Identification of Biomarkers for Inflammatory Bowel Disease Based on Single-Cell RNA Sequencing Data

Inflammatory bowel disease (IBD) is a chronic gastrointestinal disease that imposes a severe health burden globally. Single-cell RNA sequencing (scRNA-seq) technology helps to elucidate the molecular characteristics and functional states of individual cells, thereby advancing the study of IBD's intricate mechanisms. Most current studies focus on small-scale samples from a few cell subclusters, lacking large-scale, systematic analyses of IBD. By collecting and integrating multiple datasets, large-scale sample datasets were analyzed for cell type identification and reclassification, addressing this gap. In this study, we collected and merged several public IBD-related scRNA-seq datasets, creating a dataset with millions of cells. Using data mining tools and bioinformatics techniques, we have identified Treg cells, Th17 cells, the macrophage C12 subcluster, and the fibroblast C5 subcluster as being significantly associated with IBD. These cell types play crucial roles in inflammation, fibrosis, and immune regulation. Differential gene expression analysis revealed several potential biomarkers, including IL2RA, HSF1, and TNFSF8 in Treg cells; PIM3, RIPK2, and TLR2 in macrophage C12 subcluster; and CDH11, OSMR, and BRD4 in fibroblast C5 subcluster. These biomarkers could serve as potential therapeutic targets, contributing to a deeper understanding and more effective treatment of IBD.