Dataset Information

Discrimination of sepsis stage metabolic profiles with an LC/MS-MS-based metabolomics approach.

ABSTRACT:

Background

To identify metabolic biomarkers that can be used to differentiate sepsis from systemic inflammatory response syndrome (SIRS), assess severity and predict outcomes.

Methods

65 patients were involved in this study, including 35 patients with sepsis, 15 patients with SIRS and 15 normal patients. Small metabolites that were present in patient serum samples were measured by liquid chromatography mass spectrometry techniques and analysed using multivariate statistical methods.

Results

The metabolic profiling of normal patients and patients with SIRS or sepsis was markedly different. A significant decrease in the levels of lactitol dehydrate and S-phenyl-d-cysteine and an increase in the levels of S-(3-methylbutanoyl)-dihydrolipoamide-E and N-nonanoyl glycine were observed in patients with sepsis in comparison to patients with SIRS (p<0.05). Patients with severe sepsis and septic shock displayed lower levels of glyceryl-phosphoryl-ethanolamine, Ne, Ne dimethyllysine, phenylacetamide and d-cysteine (p<0.05) in their sera. The profiles of patients with sepsis 48 h before death illustrated an obvious state of metabolic disorder, such that S-(3-methylbutanoyl)-dihydrolipoamide-E, phosphatidylglycerol (22:2 (13Z, 16Z)/0:0), glycerophosphocholine and S-succinyl glutathione were significantly decreased (p<0.05). The receiver operating characteristic curve of the differential expression of these metabolites was also performed.

Conclusions

The body produces significant evidence of metabolic disorder during SIRS or sepsis. Seven metabolites may potentially be used to diagnose sepsis.

Trial registration number

ClinicalTrial.gov identifier NCT01649440.

SUBMITTER: Su L

PROVIDER: S-EPMC4265126 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Discrimination of sepsis stage metabolic profiles with an LC/MS-MS-based metabolomics approach.

Su Longxiang L Huang Yingyu Y Zhu Ying Y Xia Lei L Wang Rentao R Xiao Kun K Wang Huijuan H Yan Peng P Wen Bo B Cao Lichao L Meng Nan N Luan Hemi H Liu Changting C Li Xin X Xie Lixin L

BMJ open respiratory research 20141210 1

<h4>Background</h4>To identify metabolic biomarkers that can be used to differentiate sepsis from systemic inflammatory response syndrome (SIRS), assess severity and predict outcomes.<h4>Methods</h4>65 patients were involved in this study, including 35 patients with sepsis, 15 patients with SIRS and 15 normal patients. Small metabolites that were present in patient serum samples were measured by liquid chromatography mass spectrometry techniques and analysed using multivariate statistical method ...[more]

PMID: 25553245

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Dataset Information

Discrimination of sepsis stage metabolic profiles with an LC/MS-MS-based metabolomics approach.

Background

Methods

Results

Conclusions

Trial registration number

Publications

Discrimination of sepsis stage metabolic profiles with an LC/MS-MS-based metabolomics approach.

Similar Datasets

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