Decomposing polygenic risk of coronary artery disease into distinct biological processes
- 1Chalmers University of Technology
Abstract
Standard polygenic risk scores capture overall genetic liability to coronary artery disease (CAD) but do not reveal the biological processes contributing to risk in an individual. Here, we applied data-driven latent factor decomposition to 526 genome-wide significant CAD-associated variants, using their associations with 78 CAD-related phenotypic traits. We identified eight genetic components corresponding to cholesterol-enriched lipoproteins, triglyceride-rich lipoproteins, lipoprotein(a), metabolically unhealthy normal weight, obesity, endothelial dysfunction, coagulation and cardiac remodeling. Process-specific polygenic risk scores (pPRSs) captured biological profiles beyond those reflected by conventional risk factors. In UK Biobank (n = 458,905), the Swedish CArdioPulmonary bioImage Study (n = 24,904) and Mass General Brigham Biobank (n = 53,848), pPRSs were consistently associated with clinical and subclinical CAD and showed distinct biomarker, proteomic and comorbidity profiles. These findings establish a framework for biologically resolved genetic CAD risk and may inform process-specific approaches to precision prevention.
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BibTeX
@misc{morze2026decomposing,
title = {{Decomposing polygenic risk of coronary artery disease into distinct biological processes}},
author = {J. Morze and K. Smith and M. Kierczak and G. Bergstrom and H. Li and A. Gummesson and T. Fall and S. Soderberg and T. Ebbers and J. G. Smith and R. Landberg and P. Franks and T. Lappalainen and M. Udler and C. Wittenbecher},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.08.26365088},
url = {https://www.medrxiv.org/content/10.64898/2026.10.08.26365088v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Decomposing polygenic risk of coronary artery disease into distinct biological processes
AU - J. Morze
AU - K. Smith
AU - M. Kierczak
AU - G. Bergstrom
AU - H. Li
AU - A. Gummesson
AU - T. Fall
AU - S. Soderberg
AU - T. Ebbers
AU - J. G. Smith
AU - R. Landberg
AU - P. Franks
AU - T. Lappalainen
AU - M. Udler
AU - C. Wittenbecher
PY - 2026
DA - 2026/10/08
PB - medRxiv
DO - 10.64898/2026.10.08.26365088
UR - https://www.medrxiv.org/content/10.64898/2026.10.08.26365088v1
AB - Standard polygenic risk scores capture overall genetic liability to coronary artery disease (CAD) but do not reveal the biological processes contributing to risk in an individual. Here, we applied data-driven latent factor decomposition to 526 genome-wide significant CAD-associated variants, using their associations with 78 CAD-related phenotypic traits. We identified eight genetic components corresponding to cholesterol-enriched lipoproteins, triglyceride-rich lipoproteins, lipoprotein(a), metabolically unhealthy normal weight, obesity, endothelial dysfunction, coagulation and cardiac remodeling. Process-specific polygenic risk scores (pPRSs) captured biological profiles beyond those reflected by conventional risk factors. In UK Biobank (n = 458,905), the Swedish CArdioPulmonary bioImage Study (n = 24,904) and Mass General Brigham Biobank (n = 53,848), pPRSs were consistently associated with clinical and subclinical CAD and showed distinct biomarker, proteomic and comorbidity profiles. These findings establish a framework for biologically resolved genetic CAD risk and may inform process-specific approaches to precision prevention.
ER -