Critical Care (May 2018)
Metabolic profiles in community-acquired pneumonia: developing assessment tools for disease severity
Abstract
Abstract Background This study aimed to determine whether community-acquired pneumonia (CAP) had a metabolic profile and whether this profile can be used for disease severity assessment. Methods A total of 175 individuals including 119 CAP patients and 56 controls were enrolled and divided into two cohorts. Serum samples from a discovery cohort (n = 102, including 38 non-severe CAP, 30 severe CAP, and 34 age and sex-matched controls) were determined by untargeted ultra-high-performance liquid chromatography with tandem mass spectrometry (LC-MS/MS)-based metabolomics. Selected differential metabolites between CAP patients versus controls, and between the severe CAP group versus non-severe CAP group, were confirmed by targeted mass spectrometry assays in a validation cohort (n = 73, including 32 non-severe CAP, 19 severe CAP and 22 controls). Pearson’s correlation analysis was performed to assess relationships between the identified metabolites and clinical severity of CAP. The area under the curve (AUC), sensitivity and specificity of the metabolites for predicting the severity of CAP were also investigated. Results The metabolic signature was markedly different between CAP patients and controls. Fifteen metabolites were found to be significantly dysregulated in CAP patients, which were mainly mapped to the metabolic pathways of sphingolipid, arginine, pyruvate and inositol phosphate. The alternation trends of five metabolites among the three groups including sphinganine, p-Cresol sulfate, dehydroepiandrosterone sulfate (DHEA-S), lactate and l-arginine in the validation cohort were consistent with those in the discovery cohort. Significantly lower concentrations of sphinganine, p-Cresol sulfate and DHEA-S were observed in CAP patients than in controls (p 65 years (CURB-65), pneumonia severity index (PSI) and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, while DHEA-S inversely correlated with the three scoring systems. Combining lactate, sphinganine and DHEA-S as a metabolite panel for discriminating severe CAP from non-severe CAP exhibited a better AUC of 0.911 (95% confidence interval 0.825–0.998) than CURB-65, PSI and APACHE II scores. Conclusions This study demonstrates that serum metabolomics approaches based on the LC-MS/MS platform can be applied as a tool to reveal metabolic changes during CAP and establish a metabolite signature related to disease severity. Trial registration ClinicalTrials.gov, NCT03093220. Registered retrospectively on 28 March 2017.
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