Identification of immune-related lncRNA in sepsis by construction of ceRNA network and integrating bioinformatic analysis

• Published in: BMC genomics Vol. 24; no. 1; pp. 1 - 15
• Main Authors: Wang, Tianfeng, Xu, Si, Zhang, Lei, Yang, Tianjun, Fan, Xiaoqin, Zhu, Chunyan, Wang, Yinzhong, Tong, Fei, Mei, Qing, Pan, Aijun
• Format: Journal Article
• Language: English
• Published: London BioMed Central 24.08.2023; BioMed Central Ltd; Springer Nature B.V; BMC
• Subjects: Algorithms; Animal Genetics and Genomics; Bioinformatics; Biomarker; Biomarkers; Biomedical and Life Sciences; CD4 antigen; Computational biology; Correlation analysis; Gene expression; Genes; Genetic aspects; Genomics; Health aspects; Human immunogenetics; Immune system; Immune-related genes; Immunopathogenesis; Inflammation; Life Sciences; lncRNA; Macrophages; Microarrays; Microbial Genetics and Genomics; MicroRNA; MicroRNAs; miRNA; Modular structures; Multiple organ dysfunction syndrome; Network analysis; Non-coding RNA; Pathogenesis; Plant Genetics and Genomics; Proteomics; Sepsis; Stat4 protein; Therapeutic targets; China; Sepsis; Biomarker; lncRNA; Network analysis; Immune-related genes
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-023-09535-7

Background Sepsis is a high mortality disease which seriously threatens human life and health, for which the pathogenetic mechanism still unclear. There is increasing evidence showed that immune and inflammation responses are key players in the development of sepsis pathology. LncRNAs, which act as ceRNAs, have critical roles in various diseases. However, the regulatory roles of ceRNA in the immunopathogenesis of sepsis have not yet been elucidated. Results In this study, we aimed to identify immune biomarkers associated with sepsis. We first generated a global immune-associated ceRNA (IMCE) network based on data describing interactions pairs of gene–miRNA and miRNA–lncRNA. Afterward, we excavated a dysregulated sepsis immune-associated ceRNA (SPIMC) network from the global IMCE network by means of a multi-step computational approach. Functional enrichment indicated that lncRNAs in SPIMC network have pivotal roles in the immune mechanism underlying sepsis. Subsequently, we identified module and hub genes (CD4 and STAT4) via construction of a sepsis immune-related PPI network. Then, we identified hub genes based on the modular structure of PPI network and generated a ceRNA subnetwork to analyze key lncRNAs associated with sepsis. Finally, 6 lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) that identified as immune biomarkers of sepsis. Moreover, the CIBERSORT algorithm and the infiltration of circulating immune cells types were performed to identify the inflammatory state of sepsis. Correlation analyses between immune cells and sepsis immune biomarkers showed that the LINC00265 was strongly positive correlated with the macrophages M2 (r = 0.77). Conclusion Collectively, these results may suggest that these lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) played important roles in the immune pathogenesis of sepsis and provide potential therapeutic targets for further researches on immune therapy treatment in patients with sepsis.