An integrated germline and somatic genomic model for coronary artery disease

Multiple germline and somatic genomic factors are associated with risk of coronary artery disease, but there is no single measure of risk that integrates all information from a DNA sample. To address this gap, we develop an integrated genomic model that includes six germline and somatic genetic drivers for coronary artery disease, including polygenic risk score, genetically-proxied proteomic/metabolomic risk scores, and clonal hematopoiesis of indeterminate potential. We evaluated its predictive power in the UK Biobank (N = 391,536), and validate it using data from the TOPMed program (N = 34,177). The 10-year coronary artery disease risk based on the integrated genomic model profile ranges from 1.1% to 15.5% in the UK Biobank and from 3.8% to 33.0% in TOPMed, with a more pronounced gradient in males than females. The integrated genomic model captures the cumulative effect of multiple genetic drivers, identifying individuals at high risk for coronary artery disease despite lacking any single high-risk genetic factor, as well as individuals at low risk despite carrying known high-risk factors. In middle age, the integrated genomic model augments the performance of the Pooled Cohort Equations, a clinical risk calculator for coronary artery disease. While the integrated genomic model yields only modest incremental predictive value over polygenic risk score at the population level, it identifies approximately 13% of high-risk individuals not detected by polygenic risk score alone.

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Journal
Nature Communications
Published
2026-03-26
DOI
https://doi.org/10.1038/s41467-026-70379-2
Primary Topic
Genetic Associations and Epidemiology
Type
article
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article

An integrated germline and somatic genomic model for coronary artery disease

A Yunga, Ramachandran Srini Vasan, Md Mesbah Uddin, Brian G. Kral et al.
Nature Communications
Genetic Associations and Epidemiology
article

An integrated germline and somatic genomic model for coronary artery disease

A Yunga, Ramachandran Srini Vasan, Md Mesbah Uddin, Brian G. Kral, Jeong H. Yun, Dong Keon Yon, Laurens F. Reeskamp, Lawrence F. Bielak, Zhaoqi Liu, Tingfeng Xu, Rufan Zhang, Tetsushi Nakao, George T. O’Connor, Lisa R. Yanek, Nicholette D. Palmer, Nancy L. Heard-Costa, Satoshi Koyama, Jennifer D. Smith, Pradeep Natarajan, Xiong Yang, Eric Boerwinkle, Kent D. Taylor, Xinyu Zhu, Patricia A. Peyser, Alanna C. Morrison, Susan R. Heckbert, So Mi Jemma Cho, Donald W. Bowden, Russell P. Tracy, Braxton D. Mitchell, Sharon L. R. Kardia, Stacey B. Gabriel, Jerome I. Rotter, Minxian Wang, Laura M. Raffield, Stephen S. Rich, Min Seo Kim, Lewis C. Becker, Bertha Hidalgo, Wendy S. Post, Michael H. Cho, Joanne M. Murabito, Paul S. de Vries, Donna K. Arnett, Alexander P. Reiner, Bruce M. Psaty, Daniel Levy, Ellinor, Patrick, T, Albert V. Smith, Akl C. Fahed, Hong-Hee Won, Charles Kooperberg
article en

Abstract

Multiple germline and somatic genomic factors are associated with risk of coronary artery disease, but there is no single measure of risk that integrates all information from a DNA sample. To address this gap, we develop an integrated genomic model that includes six germline and somatic genetic drivers for coronary artery disease, including polygenic risk score, genetically-proxied proteomic/metabolomic risk scores, and clonal hematopoiesis of indeterminate potential. We evaluated its predictive power in the UK Biobank (N = 391,536), and validate it using data from the TOPMed program (N = 34,177). The 10-year coronary artery disease risk based on the integrated genomic model profile ranges from 1.1% to 15.5% in the UK Biobank and from 3.8% to 33.0% in TOPMed, with a more pronounced gradient in males than females. The integrated genomic model captures the cumulative effect of multiple genetic drivers, identifying individuals at high risk for coronary artery disease despite lacking any single high-risk genetic factor, as well as individuals at low risk despite carrying known high-risk factors. In middle age, the integrated genomic model augments the performance of the Pooled Cohort Equations, a clinical risk calculator for coronary artery disease. While the integrated genomic model yields only modest incremental predictive value over polygenic risk score at the population level, it identifies approximately 13% of high-risk individuals not detected by polygenic risk score alone.

Nature Communications
Broad Institute (US), Boston University (US), University of Vermont (US), University of North Carolina at Chapel Hill (US), University of Maryland, Baltimore (US), Brigham and Women's Hospital (US), Boston Medical Center (US), Harvard University (US), Johns Hopkins University (US), University of South Carolina (US), Chinese Academy of Sciences (CN), University of Washington (US), Samsung (South Korea) (KR), University of Michigan (US), Johns Hopkins Medicine (US), UCLA Medical Center (US), Beijing Institute of Genomics (CN), Samsung Medical Center (KR), University of Alabama at Birmingham (US), Kyung Hee University (KR), Wuhan University (CN), Institute of Vertebrate Paleontology and Paleoanthropology (CN), Massachusetts General Hospital (US), Fred Hutch Cancer Center (US), Hubei Provincial Hospital of Traditional Chinese Medicine (CN), Wuhan Prevention and Treatment Center for Occupational Diseases (CN), OLVG (NL), National Heart, Lung, and Blood Institute (US), Kyung Hee University Medical Center (KR), Sino-Danish Centre for Education and Research (CN), China National Biotechnology (China) (CN), Dana-Farber Cancer Institute (US), Zhongnan Hospital of Wuhan University (CN), Framingham Heart Study (US), Amsterdam University Medical Centers (NL), Center for Systems Biology (US), Harbor–UCLA Medical Center (US), The University of Texas at San Antonio (US), Wake Forest University (US), University of Virginia (US), Sungkyunkwan University (KR), The University of Texas Health Science Center at Houston (US)
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Genetic Associations and Epidemiology
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