Metabolomic derangements are associated with mortality in critically ill adult patients

To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults. Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible. We performed metabolomic profiling of plasma from 90 ICU subje...

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Published inPloS one Vol. 9; no. 1; p. e87538
Main Authors Rogers, Angela J, McGeachie, Michael, Baron, Rebecca M, Gazourian, Lee, Haspel, Jeffrey A, Nakahira, Kiichi, Fredenburgh, Laura E, Hunninghake, Gary M, Raby, Benjamin A, Matthay, Michael A, Otero, Ronny M, Fowler, Vance G, Rivers, Emanuel P, Woods, Christopher W, Kingsmore, Stephen, Langley, Ray J, Choi, Augustine M K
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 30.01.2014
Public Library of Science (PLoS)
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Summary:To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults. Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible. We performed metabolomic profiling of plasma from 90 ICU subjects enrolled in the BWH Registry of Critical Illness (RoCI). We tested individual metabolites and a Bayesian Network of metabolites for association with 28-day mortality, using logistic regression in R, and the CGBayesNets Package in MATLAB. Both individual metabolites and the network were tested for replication in an independent cohort of 149 adults enrolled in the Community Acquired Pneumonia and Sepsis Outcome Diagnostics (CAPSOD) study. We tested variable metabolites for association with 28-day mortality. In RoCI, nearly one third of metabolites differed among ICU survivors versus those who died by day 28 (N = 57 metabolites, p<.05). Associations with 28-day mortality replicated for 31 of these metabolites (with p<.05) in the CAPSOD population. Replicating metabolites included lipids (N = 14), amino acids or amino acid breakdown products (N = 12), carbohydrates (N = 1), nucleotides (N = 3), and 1 peptide. Among 31 replicated metabolites, 25 were higher in subjects who progressed to die; all 6 metabolites that are lower in those who die are lipids. We used Bayesian modeling to form a metabolomic network of 7 metabolites associated with death (gamma-glutamylphenylalanine, gamma-glutamyltyrosine, 1-arachidonoylGPC(20:4), taurochenodeoxycholate, 3-(4-hydroxyphenyl) lactate, sucrose, kynurenine). This network achieved a 91% AUC predicting 28-day mortality in RoCI, and 74% of the AUC in CAPSOD (p<.001 in both populations). Both individual metabolites and a metabolomic network were associated with 28-day mortality in two independent cohorts. Metabolomic profiling represents a valuable new approach for identifying novel biomarkers in critically ill patients.
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Competing Interests: The CAPSOD trial was supported in part by Pfizer and Roche diagnostics. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.
Conceived and designed the experiments: AJR MM RMB LG KN LF BAR RMO VGF EPR CWW SK RL AMC. Performed the experiments: LG RMB RL AMC. Analyzed the data: AJR MM GMH BAR AMC. Contributed reagents/materials/analysis tools: RL SK AMC. Wrote the paper: AJR MM MAM RMB LG JAH KN GMH SK AMC.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0087538