Metabolomic derangements are associated with mortality in critically ill adult patients. Academic Article uri icon

Overview

MeSH

  • Aged
  • Bayes Theorem
  • Biological Markers
  • Community-Acquired Infections
  • Female
  • Humans
  • Male
  • Metabolomics
  • Middle Aged
  • Prognosis
  • Sepsis

MeSH Major

  • Critical Illness
  • Hospital Mortality
  • Intensive Care Units

abstract

  • 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.

publication date

  • 2014

has subject area

  • Aged
  • Bayes Theorem
  • Biological Markers
  • Community-Acquired Infections
  • Critical Illness
  • Female
  • Hospital Mortality
  • Humans
  • Intensive Care Units
  • Male
  • Metabolomics
  • Middle Aged
  • Prognosis
  • Sepsis

Research

keywords

  • Journal Article

Identity

Language

  • eng

PubMed Central ID

  • PMC3907548

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0087538

PubMed ID

  • 24498130

Additional Document Info

start page

  • e87538

volume

  • 9

number

  • 1