Trans-omics analyses identify the biochemical network of LPCAT1 associated with coronary artery disease
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ABSTRACT: This study used a trans-omics approach—combining genome-wide SNP analysis and metabolomics—to distinguish coronary artery disease (CAD) patients from high-risk and healthy individuals. It identified declining plasma phospholipids as potential biomarkers, linked key SNPs and genes (notably LPCAT1) to lipid changes, and developed a machine-learning model that accurately predicts CAD (AUC = 0.917). The results highlight the role of phospholipid metabolism and genetic variation in CAD progression.
ORGANISM(S): Homo sapiens
PROVIDER: GSE303414 | GEO | 2025/07/28
REPOSITORIES: GEO
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