{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T10:26:37Z","timestamp":1767176797357,"version":"build-2238731810"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1013191","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000}}],"reference-count":45,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T00:00:00Z","timestamp":1750896000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institute of Health","award":["R01 HG012735"],"award-info":[{"award-number":["R01 HG012735"]}]},{"name":"National Institute of Health","award":["R01 GM134005"],"award-info":[{"award-number":["R01 GM134005"]}]},{"name":"National Institute of Health","award":["R01 HL127564"],"award-info":[{"award-number":["R01 HL127564"]}]},{"name":"National Institute of Health","award":["U01 HG011719"],"award-info":[{"award-number":["U01 HG011719"]}]},{"DOI":"10.13039\/100000121","name":"Division of Mathematical Sciences","doi-asserted-by":"publisher","award":["1902903"],"award-info":[{"award-number":["1902903"]}],"id":[{"id":"10.13039\/100000121","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:sec id=\"sec024\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Polygenic risk score (PRS) have proved to offer robust risk prediction for coronary artery disease (CAD). However, the global CAD PRS summarizes the joint effects of all the markers in the genome, masking potential genetic heterogeneity that may be important for disease interpretation and targeted interventions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec025\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using summary-level data, we identified 43 significant CAD-related traits based on genetic correlations, and further classified them into eight pleiotropy clusters based on their biological functions. We then partitioned the genome into 2,353 near-independent regions. Variants in each region were assigned to the trait most genetically similar to CAD, and then were labeled with the corresponding pleiotropy cluster. We grouped variants without labels into a ninth, non-specific cluster. The Pleiotropy Decomposed (PD) PRSs for each of the nine clusters were calculated using variants assigned to each cluster for 407,903 samples of European ancestry from the UK Biobank (UKBB).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec026\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We decomposed the CAD PRS into nine PD-PRSs and further stratified individuals with high CAD-PRS into nine subgroups. Each PD-PRS accounted for a higher proportion of the global CAD-PRS within its corresponding subgroup than in the remaining subjects with high CAD-PRS (e.g., 25.2% (0.07) vs. 10.06% (0.07) for lipids-PD-PRS). Additionally, these subgroups showed distinct clinical features. For example, in the lipids-related subgroup, lipoprotein(a) and LDL-cholesterol levels were 67.5% and 18.3% higher, respectively, compared to the remaining high-risk individuals. Furthermore, significant interactions were observed between blood pressure and BP PD-PRS, and between current smoking and respiratory system PD-PRS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec027\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our findings suggest that PD-PRSs may reveal substantial genetic and phenotypic heterogeneity among individuals with high CAD-PRS. The unique PD-PRS compositions of each individual can highlight the relative importance of different pleiotropic regions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pcbi.1013191","type":"journal-article","created":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T14:00:12Z","timestamp":1750946412000},"page":"e1013191","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6317-7730","authenticated-orcid":true,"given":"Jiaqi","family":"Hu","sequence":"first","affiliation":[]},{"given":"Yixuan","family":"Ye","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2682-4142","authenticated-orcid":true,"given":"Chi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yunfeng","family":"Ruan","sequence":"additional","affiliation":[]},{"given":"Pradeep","family":"Natarajan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1195-9607","authenticated-orcid":true,"given":"Hongyu","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2025,6,26]]},"reference":[{"key":"pcbi.1013191.ref001","volume-title":"Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017","author":"GBD 2017 Disease and Injury Incidence and Prevalence Collaborators","year":"2019"},{"issue":"9","key":"pcbi.1013191.ref002","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1161\/CIRCRESAHA.120.315928","article-title":"Polygenic scores to assess atherosclerotic cardiovascular disease risk: clinical perspectives and basic implications","volume":"126","author":"KG Aragam","year":"2020","journal-title":"Circ Res"},{"key":"pcbi.1013191.ref003","doi-asserted-by":"crossref","unstructured":"Nelson CP, Goel A, Butterworth AS, Kanoni S, Webb TR, Marouli E, et al. 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