Identification and validation of oxidative stress-related genes in sepsis-induced myopathy.

BACKGROUND: Sepsis-induced myopathy (SIM) a complication of sepsis that results in prolonged mechanical ventilation, long-term functional disability, and increased patient mortality. This study was performed to identify potential key oxidative stress-related genes (OS-genes) as biomarkers for the diagnosis of SIM using bioinformatics. METHODS: The GSE13205 was obtained from the Gene Expression Omnibus (GEO) database, including 13 SIM samples and 8 healthy samples, and the differentially expressed genes (DEGs) were identified by limma package in R language. Simultaneously, we searched for the genes related to oxidative stress in the Gene Ontology (GO) database. The intersection of the genes selected from the GO database and the genes from the GSE13205 was considered as OS-genes of SIM, where the differential genes were regarded as OS-DEGs. OS-DEGs were analyzed using GO enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. Hub genes in OS-DEGs were selected based on degree, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. Finally, a miRNA-gene network of diagnostic genes was constructed. RESULTS: A total of 1089 DEGs were screened from the GSE13205, and 453 OS-genes were identified from the GO database. The overlapping DEGs and OS-genes constituted 25 OS-DEGs, including 15 significantly upregulated and 10 significantly downregulated genes. The top 10 hub genes, including CD36, GPX3, NQO1, GSR, TP53, IDH1, BCL2, HMOX1, JAK2, and FOXO1, were screened. Furthermore, 5 diagnostic genes were identified: CD36, GPX3, NQO1, GSR, and TP53. The ROC analysis showed that the respective area under the curves (AUCs) of CD36, GPX3, NQO1, GSR, and TP53 were 0.990, 0.981, 0.971, 0.971, and 0.971, which meant these genes had very high diagnostic values of SIM. Finally, based on these 5 diagnostic genes, we found that miR-124-3p and miR-16-5p may be potential targets for the treatment of SIM. CONCLUSIONS: The results of this study suggest that OS-genes might play an important role in SIM. CD36, GPX3, NQO1, GSR, and TP53 have potential as specific biomarkers for the diagnosis of SIM.

Association Between IL10 Polymorphisms and the Susceptibility to Sepsis: A Meta-Analysis.

Many genetic variations have been identified to associate with sepsis in numerous studies, but the function of these variants in influencing sepsis is a complex process. We make use of mate-analysis and other analytic strategies (eQTL analysis and PPI network) to investigate the effect of interleukin-10 (IL10) on sepsis. Single-nucleotide polymorphisms (SNPs) in IL10 were analyzed in 3011 septic cases and 2976 controls from 22 studies. In results, the IL10-rs1800871 showed a significant association with sepsis in Asians (P < 0.05). Moreover, there is a association between rs1800896 and sepsis in pooled populations and Asians (P < 0.05). However, there is no association between rs1800872 and sepsis in different models. The three polymorphisms were also identified for the regulation of IL10 expression in an eQTL analyze, and the increased IL10 expression was related to the development of sepsis. Furthermore, the IL10 was discovered to associate with the expression of DRD1, TANK, MKL1, and STARD3NL genes in another independent cohort, which are functionally enriched for IRF3 (interferon regulatory factor 3)/IRF7 (interferon regulatory factor 7) and hormone pathways. In conclusion, the study confirmed the association between IL10 polymorphisms (rs1800871, rs1800872, rs1800896) and sepsis, and suggested the role of the variants in inflammatory pathologies.