Identification of immunometabolism-associated genes and immune infiltration in sepsis-induced cardiomyopathy using integrated bioinformatics and machine learning approaches.

ABSTRACT: ObjectiveSepsis-induced cardiomyopathy, a life-threatening complication of sepsis, carries a significant mortality risk. Despite its clinical severity, the immunometabolic mechanisms driving its pathogenesis remain poorly understood. This study aimed to identify immunometabolism-associated genes in sepsis-induced cardiomyopathy and analyze immune infiltration.MethodsWe integrated single-cell and bulk RNA sequencing data from septic cohorts, using a multistep bioinformatic approach involving machine learning and weighted gene co-expression network analysis to identify key immunometabolism-associated genes and explore their role in sepsis-induced cardiomyopathy. Key findings were validated using in vitro and in vivo experiments.ResultsWe identified two distinct macrophage subsets (functional

SUBMITTER: Pei C 

PROVIDER: S-EPMC12627361 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature