Metabolomic derangements are associated with mortality in critically ill adult patients.
OBJECTIVE
To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults.


BACKGROUND
Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible.


METHODS
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.


RESULTS
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).


CONCLUSIONS
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.
Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America ; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America ; Division of Pulmonary and Critical Care Medicine, Stanford University, Stanford, California, United States of America.
Angela J
AJ
Rogers
Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Michael
M
McGeachie
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Rebecca M
RM
Baron
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Lee
L
Gazourian
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Jeffrey A
JA
Haspel
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America ; Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America.
Kiichi
K
Nakahira
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Laura E
LE
Fredenburgh
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Gary M
GM
Hunninghake
Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America ; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Benjamin A
BA
Raby
Department of Medicine and Anesthesia, University of California San Francisco, San Francisco, California, United States of America.
Michael A
MA
Matthay
Department of Emergency Medicine, Henry Ford Hospital, Detroit, Michigan, United States of America.
Ronny M
RM
Otero
Duke Institute for Genome Sciences and Policy, and Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America.
Vance G
VG
Fowler
Department of Emergency Medicine, Henry Ford Hospital, Detroit, Michigan, United States of America.
Emanuel P
EP
Rivers
Duke Institute for Genome Sciences and Policy, and Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America.
Christopher W
CW
Woods
National Center for Genome Resources, Santa Fe, New Mexico, United States of America.
Stephen
S
Kingsmore
National Center for Genome Resources, Santa Fe, New Mexico, United States of America ; Lovelace Respiratory Research Institute, Santa Fe, New Mexico, United States of America.
Ray J
RJ
Langley
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America ; Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America.
Augustine M K
AM
Choi
D000368:Aged; D001499:Bayes Theorem; D015415:Biomarkers / Q000378:metabolism; D017714:Community-Acquired Infections / Q000378:metabolism / Q000401:mortality; D016638:Critical Illness / Q000401:mortality*; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D055432:Metabolomics / Q000379:methods; D008875:Middle Aged; D011379:Prognosis; D018805:Sepsis / Q000378:metabolism / Q000401:mortality
D015415:Biomarkers