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Updated: Jan 21, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
Published on: March 14, 2013
Metabolomic profiling of patients with sepsis-associated encephalopathy
E D Kessenikh1, K M Bykova1, E A Murashko1
1Almazov National Medical Research Centre, Saint Petersburg, Russia.
Abstract:
Sepsis-associated encephalopathy (SAE) is a condition characterized by acute brain dysfunction developed in the absence of a primary infection in the central nervous system. The aim of this study was to perform a pilot, untargeted metabolomic profiling of the blood plasma of SAE patients to identify metabolic changes potentially associated with the pathological condition and to generate hypotheses for further studies of its pathogenesis, as well as to the search for promising biomarkers, and the assessment of the severity of the patient's condition. Metabolomic profiling was performed using HPLC-HR-MS, followed by statistical analysis of the obtained data. This blinded, randomized, controlled clinical trial revealed significant differences in the metabolic profiles of the study and control groups. Functional analysis showed the metabolic pathways most affected by pathological processes in SAE patients. These included metabolism of acylcarnitines, lysophosphatidylcholines, and taurine, folate biosynthesis, and the drug metabolism involving the cytochrome P450 pathway. In SAE patients with impaired consciousness, including delirium and coma, decreased levels of long-chain acylcarnitines and lysophosphatidylcholines were observed. The metabolomic profiles of SAE patients differed significantly between the groups of deceased and surviving patients: concentrations of sulfur-containing amino acids were significantly lower in the group of deceased than in the group of survivors. Our study identified 64 candidate biomarkers that could potentially be used to predict sepsis outcomes. However, further study is needed using an expanded and independent cohort of patients.
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