Current medical science · 2025
Immune Dysregulation and Hub Gene Identification in Non-Pulmonary Sepsis-Induced Acute Lung Injury: Insights from Transcriptomic and Experimental Analyses.
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Yan Chen, Li Wen, Cai Yang-Ming, Cai Wei-Yi, Hu Nian-Dan, Song Yang-Yi-Yan, Li Wen-Qiang, Sun Zhou, Geng Qing
Аннотация
OBJECTIVE: Sepsis-induced acute lung injury (ALI) poses a critical challenge in critical care, yet its immunoregulatory mechanisms remain poorly defined. This study aimed to delineate immune dysregulation networks and identify therapeutic targets through multiomics data integration.
METHODS: Transcriptomic datasets (GSE40180 and GSE165226) were analyzed through a multiphase bioinformatics workflow, including gene set enrichment analysis (GSEA), immune cell deconvolution (CIBERSORT), differential gene expression profiling (|log2FC|> 1.5, P.adj < 0.05), and pathway annotation (GO/KEGG). Protein-protein interaction (PPI) networks were constructed to identify hub genes. Experimental validation was done using a murine cecal ligation and puncture (CLP) model with histopathological lung injury scoring and RT-qPCR-based hub gene verification.
RESULTS: Integrated analysis revealed 26 consensus biological processes (24 upregulated, 2 downregulated) dominated by innate immune activation. CIBERSORT revealed significant infiltration of M1 macrophages, neutrophils, activated dendritic cells (DCs), and activated natural killer (NK) cells in septic lungs, which was concurrent with Th17/naive CD8+ T-cell dysregulation. Among the 58 differentially expressed genes (DEG), 7 hub genes (Cxcl1, Cxcl2, Ccl3, Cd14, Saa3, Timp1, and Socs3) were significantly correlated with immune cell dynamics. CLP modeling confirmed severe alveolar damage (lung injury score: 8.11 ± 1.17 vs. 1.97 ± 0.29; P < 0.0001) and upregulated hub gene expression (all P < 0.01) in septic lungs, with hub gene expression levels strongly correlated with the lung injury score (Pearson's r > 0.85, P < 0.001).
CONCLUSION: Innate adaptive immune crosstalk, particularly dysregulated immune cell infiltration, drives sepsis-induced ALI pathogenesis. The 7 hub genes mechanistically connect immune dyshomeostasis to tissue injury, suggesting novel targets for precision immunomodulation and biomarker development in critical care.
METHODS: Transcriptomic datasets (GSE40180 and GSE165226) were analyzed through a multiphase bioinformatics workflow, including gene set enrichment analysis (GSEA), immune cell deconvolution (CIBERSORT), differential gene expression profiling (|log2FC|> 1.5, P.adj < 0.05), and pathway annotation (GO/KEGG). Protein-protein interaction (PPI) networks were constructed to identify hub genes. Experimental validation was done using a murine cecal ligation and puncture (CLP) model with histopathological lung injury scoring and RT-qPCR-based hub gene verification.
RESULTS: Integrated analysis revealed 26 consensus biological processes (24 upregulated, 2 downregulated) dominated by innate immune activation. CIBERSORT revealed significant infiltration of M1 macrophages, neutrophils, activated dendritic cells (DCs), and activated natural killer (NK) cells in septic lungs, which was concurrent with Th17/naive CD8+ T-cell dysregulation. Among the 58 differentially expressed genes (DEG), 7 hub genes (Cxcl1, Cxcl2, Ccl3, Cd14, Saa3, Timp1, and Socs3) were significantly correlated with immune cell dynamics. CLP modeling confirmed severe alveolar damage (lung injury score: 8.11 ± 1.17 vs. 1.97 ± 0.29; P < 0.0001) and upregulated hub gene expression (all P < 0.01) in septic lungs, with hub gene expression levels strongly correlated with the lung injury score (Pearson's r > 0.85, P < 0.001).
CONCLUSION: Innate adaptive immune crosstalk, particularly dysregulated immune cell infiltration, drives sepsis-induced ALI pathogenesis. The 7 hub genes mechanistically connect immune dyshomeostasis to tissue injury, suggesting novel targets for precision immunomodulation and biomarker development in critical care.