such as elevated lipoprotein(a), increased central adiposity, earlier age of menopause, and rheumatoid arthritis. Analysis of adjudicated outcomes showed a graded association between atherosclerosis related outcomes, with the highest odds ratios being observed for the most severe manifestations of CAD. Higher polygenic risk for CAD was also associated with decreased risk for any incident cancer, breast cancer, and invasive breast cancer but a younger age of death. Conclusion: Polygenic risk for CAD has broad clinical manifestations, reflected in biomarkers, clinical measurements, behaviors, and diagnoses. Some of these associations may represent direct pathways between genetic risk and CAD while others may reflect pleiotropic effects independent of CAD risk.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Broad Clinical Manifestations of Polygenic Risk for Coronary Artery Disease in the Women’s Health Initiative

Clarke

Parham

Shadyab

et al. 2021

Preprint

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“…Among these, PCSK9 is a well-documented drug target, not only for lipids but also for cardiovascular events 58-60 . In comparison to published studies 61 , others find a non-significant increased risk for T2D 62 and an arguably stronger protective effect for CAD 63 , for PCSK9 variant carriers. Our observation is consistent with the lack of excess T2D risk observed in PCSK9 inhibitor clinical trials 58-60,64 and with strong protective effects for coronary heart disease 65 .…”

Section: Discussionmentioning

confidence: 59%

“…The GWAS meta-analysis results of CAD and T2D were acquired from MVP 63 and DIAGRAM Consortium 62 , respectively. For variant rs1229984, the CAD result is from CARDIoGRAM Plus C4D meta-analysis 99 , as it was not present in the MVP results.…”

Section: Methodsmentioning

confidence: 99%

Implicating genes, pleiotropy and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Kanoni

Graham

Wang

et al. 2021

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Genetic variants within nearly 1,000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N=1,654,960) of blood lipids to prioritize putative causal genes for 2,286 lipid associations by combining six gene prediction methods and assigning a confidence score. We assign, most confidently, 118 candidate causal genes and identify potential drug targets including bona-fide (PCSK9) and putative (PNLIP and ARF6) genes. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically-predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Taken together, our findings provide insights into the mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

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“…Genome-wide association studies (GWAS) have identified a large number of genetic loci associated with coronary heart disease 42 – 44 , ASCVD 45 - 47 , HF 48 , 49 , and their risk factors, such as BMI 50 , 51 , blood lipids 52 , 53 , blood pressure 54 – 57 , and T2DM 58 ; however, these genetic variations explain only a small portion of risk in populations 59 , 60 . Joint genetic-environmental effects may be a key mechanism responsible for unexplained CVD risk.…”

Section: Genetic Basis Of Atherosclerotic Cardiovascular Disease and Heart Failurementioning

confidence: 99%

Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light?

et al. 2021

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Cardiovascular disease (CVD) is the leading cause of mortality in South Asia, with rapidly increasing prevalence of hypertension, type 2 diabetes (T2DM) and hyperlipidemia over the last two decades. Atherosclerotic CVD (ASCVD) affects South Asians earlier in life and at lower body weights, which is not fully explained by differential burden of conventional risk factors. Heart failure (HF) is a complex clinical syndrome of heterogeneous structural phenotypes including two major clinical subtypes, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF). The prevalence of HF in South Asians is also rising with other metabolic diseases, and HFpEF develops at younger age and leaner body mass index in South Asians than in Whites. Recent genome-wide association studies, epigenome-wide association studies and metabolomic studies of ASCVD and HF have identified genes, metabolites and pathways associated with CVD traits. However, these findings were mostly driven by samples of European ancestry, which may not accurately represent the CVD risk at the molecular level, and the unique risk profile of CVD in South Asians. Such bias, while formulating hypothesis-driven research studies, risks missing important causal or predictive factors unique to South Asians. Importantly, a longitudinal design of multi-omic markers can capture the life-course risk and natural history related to CVD, and partially disentangle putative causal relationship between risk factors, multi-omic markers and subclinical and clinical ASCVD and HF. In conclusion, combining high-resolution untargeted metabolomics with epigenomics of rigorous, longitudinal design will provide comprehensive unbiased molecular characterization of subclinical and clinical CVD among South Asians. A thorough understanding of CVD-associated metabolomic profiles, together with advances in epigenomics and genomics, will lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health.

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A large-scale multi-ethnic genome-wide association study of coronary artery disease

Cited by 11 publications

References 55 publications

Broad Clinical Manifestations of Polygenic Risk for Coronary Artery Disease in the Women’s Health Initiative

Broad Clinical Manifestations of Polygenic Risk for Coronary Artery Disease in the Women’s Health Initiative

Implicating genes, pleiotropy and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light?

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