Genetic Insights into Coronary Heart Disease: A Multi-Omic Approach

Background: Coronary heart disease (CHD) is a leading cause of mortality worldwide, with a complex interplay of genetic and environmental factors influencing its development. Genome-wide association studies (GWAS) have identified multiple genetic loci associated with CHD, providing crucial insights into its pathophysiology. However, the full spectrum of genetic contributors and their biological mechanisms remains to be elucidated. Methods: This study integrates GWAS data with functional enrichment, transcriptomic, and metabolomic analyses to identify key genetic determinants of CHD. Variants associated with CHD were retrieved from publicly available datasets and analyzed using bioinformatics tools to explore their biological significance. Pathway enrichment, protein-protein interaction (PPI) networks, and clustering algorithms were employed to delineate functional relationships among candidate genes. Additionally, microRNA (miRNA) interactions were assessed to understand post-transcriptional regulatory mechanisms. Results: Our analysis confirms the strong association of CHD with loci such as 9p21.3 (CDKN2B-AS1), COL4A2, and PHACTR1, emphasizing their roles in vascular remodeling, inflammation, and lipid metabolism. Functional enrichment revealed significant involvement in TGF-beta signaling, extracellular matrix organization, and AGE-RAGE signaling pathways. Furthermore, miRNA analysis highlighted potential regulatory targets such as hsa-miR-147b and hsa-miR-4790-5p, which may modulate disease progression. Conclusion: This study advances our understanding of CHD genetics by integrating multi-omic data to identify key genetic determinants and biological pathways. The findings underscore the potential of precision medicine approaches for early detection and targeted intervention in high-risk individuals.