Objective To identify immune-related genes critical to asthma pathogenesis and construct a clinically applicable diagnostic model based on immune-gene signatures. Methods We first intersected 1639 immune-related genes (IRGs) with differentially expressed genes (DEGs) from the discovery dataset (GSE43696, n=128) to obtain differentially expressed IRGs (DE-IRGs). Expression stability was confirmed in the independent validation dataset GSE64913 (n=62). Least absolute shrinkage and selection operator (LASSO) regression and support-vector-machine (SVM) recursive feature elimination were applied to rank genes, followed by overlap with key modules identified by weighted gene co-expression network analysis (WGCNA). A logistic-regression diagnostic model was constructed using the optimal gene set, and its functional landscape was interrogated by gene-set enrichment analysis (GSEA). Finally, the model and the selected genes were cross-validated in ten transcriptomic cohorts encompassing eight distinct asthma phenotypes (total n=1137) and in lung tissue from an ovalbumin (OVA)-induced murine asthma model. Results A total of 38 DE-IRGs were identified. Among them, cholecystokinin (CCK), cellular retinol binding protein 2 (CRABP2) and C-X-C motif chemokine ligand 6 (CXCL6) were involved in immune-related processes and signaling pathways, which were of great significance in the diagnosis of asthma. The logistic regression diagnostic model based on three genes has shown good universality in various asthma samples. These three genes have also been verified to a certain extent in the lung tissues of OVA mice. Conclusion Integrative bioinformatics and in vivo validation establish CCK, CRABP2, and CXCL6 as a compact, biologically grounded immune-gene signature for asthma diagnosis and mechanistic investigation.
The present paper reports the effect of pancreatitis induced by cholecystokinin (CCK) on free-running rhythm of locomotor activity of the ICR mice, and analyzes the interaction of inflammatory diseases and acute pancreatitis with circadian rhythm system. In the study, the mice were modeled under different phases of acute pancreatitis in DD status (Double Dark，constant dark condition). By comparing of the inflammatory status and the indicators of rhythm before and after modeling of the running wheel activity group and the rest group, it was observed that the rest group showed more possibility of inflammation than the activity group did in ICR mice model of acute pancreatitis. In the rest phase model, the extension of the period is particularly longer. The results presented indicated that CCK-induced acute pancreatitis impacted free activity rhythm of ICR mice. Also in a free running model under different phase, the inflammation severity was proved significantly different. This study provides possible clues for the research of the pathogenesis of acute pancreatitis severe tendency.
