Deriving consensus sepsis clusters via goal-directed subgroup identification in multi-omics study.
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ABSTRACT: Sepsis, a syndrome of life-threatening organ dysfunction caused by dysregulated host responses to infection, exhibits profound pathobiological heterogeneity, hindering the development of effective therapies. Current subtyping approaches, often reliant on single-omics data or unsupervised clustering, yield poorly reproducible and therapeutically misaligned classifications. Here, we introduce a goal-directed subgroup identification (GD-SI) framework that optimizes patient stratification for differential treatment responses, integrating longitudinal multi-omics data (transcriptomic, proteomic, metabolomic, phenomic) from 1327 subjects across 43 hospitals. While supervised multi-omics integration frameworks (e.g., DIABLO) effectively capture shared biological signals, our approach anchors subg
SUBMITTER: Zhang Z
PROVIDER: S-EPMC12644673 | biostudies-literature | 2025 Nov
REPOSITORIES: biostudies-literature
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