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ABSTRACT: Background
Sepsis is a global health challenge associated with high morbidity and mortality rates. Early diagnosis and treatment are challenging because of the limited understanding of its underlying mechanisms. This study aimed to identify effective biomarkers for diagnosing and treating sepsis through an integrated multi-method approach.Methods
Publicly available single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq datasets were analyzed for naive CD4 + T cell-specific genes. Based on these hub genes, Mendelian randomization (MR) analysis, followed by the MR-Bayesian model averaging (MR-BMA) algorithm, was implemented to explore the causality between these genes and sepsis. In addition, single-cell-type expression analysis, cell-cell communication detection, metabonomi
SUBMITTER: Shang W
PROVIDER: S-EPMC12908785 | biostudies-literature | 2026 Feb
REPOSITORIES: biostudies-literature