| Title: | An integrated germline and somatic genomic model for coronary artery disease |
| Journal: | Nature Communications |
| Published: | 26 Mar 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41888514/ |
| DOI: | https://doi.org/10.1038/s41467-026-70379-2 |
Publication 18188
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
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.</p>
52 Authors
- Xiong Yang
- Min Seo Kim
- Xinyu Zhu
- Md Mesbah Uddin
- Tetsushi Nakao
- So Mi Jemma Cho
- Satoshi Koyama
- Tingfeng Xu
- Laurens F. Reeskamp
- Rufan Zhang
- Zhaoqi Liu
- Yunga A
- Paul S. de Vries
- Ramachandran S. Vasan
- Eric Boerwinkle
- Alanna C. Morrison
- Bruce M. Psaty
- Russell P. Tracy
- Susan R. Heckbert
- Michael H. Cho
- Jeong H. Yun
- Nicholette D. Palmer
- Donald W. Bowden
- Joanne M. Murabito
- Daniel Levy
- Nancy L. Heard-Costa
- George T. O'Connor
- Lewis C. Becker
- Brian G. Kral
- Lisa R. Yanek
- Laura M. Raffield
- Bertha Hidalgo
- Jerome I. Rotter
- Stephen S. Rich
- Kent D. Taylor
- Wendy S. Post
- Charles Kooperberg
- Alexander P. Reiner
- Braxton D. Mitchell
- Sharon L. R. Kardia
- Jennifer A. Smith
- Patricia A. Peyser
- Lawrence F. Bielak
- Dong Keon Yon
- Hong-Hee Won
- Donna K. Arnett
- Albert V. Smith
- Stacey B. Gabriel
- Patrick T. Ellinor
- Pradeep Natarajan
- Minxian Wang
- Akl C. Fahed
1 Application
| Application ID | Title |
|---|---|
| 89885 | Genetics of complex diseases, comorbidities, and the disease risk prediction |
Enabling scientific discoveries that improve human health