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Deciphering the role of SEMA4A/MAPK signaling in sepsis: insights from Mendelian randomization, transcriptomic, single-cell sequencing analyses, and vitro experiments

Year: 2025
Type: article
Abstract: Background Sepsis is a condition with high mortality and multiple organ dysfunction, undergoing complex pathogenesis and limited treatment options. This study aims to uncover new therapeutic targets for sepsis Methods Three independent transcriptomic datasets from sepsis patients in the GEO database were utilized. Batch effect correction and differential gene expression analysis were performed to identify differentially expressed genes (DEGs), followed by mendelian randomization (MR) analysis to identify sepsis-related risk genes. The intersection of DEGs and MR risk genes revealed final core sepsis genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to elucidate the functional pathways of core genes. Single-cell RNA sequencing (scRNA-seq) analysis was employed to evaluate gene expression profiles across various cell types in sepsis. In vitro experiments were performed to validate pathways associated with the core genes. Results We identified 307 highly expressed DEGs and 72 disease-related risk genes, culminating in the identification of three core sepsis genes including SEMA4A, LRPAP1, and NTSR1. These genes are involved in biological processes and pathways related to immune responses, such as immune rejection. scRNA-seq data indicated that three core sepsis genes are predominantly expressed in monocytes. In vitro experiments using THP-1 human monocytic cells validated that SEMA4A as well as the MAPK biomarker gene ERK were up-regulated in LPS-induced sepsis cells. Conclusion This study proposes SEMA4A, LRPAP1, and NTSR1 as promising therapeutic targets for sepsis. Particularly, it underscores the crucial role of SEMA4A/MAPK in monocytes in the pathogenesis and progression of sepsis, offering valuable insights for potential treatment strategies.
Authors: Meng-Qin Pei, Yan-Ling Lin, Li-Ming Xu, Yu-Shen Yang, Zhen-Dong Sun, Ya-Fen Zeng, Gui-Dan Wang, He-Fan He, Li-Ying Yu
Language: English
Subfield: Epidemiology
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4412957377
FWCI: 1.246
Cites: 43
Cited by: 2
Related to: 10