
A study uncovered several potential biomarkers of ulcerative colitis (UC) that may help better describe the disease’s underlying molecular mechanisms. The findings were published in Frontiers in Immunology.
Researchers used transcriptomic data from intestinal mucosal biopsies that underwent robust rank aggregation analysis to identify 251 up-regulated and 211 down-regulated genes. They then analyzed the genes using weighted gene co-expression network analysis. Machine learning identified UC signature genes, aiding predictive model development, the researchers noted.
The analysis yielded 212 key differentially expressed genes (DEGs). Subsequently, the researchers identified 5 UC signature biomarkers by machine learning based on the key DEGs: THY1, SLC6A14, ECSCR, FAP, and GPR109B. Activation of the IL-17, TNF, and PI3K-Akt signaling pathways in UC was indicated by KEGG and GSVA analyses, which were positively correlated with the signature biomarkers.
“THY1, SLC6A14, ECSCR, FAP, and GPR109B can serve as potential biomarkers of UC and are closely related to signaling pathways associated with UC progression. The discovery of these markers provides valuable information for understanding the molecular mechanisms of UC,” the researchers concluded.