DUSP6 protein action and related hub genes prevention of sepsis-induced lung injury were screened by WGCNA and Venn

小桶 败血症 基因 急性呼吸窘迫综合征 计算生物学 生物 基因表达 生物信息学 遗传学 免疫学 转录组 医学 内科学
作者
Chao Song,Ling Wang,Fei Zhang,Chuanxin Lv,Min Meng,Wei Wang,Wenxing Zhou
出处
期刊:International Journal of Biological Macromolecules [Elsevier BV]
卷期号:279: 135117-135117 被引量:1
标识
DOI:10.1016/j.ijbiomac.2024.135117
摘要

During a sepsis infection, the lung is extremely susceptible to damage. A condition known as acute respiratory distress syndrome (ARDS) may develop in extreme circumstances. The primary objective of this research is to identify important genes that are related with both sepsis and lung injury. These genes have the potential to act as novel biomarkers in the investigation of sepsis-induced lung injury prevention strategies. It was possible to download from GEO data both the sepsis-related dataset (GSE64457) and the lung injury-related dataset (GSE40839). In the GSE64457 dataset, using the "limma" package in R revealed 429 differentially expressed genes (DEGs) with logFC values more than or equal to -1 and p values <0.05. There were 266 genes that were up-regulated and 163 genes that were down-regulated. Through the use of Gene Ontology (GO), it was discovered that the majority of the DEGs were associated with the inflammatory response (BP terms), a particular granule lumen (CC terms), and protein binding (MF terms). By doing a pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG), researchers were able to identify DEGs that were mostly associated with the NOD-like receptor signalling pathway, the TNF signalling pathway, and Epstein-Barr virus infection. Within the GSE40839 dataset, Weighted Gene Co-Expression Network Analysis (WGCNA) yielded a total of 7 modules, from which it was possible to screen out 2 critical modules and 693 key genes. The important genes and DEGs were both subjected to a Venn analysis. Finally, 14 genes that overlapped (ARL4A, LAIR1, MTHFD2, TSPAN13, DUSP6, PECR, CBS, TES, ASNS, SYNE1, FGF13, LCN2, KLF10, BCAT1) were closely associated to the incidence and development of sepsis-induced lung injury. This indicates that these genes are the essential genes to avoid the occurrence of sepsis-induced lung injury. This study provides novel strategies for preventing lung harm brought on by sepsis.
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