Plasma Lipidomic Signatures Reveal Age-Associated Patterns of Septic Shock Risk and Immune Dysregulation in Sepsis

Yuhan Sun¹Ke Lin¹Ling Wang²Jingwen Ai¹Jingjing Zhao¹Ruiwen Sun¹Xiaoyang Cheng¹Yanmin Wan¹Peng Cui¹Sen Wang¹Jing Wu¹Jialin Jin^1*

• ¹Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China
• ²Omicsolution Co., Ltd., 28 Yuanwen Road, Shanghai, 201199, Shanghai, China

Background: Sepsis is associated with significant lipidomic disturbances, but age-associated lipidomic patterns remain poorly characterized. Given the links between aging, immune dysfunction, and metabolic dysregulation, defining age-specific lipid profiles could improve sepsis risk assessment. This study investigates age-stratified lipidomic signatures in sepsis and identifies biomarkers for clinical severity. Methods: We prospectively enrolled 62 sepsis patients (21 <65 years, 41 ≥65 years) and 40 healthy controls. Plasma lipidomics was performed via untargeted LC-MS/MS, identifying 1,277 lipid species across 38 subclasses. Principal component analysis (PCA) and consensus clustering were used to assess lipidomic differences and define patient subtypes. Correlations between lipid subclasses, clinical severity (SOFA scores), and immune cell subsets were analyzed. An age-adjusted risk stratification model was developed to assess septic shock and mortality risk (AUC analysis). Results: Sepsis patients exhibited reduced phosphatidylcholine (PC), cholesteryl ester (CE), and lysophosphatidylcholine (LPC) levels (all P<0.05). Clustering revealed four lipidomic patterns, with Cluster 4 distinguishing two sepsis subtypes (C1, C2). Subtype C2 had higher septic shock incidence (57.1% vs. 14.8%, P=0.0013) and downregulation of 92 lipids, 35 of which strongly correlated with SOFA scores. A risk stratification model incorporating six key lipids (LPC(19:0), PC(P-19:0), SM 32:3;2O(FA 16:3), PC(P-20:0), PC(O-18:1/20:3), CE(15:0)) and age accurately predicted septic shock (AUC: 0.87 training, 0.82 validation) and mortality risk in elderly patients. PC levels correlated with monocytes, while CE and LPC associated with complement proteins and CD8+ T cells. Conclusions: Our lipid-based model effectively predicts septic shock and mortality, particularly in elderly sepsis patients. Age-associated lipid alterations (PC, LPC, CE reduction) correlate with disease severity and immune dysregulation, suggesting distinct lipid-immune mechanisms in younger vs. elderly patients. These findings support lipidomics as a tool for sepsis risk stratification and personalized therapy.