Intensive Care Medicine

, Volume 39, Issue 8, pp 1423–1434

Metabolomics in pneumonia and sepsis: an analysis of the GenIMS cohort study

Authors

    • Department of Critical Care Medicine and Emergency MedicineUniversity of Pittsburgh School of Medicine
    • Department of Critical Care, Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) CenterUniversity of Pittsburgh
  • Sachin Yende
    • Department of Critical Care, Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) CenterUniversity of Pittsburgh
    • Department of Critical CareUniversity of Pittsburgh School of Medicine
  • Melanie J. Scott
    • Department of Critical Care, Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) CenterUniversity of Pittsburgh
    • Department of SurgeryUniversity of Pittsburgh School of Medicine
  • John Pribis
    • Department of SurgeryUniversity of Pittsburgh School of Medicine
  • Robert P. Mohney
    • Metabolon, Inc.
  • Lauren N. Bell
    • Metabolon, Inc.
  • Yi-Fan Chen
    • Department of Biostatistics, Graduate School of Public HealthUniversity of Pittsburgh
  • Brian S. Zuckerbraun
    • Department of SurgeryUniversity of Pittsburgh School of Medicine
  • William L. Bigbee
    • Magee Women’s Research InstituteUniversity of Pittsburgh
  • Donald M. Yealy
    • Department of Emergency MedicineUniversity of Pittsburgh School of Medicine
  • Lisa Weissfeld
    • Department of Biostatistics, Graduate School of Public HealthUniversity of Pittsburgh
  • John A. Kellum
    • Department of Critical Care, Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) CenterUniversity of Pittsburgh
    • Department of Critical CareUniversity of Pittsburgh School of Medicine
  • Derek C. Angus
    • Department of Critical Care, Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) CenterUniversity of Pittsburgh
    • Department of Critical CareUniversity of Pittsburgh School of Medicine
Original

DOI: 10.1007/s00134-013-2935-7

Cite this article as:
Seymour, C.W., Yende, S., Scott, M.J. et al. Intensive Care Med (2013) 39: 1423. doi:10.1007/s00134-013-2935-7

Abstract

Purpose

To determine the global metabolomic profile as measured in circulating plasma from surviving and non-surviving patients with community-acquired pneumonia (CAP) and sepsis.

Methods

Random, outcome-stratified case–control sample from a prospective study of 1,895 patients hospitalized with CAP and sepsis. Cases (n = 15) were adults who died before 90 days, and controls (n = 15) were adults who survived, matched on demographics, infection type, and procalcitonin. We determined the global metabolomic profile in the first emergency department blood sample using non-targeted mass-spectrometry. We derived metabolite-based prognostic models for 90-day mortality. We determined if metabolites stimulated cytokine production by differentiated Thp1 monocytes in vitro, and validated metabolite profiles in mouse liver and kidney homogenates at 8 h in cecal ligation and puncture (CLP) sepsis.

Results

We identified 423 small molecules, of which the relative levels of 70 (17 %) were different between survivors and non-survivors (p ≤ 0.05). Broad differences were present in pathways of oxidative stress, bile acid metabolism, and stress response. Metabolite-based prognostic models for 90-day survival performed modestly (AUC = 0.67, 95 % CI 0.48, 0.81). Five nucleic acid metabolites were greater in non-survivors (p ≤ 0.05). Of these, pseudouridine increased monocyte expression of TNFα and IL1β versus control (p < 0.05). Pseudouridine was also increased in liver and kidney homogenates from CLP mice versus sham (p < 0.05 for both).

Conclusions

Although replication is required, we show the global metabolomic profile in plasma broadly differs between survivors and non-survivors of CAP and sepsis. Metabolite-based prognostic models had modest performance, though metabolites of oxidative stress may act as putative damage-associated molecular patterns.

Keywords

SepsisPneumoniaMetabolomicsBiomarker

Supplementary material

134_2013_2935_MOESM1_ESM.docx (26 kb)
Supplementary material 1 (DOCX 26 kb)
134_2013_2935_MOESM2_ESM.docx (404 kb)
Supplementary material 2 (DOCX 403 kb)

Copyright information

© Springer-Verlag Berlin Heidelberg and ESICM 2013