Identification of autophagy-related genes and immune cell infiltration characteristics in sepsis via bioinformatic analysis

Journal of Thoracic Disease

article

Chong Di¹  Yingying Du²  Renlingzi Zhang²  Lei Zhang¹  Sheng Wang² 

[1] Department of Critical Care Medicine, Shanghai Tongji Hospital, Tongji University, School of Medicine;Department of Critical Care Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine

关键词: Sepsis;    autophagy;    immune cell infiltration;    bioinformatics analysis;   

DOI  :  10.21037/jtd-23-312

学科分类：呼吸医学

来源: Pioneer Bioscience Publishing Company

【 摘 要 】

Background: Sepsis is a life-threatening disease with a high mortality in the intensive care unit (ICU), and autophagy plays an essential role in the development of sepsis. The purpose of this study was to identify potential autophagy-related genes in sepsis and their relationship with immune cell infiltration by bioinformatics analysis. Methods: The messenger RNA (mRNA) expression profile of the GSE28750 data set was collected from the Gene Expression Omnibus (GEO) database. The potential differentially expressed autophagy-related genes of sepsis were screened with the “limma” package in R (The Foundation for Statistical Computing). The hub genes were selected by weighted gene coexpression network analysis (WGCNA) networks with Cytoscape, and functional enrichment analysis was performed. The expression level and diagnostic value of the hub genes were validated by Wilcoxon test and receiver operating characteristic (ROC) curve analysis of the GSE95233 data set. The compositional patterns of immune cell infiltration in sepsis were estimated using the CIBERSORT algorithm. Spearman rank correlation analysis was used to associate the identified biomarkers with infiltrating immune cells. A competing endogenous (ceRNA) network was constructed to predict related noncoding RNAs of identified biomarkers with the miRWalk platform. Results: In all, 80 differential autophagy-related genes were obtained. GABARAPL2, GAPDH, WDFY3, MAP1LC3B, DRAM1, WIPI1, and ULK3 were identified as hub genes and diagnostic biomarker groups for sepsis. In addition, 7 differentially infiltrated immune cells correlated with the hub autophagy-related genes were identified. The ceRNA network predicted 23 microRNAs and 122 long noncoding RNAs related to 5 hub autophagy-related genes. Conclusions: GABARAPL2, GAPDH, WDFY3, MAP1LC3B, DRAM1, WIPI1, and ULK3 may influence the development of sepsis and have a vital impact on sepsis immune regulation as autophagy-related genes.

【 授权许可】

Unknown