Purpose: The purpose of our present study was to, for the first time, identify key genes associated with postpartum depression (PPD) and discovery the potential molecular mechanisms of this condition. Methods: First, microarray expression profiles GSE45603 dataset were acquired from the Gene Expression Omnibus (GEO) in National Center for Biotechnology Information (NCBI). The weighted gene co-expression network analysis (WGCNA) was performed to identify the top three modules from differentially expressed genes (DEGs). Furthermore, cross-validated differential gene expression analysis of the top three modules and DEGs was used to identify the hub genes. Gene set enrichment analysis (GSEA) was conducted to identify the potential functions of the hub genes. We conducted a Receiver Operator Characteristic (ROC) curve to verify the diagnostic efficiencies of the hub genes. Lastly, GSE44132 dataset was used to search the association between the methylation profiles of the hub genes and susceptibility to PPD. Results: Altogether, 8979 genes were identified as DEGs for WGCNA analysis. The turquoise, yellow, and green functional modules were the most significant modules related to PPD development after WGCNA analysis. The enrichment analysis results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway demonstrated that hub genes in the three modules were mainly enriched in the neurotrophin signaling pathway, chemokine signaling pathway, Fcγ receptor-mediated phagocytosis, and Mitogen-activated protein kinase (MAPK) signaling pathway. Eight genes (HNRNPA2B1, IL10, RAD51, UBA52, NHP2, RPL13A, FBL, SPI1) were identified as "real" hub genes from cross-validation data of the three modules and DEGs, and possessed diagnostic value in PPD. The GSEA suggested that "OLFACTORY_TRANSDUCTION", "BUTANOATE_METABOLISM", "MELANOMA", "AMINOACYL_TRNA_BIOSYNTHESIS", and "LYSINE_DEGRADATION" were all crucial in the development of PPD. Highly significant differentially methylated positions in the three genes (HNRNPA2B1, RPL13A and UBA52) were identified in the GSE44132. Conclusion: Using WGCNA analysis of GEO data, our present study, for the first time, may contribute to elucidate the pathophysiology of PPD and provide potential diagnostic biomarkers and therapeutic targets for postpartum depression.
Keywords: Postpartum depression; Potential diagnostic biomarkers; WGCNA.
© 2021 The Author(s). Published by BRI.