Integrative computational approach identifies immune‐relevant biomarkers in ulcerative colitis

Ulcerative colitis is a common inflammatory bowel disease with a complex genetic and immune etiology. Immune infiltration plays a vital role in the development of ulcerative colitis. To explore potential biomarkers for ulcerative colitis and analyze characteristics of immune cell infiltration, we used bioinformatic analyses, including machine learning algorithms, cell type deconvolution methods, and pathway enrichment methods. In this study, we identified 216 differentially expressed mRNAs (DEMs), of which 153 were upregulated, and 63 were downregulated genes. DEMs were mainly enriched in infiltrating neutrophils and regulation of leukocyte migration. Moreover, eight candidate biomarkers, DPP10, MST1L, DPP10‐AS1, CEP55, ACSL1, MGP, OLFM4, and SGK1, were identified. Of these candidate biomarkers, MST1L, OLFM4, and DPP10 were then validated in the GSE48958 dataset and were predicted to be strongly correlated with infiltrating immune cells of ulcerative colitis. The underlying mechanism of these key genes in the development of colitis was also predicted by gene set variation analysis. To further validate these biomarkers' expression in ulcerative colitis, we determined mRNA levels of SGK1, CEP55, ACSL1, OLFM4, and DPP10 in lipopolysaccharides (LPS)‐stimulated Raw264.7 cells by quantitative reverse transcription‐polymerase chain reaction. We also examined SGK1, CEP55, ACSL1, OLFM4, DPP10, and MGP expression in the colon tissues of dextran sodium sulfate‐induced colitis mice. Consistent with the predicted computational results, the mRNA levels of these candidate genes were markedly changed in LPS‐stimulated Raw264.7 cells and inflamed colon tissues. Hence, our findings indicated that these critical genes may act as diagnostic biomarkers for ulcerative colitis and that differential immune infiltration cells may help illustrate the progression of ulcerative colitis. In this study, we identified eight critical genes closely related to ulcerative colitis by machine learning algorithms and validated them in GSE48958 and quantitative reverse transcription‐polymerase chain reaction in in vitro bioassays. For these genes, we also analyzed their characteristics of immune cell infiltration and their downstream signaling pathways. Hence, our findings indicated that these genes may act as diagnostic biomarkers for ulcerative colitis.