Identification of genes and functional coexpression modules closely related to ulcerative colitis by gene datasets analysis

BACKGROUND: Ulcerative colitis is a type of inflammatory bowel disease posing a great threat to the public health worldwide. Previously, gene expression studies of mucosal colonic biopsies have provided some insight into the pathophysiological mechanisms in ulcerative colitis; however, the exact pathogenesis is unclear. The purpose of this study is to identify the most related genes and pathways of UC by bioinformatics, so as to reveal the core of the pathogenesis. METHODS: Genome-wide gene expression datasets involving ulcerative colitis patients were collected from gene expression omnibus database. To identify most close genes, an integrated analysis of gene expression signature was performed by employing robust rank aggregation method. We used weighted gene co-expression network analysis to explore the functional modules involved in ulcerative colitis pathogenesis. Besides, biological process and pathways analysis of co-expression modules were figured out by gene ontology enrichment analysis using Metascape. RESULTS: A total of 328 ulcerative colitis patients and 138 healthy controls were from 14 datasets. The 150 most significant differentially expressed genes are likely to include causative genes of disease, and further studies are needed to demonstrate this. Seven main functional modules were identified, which pathway enrichment analysis indicated were associated with many biological processes. Pathways such as ‘extracellular matrix, immune inflammatory response, cell cycle, material metabolism’ are consistent with the core mechanism of ulcerative colitis. However, ‘defense response to virus’ and ‘herpes simplex infection’ suggest that viral infection is one of the aetiological agents. Besides, ‘Signaling by Receptor Tyrosine Kinases’ and ‘pathway in cancer’ provide new clues for the study of the risk and process of ulcerative colitis cancerization.