Identification of Common Hub Genes in COVID-19 and Comorbidities: Insights into Shared Molecular Pathways and Disease Severity - Suresh Kumar; Jia-Jin Wee; K. J. Senthil Kumar (COVID)
Severe COVID-19 disproportionately impacts patients with comorbidities such as type 1 diabetes (T1D), type 2 diabetes (T2D), obesity (OBCD), cardiovascular disease (CVD), hypertension (HTN), and cerebrovascular disease (CeVD), affecting 10–30% of cases. This study elucidates shared molecular mechanisms by identifying common hub genes and genetic variants across these conditions using an integrative bioinformatics approach. We curated 5463 COVID-19-related genes from DisGeNET, GeneCards, T-HOD, and other databases, comparing them with gene sets for T1D (324 genes), T2D (497), OBCD (835), CVD (1756), HTN (837), and CeVD (1421). Functional similarity analysis via ToppGene, hub gene prediction with cytoHubba, and Cytoscape-based protein–protein interaction networks identified four hub genes—CCL2, IL6, IL10, and TLR4—consistently shared across all conditions (p < 1.0 × 10−5). Enrichr-based gene ontology and KEGG analyses revealed cytokine signaling and inflammation as key drivers of COVID-19 cytokine storms. Polymorphisms like IL6 rs1800795 and TLR4 rs4986790 contribute to immune dysregulation, consistent with previous genomic studies. These genes suggest therapeutic targets, such as tocilizumab for IL6-driven inflammation. While computational, requiring biochemical validation, this study illuminates shared pathways, advancing prospects for precision medicine and multi-omics research in high-risk COVID-19 populations.