Identification of Key Candidate Genes and Pathways in Preterm Birth by Integrated Bioinformatical Analysis

Abstract

Background: Preterm birth（PTB） is a primary cause of neonatal morbidity and mortality, the pathogenic mechanisms of PTB still remain largely unexplored. In the present study, we aimed to identify potential key genes and pathway associated with PTB by bioinformatics analysis. Methods: The GSE46510 dataset was obtained from GEO database. Differentially expressed genes (DEGs) were identified using the limma package in R software, the functional enrichment analysis was performed, and the protein-protein interaction (PPI) network was constructed by Cytoscape software. The network topology was analyzed using MCODE. Results: A total of 335 DEGs were identified from the dataset. The majority of up-regulated DEGs were significantly enriched in inflammatory response, while down-regulated DEGs were mainly enriched in mitotic nuclear division. The top 5 hub up regulated genes were ITGAM, IL1B, ITGAX, NFKB1, and SOCS3. Pathway analysis indicated enrichment in Cytokine-cytokine receptor interaction, signaling by Interleukins. The top 5 hub down regulated genes were CXCR4, ANAPC10, ANAPC4, UBE2V2, UBA3, Pathway analysis indicated enrichment in Ubiquitin mediated proteolysis, Phosphorylation of the APC/C. Conclusion: Our study indicated genes and pathways in PTB by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of PTB.