Integrative Bioinformatics Approaches to Uncover Hub Genes and Pathways Involved in Cardiovascular Diseases

Cardiovascular diseases (CVD) represent a significant global health challenge resulting from a complex interplay of genetic, environmental, and lifestyle factors. However, the molecular pathways and genetic factors involved in the onset and progression of CVDs remain incompletely understood. Here, we performed an integrative bioinformatic analysis to highlight specific genes and signaling pathways implicated in the pathogenesis of 80 CVDs. Differentially expressed genes (DEGs) were identified through the integrated analysis of microarray and GWAS datasets. Then, hub genes were identified after gene ontology functional annotation analysis and protein-protein internet (PPI) analysis. In addition, pathways were identified through KEGG and gene ontology enrichment analyses. A total of 821 hub genes related to 80 CVDs were identified, including 135 common and frequent CVD-associated genes. TNF, IL6, VEGFA, and TGFB.1 genes were the central core genes expressed in 50% or more of CVDs, confirming that the inflammation is a key pathological feature of CVDs. Analysis of hub genes by KEGG enrichment revealed predominant enrichment in 201 KEGG pathways, of which the AGE-RAGE signaling pathway in diabetic complications was identified as the common key KEGG implicated in 62 CVDs. In addition, the outcomes showed an overrepresentation in pathways categorized under human diseases, particularly in the subcategories of infectious diseases and cancers, which may be common risk factors for CVDs. In conclusion, this powerful approach for in silico fine-mapping of genes and pathways allowed the identification of determinant hubs genes and pathways implicated in the pathogenesis of CVDs which could be employed in developing more targeted and effective interventions for preventing, diagnosing, and treating CVDs. The function of these hub genes in CVDs needs further exploration to elucidate their biological characteristics.