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Updated: Sep 14, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Novel Susceptibility Genes for Sepsis Revealed by a Cross-Tissue Transcriptome-Wide Association Study
Linfeng Tao1, Ning Zhu1, Yue Zhu2
1Gusu School of Nanjing Medical University, Department of Critical Care Medicine and Emergency, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou Clinical Medical Center of Critical Care Medicine, Suzhou, China.
Background:
Sepsis, a life-threatening syndrome triggered by a dysregulated host response to infection, continues to impose a substantial global health burden. Advances in genomics and transcriptomics now enable systematic exploration of sepsis pathogenesis at the genetic level. The integration of genome-wide association studies and transcriptome-wide association studies (TWAS) offers a powerful framework to identify causal genetic variants and delineate molecular mechanisms underlying sepsis susceptibility and clinical outcomes.
Methods:
A cross-tissue TWAS was implemented using UTMOST to integrate sepsis genome-wide association studies summary statistics with transcriptomic data from the Genotype-Tissue Expression version 8 (GTEx v8) project. Candidate genes were validated through complementary approaches: FUSION, FOCUS, and MAGMA. Tissue-specific and pathway enrichment analyses were applied to prioritize sepsis-associated genes and characterize their functional roles in disease-relevant biological processes. Bayesian colocalization and two-sample Mendelian randomization (MR) analyses were employed to infer putative causal relationships between prioritized genes and sepsis risk.
Results:
Four genes-ZCCHC4, PDGFB, C18orf54, and ATG4B-demonstrated significant associations with sepsis susceptibility in cross-tissue analyses. Two-sample MR provided evidence for causal effects of genetically regulated expression of these genes on sepsis risk. Bayesian colocalization identified shared causal variants between sepsis-associated loci and expression quantitative trait loci (eQTLs), implicating dysregulation of inflammatory and autophagy pathways in sepsis pathogenesis.
Conclusions:
Our results highlight the efficacy of cross-tissue TWAS in mapping sepsis-associated loci and elucidating the genetic architecture underlying sepsis susceptibility. These prioritized loci constitute compelling targets for functional validation and represent actionable candidates for therapeutic intervention in sepsis.
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