Identification and Validation of a Lipid Metabolism-associated Gene Signature for Predicting Survival in Sepsis Patients
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Background
Sepsis is a life-threatening condition associated with high mortality rates, claiming millions of lives globally each year. To improve prognostic prediction in sepsis, this study aimed to establish a lipid metabolism-associated gene signature for risk stratification and immune function evaluation.
Methods
U sing the sepsis dataset GSE65682 (Gene Expression Omnibus, GEO), lipid metabolism-associated genes were identified via GeneCards and intersection analysis. Hub genes selection integrated Univariate Cox, Least Absolute Shrinkage and Selection Operator (LASSO), and Multivariate Cox regression. Patients were stratified into high/low-risk groups by median risk scores. Prognostic performance was validated by Kaplan-Meier analysis and Receiver Operating Characteristic curves (ROC). Immune heterogeneity was analyzed using single-sample Gene Set Enrichment Analysis (ssGSEA), CIBERSORT, and correlation networks.
Results
A 9-gene prognostic signature (Aryl Hydrocarbon Receptor Repressor, AHRR; Ceroid-Lipofuscinosis, Neuronal 8, CLN8; Fatty Acid Synthase, FASN; Lanosterol Synthase, LSS; Mediator Complex Subunit 29, MED29; Platelet-Activating Factor Acetylhydrolase IB Subunit Alpha, PAFAH1B1; Phosphatidylinositol-4-Phosphate 5-Kinase Type 1 Gamma, PIP5K1C; Tribbles Pseudokinase 3, TRIB3; UDP-Glucose Ceramide Glucosyltransferase, UGCG) demonstrated robust predictive value. High-risk patients showed poor survival (KM, p=6.75 × e⁻⁸;ROC AUC: 0.951) and enriched Chemokine Receptor (CCR) and parainflammation, while low-risk individuals exhibited elevated higher infiltration levels of Tumor-infiltrating lymphocytes(TIL), type_II_IFN_Response, Treg, and macrophages . Immune network analyses revealed coordinated interactions: activated NK cells synergized with M1 macrophages (r=0.44) but antagonized resting NK cells (r=-0.62). Immune checkpoints CD86/TNFSF4 were upregulated in low-risk patients, contrasting with CD200R1 suppression.
Conclusion
This study successfully established a lipid metabolism-derived gene signature that provides a clinically actionable tool for prognostic stratification in sepsis patients, helping personalized clinical decision-making and facilitating early interventions.
