Identification and Validation of Hub Genes in Acute Pancreatitis and Hypertriglyceridemia

Abstract

Background The pathogenesis of acute pancreatitis (AP) and the relationship between acute pancreatitis and hypertriglyceridemia are complex and not fully understood. The purpose of this study was to identify the hub genes along with common differentially expressed genes (DEGs) between acute pancreatitis and hypertriglyceridemia. Methods We downloaded three gene expression profiles of AP and one gene expression profile of hypertriglyceridemia from the Gene Expression Omnibus (GEO) database and filtered the DEGs based on the above four datasets. Next, we identified the hub genes by performing the Gene Ontology (GO) term analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein–protein interaction (PPI) construction. We also constructed the miRNA-hub gene network and established mouse models with hypertriglyceridemia and AP using a high-fat diet and injection of caerulein (CAE), respectively. Finally, the immunohistochemical analysis was used to verify the differential expressions of hub genes in AP, hypertriglyceridemia, and normal pancreatic tissue. Results A total of 105 DEGs associated with AP and 149 DEGs associated with hypertriglyceridemia were identified. Additionally, we identified six hub genes of AP, all of which were closely related to the cytoskeleton while two DEGs genes were common in both AP and hypertriglyceridemia. We also verified their expression in mouse models. Finally, a network of miRNA-mRNA was also constructed, and the top seven interactive miRNAs ( hsa-mir-1–3p, hsa-mir-5195–3p, hsa-mir-145–5p, hsa-let-7b-5p, hsa-mir-10b-5p, hsa-mir-206 , and hsa-mir-613 ) targeting the most hub genes were identified. Conclusion Overall, we identified six hub genes associated with AP and two common DEGs associated with AP and hypertriglyceridemia along with seven miRNAs that may regulate AP. This study could provide new ideas for further elucidation of the pathogenesis of hypertriglyceridemia-induced acute pancreatitis in the future.

scGENA: A Single-Cell Gene Coexpression Network Analysis Framework for Clustering Cell Types and Revealing Biological Mechanisms

“…The study of [ 48 ] emphasizes that high inflammatory cytokines might induce the accumulation of unfolded or misfolded proteins, i.e., endoplasmic reticulum stress in diabetic pancreatic islets. In the CC category functional enrichment investigation, Zhang et al, 2022 [ 49 ] discovered that the upregulated differentially expressed genes concerning acute pancreatitis were connected with the cell–substrate junction. On the other hand, chaperones’ adaptive unfolded protein response signaling maintained endoplasmic reticulum protein folding equilibrium in healthy beta cells, according to Yong et al, 2021 [ 50 ].…”

Fabp5 is a common gene between a high-cholesterol diet and acute pancreatitis

“…Zhang et al suggested that AP and hypertriglyceridemia shared common DEGs, WSB1 and FBXO4 (8). Therefore, different studies reported different hub DEGs for AP, which might be due to implementation of different bioinformatic analysis methods (5)(6)(7)(8). In addition, these studies did not evaluate test hub genes as predictive factors of SAP.…”

“…The rapid development of bioinformatics approaches is aiding in gaining a deeper understanding of disease pathobiology at the genetic level and in the development of predictive genetic biomarkers. Numerous studies have explored potential hub differentially expressed genes (DEGs) for acute pancreatitis through bioinformatics analysis (5)(6)(7)(8). Fan et al have suggested that genes EGFR, CDH1, ACTB, CD44, and VCL may play vital role in the pathogenesis of AP (5).…”

“…Zhong et al reported that both gene CDH1 and VCL were core genes in AP (7). Zhang et al suggested that AP and hypertriglyceridemia shared common DEGs, WSB1 and FBXO4 (8). Therefore, different studies reported different hub DEGs for AP, which might be due to implementation of different bioinformatic analysis methods (5)(6)(7)(8).…”

Novel insight on marker genes and pathogenic peripheral neutrophil subtypes in acute pancreatitis

“…Bioinformatic analysis of high-throughput sequencing data plays an important role in medical research. In fact, there are some studies based on bioinformatic analysis in AP (15)(16)(17)(18). However, all of these analyses are based on the identification of differentially expressed genes (DEGs), and this method could result in the omission of large-scale information from unrecognized genes.…”