Categories
Nevin Manimala Statistics

Analysis of the time-course change of acute-phase energy metabolism in critically ill patients using untargeted metabolomics

Clin Nutr. 2025 Oct 24;55:3-10. doi: 10.1016/j.clnu.2025.10.005. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Critically ill patients are believed to experience a dynamic progression of energy metabolism according to the severity and phase of the illness. Although optimizing nutrition and physical therapy to the metabolic profile is recommended for better outcomes, the mechanisms for disease-related metabolic changes remain unclear. This study aimed to elucidate key metabolites and pathways associated with time-course metabolic changes and clinical parameters in acute-phase critically ill patients using untargeted metabolomics.

METHODS: We conducted a single-center prospective case series study on critically ill adults expected to require mechanical ventilation for at least 7 days in our intensive care unit. Data collection was started within 48 h of ICU admission, and daily serum samples from day 1 to day 7 were collected. Untargeted metabolomics was performed using liquid chromatography/mass spectrometry. Statistical analyses included principal component analysis, (orthogonal) partial least squares discriminant analysis, and pathway analysis.

RESULTS: Ten patients were analyzed during the study period from July 2021 to September 2022. A total of 123 metabolites were annotated by untargeted metabolomics, with significant time-course changes in galactonic acid, ornithine, and l-arginine. Pathway analysis indicated alterations in the arginine biosynthesis pathway. A subgroup analysis showed distinct metabolic profiles for sepsis and non-sepsis patients, with creatine phosphate, uric acid, and creatinine being significant markers. In sepsis patients, metabolic changes strongly correlated with the sequential organ failure assessment (SOFA) score.

CONCLUSION: Using untargeted metabolomics, we annotated several metabolites and metabolic pathways strongly associated with time-course changes in the metabolic profile. In addition, it is suggested that nutritional therapy can be optimized according to specific pathophysiology.

PMID:41176813 | DOI:10.1016/j.clnu.2025.10.005

By Nevin Manimala

Portfolio Website for Nevin Manimala