Metabolomic Derangements Are Associated with Mortality in Critically Ill Adult Patients

Abstract

ObjectiveTo identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults.RationaleComprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible.MethodsWe 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.ResultsWe 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).ConclusionBoth 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.

Integrative “Omic” Analysis of Experimental Bacteremia Identifies a Metabolic Signature That Distinguishes Human Sepsis from Systemic Inflammatory Response Syndromes

“…The Registry of Critical Illness (RoCI) is approved by the Partners Human Research Committee under IRB protocol 2008-P-000495 (14,15).…”

“…We next tested the four-metabolite training model on the RoCI and CAPSOD clinical cohorts, which had similar metabolomic measurements (8,15). Noninfected SIRS and sepsis differentiation of the CAPSOD and RoCI cohorts has been described in detail (8,(11)(12)(13)15). Sepsis included all patients regardless of final outcome (sepsis, severe sepsis, septic shock, and sepsis nonsurvivors).…”

UCP2-induced fatty acid synthase promotes NLRP3 inflammasome activation during sepsis

“…Although inflammatory responses are important for host defense against invading microbes, excessive inflammation in sepsis can cause severe cell and tissue damage and organ dysfunction, leading to death (2). Our recent studies suggest that altered plasma metabolic profiles may reflect disease severity and predict mortality in critical illnesses such as sepsis (3,4). Furthermore, we have shown that the plasma levels of proinflammatory cytokines (e.g., IL-18) and circulating mitochondrial injury markers, such as mitochondrial DNA, increase in critical illness and are predictive of mortality (5,6).…”

Interaction of Host‐Microbial Metabolism in Sepsis

“…Later, the relationship was also found between p-HPhLA and 28-day mortality in a large study from Roger et al, after analysis of metabolic proiling of plasma samples from 90 ICU subjects [21].…”