Gene co-expression network reveals key hub genes associated with endometriosis using bulk RNA-seq
Hashemi, A.; Ghahramani, N.; Eroglu, S.; Kordlar, E. E.
Show abstract
Endometriosis (EMs) is a complex and prevalent gynecological disorder with a significant genetic component, posing a major clinical challenge in reproductive medicine due to multifactorial inheritance patterns and the involvement of gene-environment interactions in pathophysiology. However, despite extensive research, reliable diagnostic biomarkers for EMs have yet to be identified. We utilized bulk transcriptome sequencing data obtained from the Gene Expression Omnibus to identify hub genes involved in EMs. This study was conducted using a system biology analysis, incorporating differential gene expression, meta-analysis of transcriptomic data, functional enrichment analysis, construction of gene co-expression networks, and comprehensive topological analysis to identify key regulatory genes. Bulk RNA-seq analysis revealed significant differential gene expression between healthy and EMs groups. Overall, 603 and 443 meta-genes were discovered using the Fisher and Invorm P-value combination methods, respectively. A total of 427 meta-genes were subjected to functional enrichment analysis, which revealed significant enrichment in several KEGG pathways related to EMs including "Adherens junction," "p53 signaling pathway," and "AMPK signaling pathway." Additionally, Gene Ontology analysis revealed key processes including "Regulation of Anatomical Structure Morphogenesis," Acetylglucosaminyltransferase Activity" and "Positive Regulation of Intracellular Signal". Co-expression network analysis identified the turquoise module as a critical functional module, within this significant module, the genes IGFBP7, IGFBP3, and NKAP were identified as EMs hub genes based on high connectivity and central roles in the network. The constructed protein-protein interaction network further highlighted STAR, PLCD3, RPAP2, MSI2, MAS1, TBX1, LIPT1, and SVIL, as key genes. These genes represented high centrality within the network, suggesting potential regulatory and functional significance in the molecular mechanisms underlying EMs. Notably, miR-143-3p, miR-340-5p, miR-410-3p, and miR-302b-5p were implicated in EMs-associated regulatory networks. This integrative approach significantly enhances our understanding of the molecular mechanisms underlying EMs and provides a robust foundation for the development of diagnostic biomarkers.
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