ArticleFrontiers in immunology2025
Comprehensive analysis of metabolism-related genes in sepsis reveals metabolic-immune heterogeneity and highlights GYG1 as a potential therapeutic target.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Age but not sex modifies lymphoid immune responses in murine sepsis.Research square · 2026Article
- Article
- Case Report: Bevacizumab combined with chemotherapy followed by PARP inhibitor maintenance therapy inFrontiers in medicine · 2026Article
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Authors and funding
11 authors.
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Abstract
Background: Sepsis is a life-threatening syndrome characterized by dysregulated host immune responses, yet the metabolic drivers of immune dysfunction remain poorly understood. Methods: Here we systematically profiled metabolism-related genes (MRGs) in sepsis using bulk transcriptomic data and stratified patients into two subgroups with distinct immune infiltration profiles by MRGs, as assessed by CIBERSORT and single-cell RNA-seq integration. Machine learning identified five hub metabolic genes for constructing a metabolic risk score, whose prognostic relevance was robustly validated in an external cohort. Single cell analyses, cell-cell communication, and cell-type-specific differential expression analyses were performed to dissect the immunological context. Finally, Results: Patients in the high metabolic risk group exhibited a neutrophil-dominant and lymphocyte-suppressed immune landscape, consistent across bulk and single-cell analyses. Among the five hub genes (ALPL, CYP1B1, GYG1, OLAH, VNN1), GYG1 demonstrated the strongest predictive performance and was highly expressed in monocytes, neutrophils, and proliferating myeloid cells. High-risk patients displayed intensified monocyte-dendritic cell interactions and transcriptional programs enriched in neutrophil degranulation pathways. Conclusions: This integrative multi-omics study established a robust immune-metabolic risk score system to predict sepsis patient outcomes and identified GYG1 as a metabolic driver of innate immune hyperactivation. Targeting GYG1 via LNP-siRNA delivery reduces glycogen availability and inflammatory output in myeloid cells, mitigating immune overactivation and improving disease outcomes
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