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Article

Machine Learning-Driven Prediction of Coronary Artery Disease Risk Based on UK Biobank Plasma Proteomics.

Journal of the American Heart Association - 16 Jun 2026

Huang Yuezhong, Chen Xiaoli, Zhang Hao, Bai Zhanpei, Shen Yifan, Zheng Daishan, Fang Longyu, Song Hongzi, Gao Hebei, Lu Fan, Huang Xiu-Feng

Abstract excerpt

BACKGROUND: Coronary artery disease (CAD) is a leading global cause of mortality, yet the predictive accuracy of conventional risk models is limited. Here, we integrate conventional risk factors, polygenic risk scores, and large-scale proteomics to develop a unified model for enhanced CAD risk prediction. METHODS: Using data from UK Biobank, participants with plasma proteomics and genetic risk data were included...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 42294785
DOI: 10.1161/JAHA.125.047248
PMCID: PMC13323568

Genes

CAD
ACE2
ADGRG2
CDCP1
CXCL17
GDF15
MMP12
NPPB
PGF
REN

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 3 Sept 2026.

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