The association between lipid metabolism and coronary artery disease: A systematic Mendelian randomization study combined with transcriptome analysis

Coronary artery disease (CAD), a chronic progressive inflammatory cardiovascular disorder and leading global cause of mortality, imposes a substantial worldwide economic burden. Identifying lipid metabolism-related genes linked to CAD is crucial for deepening our understanding of the disease’s pathogenesis and discovering novel therapeutic targets. A total of 700 differentially expressed genes associated with CAD were determined by comparing CAD patients and healthy controls in the GSE250283 dataset. A positive relationship between lipid exposure and CAD was revealed by implementing a 2-sample Mendelian randomization analysis using genome-wide association studies data on lipid metabolism exposures and CAD outcomes. Further Mendelian randomization analysis, employing expression quantitative trait loci data from the identified differentially expressed genes as exposures and intersecting results with the Kyoto Encyclopedia of Genes and Genomes lipid metabolism pathway, identified 19 key genes exhibiting both lipid regulatory characteristics and reliable causal associations with CAD. Finally, 5 biomarker genes (SCP2, TNFAIP8, HMGCR, AGPAT3, and MAPKAPK2) were selected from the key genes by implementing 4 machine learning algorithms, and the developed nomogram incorporating these biomarkers demonstrated superior predictive accuracy for CAD risk stratification. The identification of these 5 genes as causal lipid metabolism biomarkers of CAD offers novel insights with high clinical potential, providing valuable targets for the management and treatment of CAD.