Immunometabolic reprogramming and glycolysis-associated signatures in sepsis: insights from single-cell RNA sequencing and machine learning.

BACKGROUND

Immunometabolic remodeling is central to sepsis, yet robust glycolysis-associated biomarkers and their cell-type context remain unclear.

METHODS

We integrated peripheral blood scRNA-seq (GSE175453) and a whole-blood microarray cohort (GSE100159). Glycolysis activity was scored by AUCell (HALLMARK_GLYCOLYSIS), hub genes were prioritized by LASSO/random forest/Boruta, communication was inferred by ligand-receptor analysis, and qRT-PCR was performed in CLP vs control mice.

RESULTS

Sepsis showed myeloid predominance and increased glycolysis scores, most evident in monocytes and plasma cells. Five candidates (GLRX, MDH1, MDH2, TGFBI, COPB2) displayed good discriminatory performance in bulk data; TGFBI was monocyte-enriched and centrally positioned in a dense communication network with B cells/plasma cells/neutrophils. qRT-PCR confirmed a significant between-group difference for TGFBI in the CLP model.

CONCLUSIONS

These findings link enhanced glycolysis-associated programs to a monocyte-centered TGFBI communication pattern and prioritize TGFBI as a candidate biomarker for further validation in sepsis.