A synergistic multi-omics approach: causal sepsis drivers identified in activated CD4+ T cells by single-cell RNA sequencing and Mendelian randomization.

BACKGROUND

Sepsis is a life-threatening, heterogeneous syndrome with high mortality. This heterogeneity undermines current "one-size-fits-all" therapies and conventional biomarkers (e.g., PCT) lack prognostic power. A critical need exists to identify patient-specific endotypes and causal-driven therapeutic targets.

METHODS

We employed a synergistic multi-omics strategy to identify causal drivers of sepsis. First, we used single-cell RNA sequencing (scRNA-seq) on peripheral blood mononuclear cells (GSE175453) to identify the most pathologically relevant immune cell subpopulation. Next, we used marker genes from this subset as exposures in a two-sample Mendelian randomization (MR) study, using summary statistics from a large-scale sepsis GWAS (11,643 cases/474,841 controls; ieu-b-4980) and eQTL data (eQTLGen) to validate causal relationships. Findings were explored via in-silico functional-genomics (GSEA, GSVA) and validated via qPCR in a clinical cohort (5 sepsis vs. 5 healthy controls).

RESULTS

scRNA-seq analysis identified activated CD4+ T cells (Act.CD4T) as the cell subset contributing most significantly to sepsis pathogenesis. From 81 Act.CD4T marker genes, MR analysis identified four genes with a significant causal effect on sepsis risk: RPLP0 was identified as a causal risk factor (OR: 1.272; 95% CI: 1.031-1.569), while CD52 (OR: 0.903), RPS15A (OR: 0.954), and RPS18 (OR: 0.908) were identified as causal protective factors (all $p<0.05$). Clinical qPCR validation confirmed that RPLP0 was significantly upregulated in sepsis patients, while CD52, RPS15A, and RPS18 were downregulated. Functional analysis revealed these genes converge on a novel "Metabolism-Proteostasis-Immunity" regulatory axis, where RPLP0 drives a pathogenic program (HIF-1, IL-17, ERS) and RPS15A/RPS18 mediate a protective program (AMPK, mTORC1 inhibition).

CONCLUSION

This study is to integrate scRNA-seq and MR to discover cell-specific causal genes for sepsis. The identified four-gene signature provides potentially robust, causally-validated biomarkers for patient stratification and reveals the "Metabolism-Proteostasis-Immunity" axis as a critical, therapeutically-targetable node in sepsis pathogenesis.