A synergistic multi-omics approach: causal sepsis drivers identified in activated CD4+ T cells by single-cell RNA
Jun Zhou1, Yun Liu1, Qiuyan Hu1
1Department of Emergency, Suzhou Ninth People's Hospital, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou, China.
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.
Insights
This study identifies four causal genes in activated CD4+ T cells that impact sepsis risk. These genes highlight a novel "Metabolism-Proteostasis-Immunity" axis, offering potential biomarkers for sepsis patient stratification and targeted therapies.
Area of Science:
- Genomics
- Immunology
- Systems Biology
Background:
- Sepsis is a life-threatening condition with high mortality, characterized by heterogeneity that challenges current treatments.
- Existing biomarkers for sepsis lack sufficient prognostic power, necessitating the identification of patient-specific endotypes and causal therapeutic targets.
Purpose of the Study:
- To integrate multi-omics data, including single-cell RNA sequencing and Mendelian randomization, to uncover causal drivers of sepsis pathogenesis.
- To identify cell-specific causal genes associated with sepsis risk and explore their functional implications.
Main Methods:
- Utilized single-cell RNA sequencing (scRNA-seq) to pinpoint key immune cell subpopulations involved in sepsis.
- Employed two-sample Mendelian randomization (MR) using GWAS and eQTL data to establish causal relationships between identified marker genes and sepsis risk.
- Validated findings through in-silico functional genomics and clinical qPCR in sepsis patients.
Main Results:
- Activated CD4+ T cells (Act.CD4T) were identified as a critical cell subset in sepsis pathogenesis.
- MR analysis revealed RPLP0 as a risk factor, while CD52, RPS15A, and RPS18 were identified as protective factors for sepsis.
- qPCR confirmed RPLP0 upregulation and CD52, RPS15A, RPS18 downregulation in sepsis patients, converging on a "Metabolism-Proteostasis-Immunity" axis.
Conclusions:
- The study successfully integrated scRNA-seq and MR to discover cell-specific causal genes for sepsis.
- The identified four-gene signature offers potential as robust, causally-validated biomarkers for sepsis patient stratification.
- The "Metabolism-Proteostasis-Immunity" axis represents a critical, therapeutically targetable pathway in sepsis pathogenesis.
