Immune-Related Genes can Serve as Potential Biomarkers for Predicting Severe Acute Pancreatitis

We aimed to investigate immune-related candidate genes for predicting the severity of acute pancreatitis (AP). RNA sequencing profile GSE194331 was downloaded, and differentially expressed genes (DEGs) were investigated. Meanwhile, the infiltration of immune cells in AP were assessed using CIBERSORT. Genes related with the infiltration of immune cells were investigated using weighted gene co-expression network analysis (WGCNA). Furthermore, immune subtypes, micro-environment, and DEGs between immune subtypes were explored. Immune-related genes, protein-protein interaction (PPI) network, and functional enrichment analysis were further performed. Overall, 2533 DEGs between AP and healthy controls were obtained. After trend cluster analysis, 411 upregulated and 604 downregulated genes were identified. Genes involved in two modules were significantly positively related to neutrophils and negatively associated with T cells CD4 memory resting, with correlation coefficient more than 0.7. Then, 39 common immune-related genes were obtained, and 56 GO BP were enriched these genes, including inflammatory response, immune response, and innate immune response; 10 KEGG pathways were enriched, including cytokine-cytokine receptor interaction, Th1 and Th2 cell differentiation, and IL-17 signaling pathway. Genes, including S100A12, MMP9, IL18, S100A8, HCK, S100A9, RETN, OSM, FGR, CAMP, were selected as genes with top 10 degree in PPI, and the expression levels of these genes increased gradually in subjects of healthy, mild, moderately severe, and severe AP. Our findings indicate a central role of immune-related genes in predicting the severity of AP, and the hub genes involved in PPI represent logical candidates for further study.