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Combining Genomics With Lipid and Inflammatory Biomarkers to Predict Coronary Artery Disease Risk UK Biobank Study

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dc.contributor.authorFarah, Raysha-
dc.contributor.authorKim, Min Seo-
dc.contributor.authorTruong, Buu-
dc.contributor.authorSui, Yang-
dc.contributor.authorCho, So Mi Jemma-
dc.contributor.authorUrbut, Sarah Margaret-
dc.contributor.authorPatel, Aniruddh-
dc.contributor.authorRidker, Paul M.-
dc.contributor.authorNatarajan, Pradeep-
dc.contributor.authorFahed, Akl C.-
dc.date.accessioned2026-07-16T00:16:11Z-
dc.date.available2026-07-16T00:16:11Z-
dc.date.created2026-06-30-
dc.date.issued2026-05-
dc.identifier.issn0735-1097-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/213064-
dc.description.abstractBACKGROUND Coronary artery disease (CAD) polygenic risk score (PRS), low-density-lipoprotein cholesterol (LDL-C), lipoprotein(a) (Lp(a)), and high-sensitivity C-reactive protein (hsCRP) are biomarkers that predict CAD. It is unclear whether integrating genomics with lipid and inflammatory biomarkers could complement traditional risk scores in identifying people at risk of CAD. OBJECTIVES This study assesses the predictive value of CAD PRS, LDL-C, Lp(a), and hsCRP for incident CAD across different age and sex groups. METHODS Participants (n = 215,695) from the UK Biobank aged 40 to 69 years with baseline CAD PRS, LDL-C, Lp(a), and hsCRP values were followed for 12 years to assess the incidence of CAD. We evaluated a multivariable-adjusted Cox model that included all 4 biomarkers, net reclassification index, C-statistics, and population attributable risk across different age and sex groups. RESULTS Over a 12-year follow-up, 4,721 men and 2,425 women developed CAD. The HRs for incident CAD associated with each biomarker elevation were 1.79 (95% CI: 1.70-1.89) for CAD PRS, 1.60 (95% CI: 1.48-1.66) for LDL-C, 1.20 (95% CI: 1.12-1.29) for Lp(a), and 1.64 (95% CI: 1.57-1.72) for hsCRP. CAD PRS demonstrated a stronger association in men (HR per SD: 1.49; 95% CI: 1.45-1.54) than women (HR per SD: 1.37; 95% CI: 1.31-1.44; P-interaction < 0.001). All biomarkers conferred greater HRs at younger ages (P < 0.0001). Individuals with all biomarkers elevated had a 4.65-fold increased risk of CAD compared with those with no elevated biomarkers. A combined 4-biomarker model had a higher C-statistic of 0.753 compared with the pooled cohort equations (C-statistic of 0.740). The C-statistic of the combined 4-biomarker model was also higher in younger individuals in both sexes and yielded a 32.0% continuous net reclassification index when compared with the pooled cohort equations. CONCLUSIONS CAD PRS, LDL-C, hsCRP, and Lp(a) show independent age-and sex-specific associations with CAD. Measuring all 4 biomarkers may improve midlife CAD risk prediction for both male and female patients.-
dc.languageEnglish-
dc.publisherElsevier Biomedical-
dc.relation.isPartOfJACC-JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY-
dc.relation.isPartOfJOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY-
dc.subject.MESHAdult-
dc.subject.MESHAged-
dc.subject.MESHBiological Specimen Banks-
dc.subject.MESHBiomarkers / blood-
dc.subject.MESHC-Reactive Protein* / analysis-
dc.subject.MESHC-Reactive Protein* / metabolism-
dc.subject.MESHCholesterol, LDL* / blood-
dc.subject.MESHCoronary Artery Disease* / blood-
dc.subject.MESHCoronary Artery Disease* / diagnosis-
dc.subject.MESHCoronary Artery Disease* / epidemiology-
dc.subject.MESHCoronary Artery Disease* / genetics-
dc.subject.MESHFemale-
dc.subject.MESHFollow-Up Studies-
dc.subject.MESHGenetic Risk Score-
dc.subject.MESHGenomics* / methods-
dc.subject.MESHHumans-
dc.subject.MESHIncidence-
dc.subject.MESHLipids* / blood-
dc.subject.MESHLipoprotein(a)* / blood-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPredictive Value of Tests-
dc.subject.MESHRisk Assessment-
dc.subject.MESHRisk Factors-
dc.subject.MESHUK Biobank-
dc.subject.MESHUnited Kingdom / epidemiology-
dc.titleCombining Genomics With Lipid and Inflammatory Biomarkers to Predict Coronary Artery Disease Risk UK Biobank Study-
dc.typeArticle-
dc.contributor.googleauthorFarah, Raysha-
dc.contributor.googleauthorKim, Min Seo-
dc.contributor.googleauthorTruong, Buu-
dc.contributor.googleauthorSui, Yang-
dc.contributor.googleauthorCho, So Mi Jemma-
dc.contributor.googleauthorUrbut, Sarah Margaret-
dc.contributor.googleauthorPatel, Aniruddh-
dc.contributor.googleauthorRidker, Paul M.-
dc.contributor.googleauthorNatarajan, Pradeep-
dc.contributor.googleauthorFahed, Akl C.-
dc.identifier.doi10.1016/j.jacc.2026.01.076-
dc.relation.journalcodeJ01770-
dc.identifier.eissn1558-3597-
dc.identifier.pmid41848465-
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S0735109726003281-
dc.subject.keywordatherosclerotic disease-
dc.subject.keywordhigh-sensitivity C-reactive protein-
dc.subject.keywordlipoprotein(a)-
dc.subject.keywordlow-density-lipoprotein cholesterol-
dc.subject.keywordpolygenic risk score-
dc.contributor.affiliatedAuthorCho, So Mi Jemma-
dc.identifier.scopusid2-s2.0-105040557257-
dc.identifier.wosid001783906700001-
dc.citation.volume87-
dc.citation.number20-
dc.citation.startPage2785-
dc.citation.endPage2803-
dc.identifier.bibliographicCitationJACC-JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, Vol.87(20) : 2785-2803, 2026-05-
dc.identifier.rimsid94396-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordAuthoratherosclerotic disease-
dc.subject.keywordAuthorhigh-sensitivity C-reactive protein-
dc.subject.keywordAuthorlipoprotein(a)-
dc.subject.keywordAuthorlow-density-lipoprotein cholesterol-
dc.subject.keywordAuthorpolygenic risk score-
dc.subject.keywordPlusCARDIOVASCULAR RISK-
dc.subject.keywordPlusGENES-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryCardiac & Cardiovascular Systems-
dc.relation.journalResearchAreaCardiovascular System & Cardiology-
Appears in Collections:
1. College of Medicine (의과대학) > Others (기타) > 1. Journal Papers

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