Identification of Key Genes and Pathways Associated With Endometriosis by Weighted Gene Co-Expression Network Analysis

Abstract

Background: Endometriosis is a common gynecological disorder with high rates of infertility and pelvic pain. However, its pathogenesis and diagnostic biomarkers remain unclear. This study aimed to elucidate potential hub genes and key pathways associated with endometriosis in ectopic endometrium (EC) and eutopic endometrium (EU). Material and Method: EU and EC-associated microarray datasets were obtained from the gene expression omnibus (GEO) database. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and gene set enrichment analysis were performed to obtain further biological insight into the EU and EC-associated genes. Weighted gene co-expression network analysis (WGCNA) was performed to find clinically significant modules of highly-correlated genes. The hub genes that belong to both weighted gene co-expression network and protein-protein interaction (PPI) network were identified using Venn diagram. Results: We obtained EC and EU-associated microarray datasets GSE7305 and GSE120103. Genes in EC were mainly enriched in the immune response and immune cell trafficking, and genes in EU were mainly enriched in stress response and steroid hormone biosynthesis. PPI networks and weighted gene co-expression networks were constructed. EC-associated blue module, EU-associated magenta module and their function annotations were identified. 12 hub genes in EC and 16 hub genes in EU were recognized and further validated. Conclusion: Our study identified for the first time the hub genes and enrichment pathways in the EC and EU using WGCNA, which may provide a comprehensive understanding of the pathogenesis of endometriosis and have important clinical implications for the treatment and diagnosis of endometriosis. Funding: This work was supported by the National Natural Science Foundation of China [grant number 81671437, 81771558], Natural Science Foundation of Hunan Province [grant number 2020JJ4814], the Fundamental Research Funds for the Central Universities 287 of Central South University [grant number 2020zzts285]. Declaration of Interest: None to declare.