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Integrative "omic" analysis of experimental bacteremia identifies a metabolic signature that distinguishes human sepsis from systemic inflammatory response syndromes.

Publication ,  Journal Article
Langley, RJ; Tipper, JL; Bruse, S; Baron, RM; Tsalik, EL; Huntley, J; Rogers, AJ; Jaramillo, RJ; O'Donnell, D; Mega, WM; Keaton, M; Otero, RM ...
Published in: Am J Respir Crit Care Med
August 15, 2014

RATIONALE: Sepsis is a leading cause of morbidity and mortality. Currently, early diagnosis and the progression of the disease are difficult to make. The integration of metabolomic and transcriptomic data in a primate model of sepsis may provide a novel molecular signature of clinical sepsis. OBJECTIVES: To develop a biomarker panel to characterize sepsis in primates and ascertain its relevance to early diagnosis and progression of human sepsis. METHODS: Intravenous inoculation of Macaca fascicularis with Escherichia coli produced mild to severe sepsis, lung injury, and death. Plasma samples were obtained before and after 1, 3, and 5 days of E. coli challenge and at the time of killing. At necropsy, blood, lung, kidney, and spleen samples were collected. An integrative analysis of the metabolomic and transcriptomic datasets was performed to identify a panel of sepsis biomarkers. MEASUREMENTS AND MAIN RESULTS: The extent of E. coli invasion, respiratory distress, lethargy, and mortality was dependent on the bacterial dose. Metabolomic and transcriptomic changes characterized severe infections and death, and indicated impaired mitochondrial, peroxisomal, and liver functions. Analysis of the pulmonary transcriptome and plasma metabolome suggested impaired fatty acid catabolism regulated by peroxisome-proliferator activated receptor signaling. A representative four-metabolite model effectively diagnosed sepsis in primates (area under the curve, 0.966) and in two human sepsis cohorts (area under the curve, 0.78 and 0.82). CONCLUSIONS: A model of sepsis based on reciprocal metabolomic and transcriptomic data was developed in primates and validated in two human patient cohorts. It is anticipated that the identified parameters will facilitate early diagnosis and management of sepsis.

Duke Scholars

Published In

Am J Respir Crit Care Med

DOI

EISSN

1535-4970

Publication Date

August 15, 2014

Volume

190

Issue

4

Start / End Page

445 / 455

Location

United States

Related Subject Headings

  • Transcriptome
  • Systemic Inflammatory Response Syndrome
  • Respiratory System
  • Metabolomics
  • Male
  • Macaca
  • Humans
  • Female
  • Early Diagnosis
  • Disease Models, Animal
 

Citation

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Langley, R. J., Tipper, J. L., Bruse, S., Baron, R. M., Tsalik, E. L., Huntley, J., … Harrod, K. S. (2014). Integrative "omic" analysis of experimental bacteremia identifies a metabolic signature that distinguishes human sepsis from systemic inflammatory response syndromes. Am J Respir Crit Care Med, 190(4), 445–455. https://doi.org/10.1164/rccm.201404-0624OC
Langley, Raymond J., Jennifer L. Tipper, Shannon Bruse, Rebecca M. Baron, Ephraim L. Tsalik, James Huntley, Angela J. Rogers, et al. “Integrative "omic" analysis of experimental bacteremia identifies a metabolic signature that distinguishes human sepsis from systemic inflammatory response syndromes.Am J Respir Crit Care Med 190, no. 4 (August 15, 2014): 445–55. https://doi.org/10.1164/rccm.201404-0624OC.
Langley RJ, Tipper JL, Bruse S, Baron RM, Tsalik EL, Huntley J, et al. Integrative "omic" analysis of experimental bacteremia identifies a metabolic signature that distinguishes human sepsis from systemic inflammatory response syndromes. Am J Respir Crit Care Med. 2014 Aug 15;190(4):445–55.
Langley, Raymond J., et al. “Integrative "omic" analysis of experimental bacteremia identifies a metabolic signature that distinguishes human sepsis from systemic inflammatory response syndromes.Am J Respir Crit Care Med, vol. 190, no. 4, Aug. 2014, pp. 445–55. Pubmed, doi:10.1164/rccm.201404-0624OC.
Langley RJ, Tipper JL, Bruse S, Baron RM, Tsalik EL, Huntley J, Rogers AJ, Jaramillo RJ, O’Donnell D, Mega WM, Keaton M, Kensicki E, Gazourian L, Fredenburgh LE, Massaro AF, Otero RM, Fowler VG, Rivers EP, Woods CW, Kingsmore SF, Sopori ML, Perrella MA, Choi AMK, Harrod KS. Integrative "omic" analysis of experimental bacteremia identifies a metabolic signature that distinguishes human sepsis from systemic inflammatory response syndromes. Am J Respir Crit Care Med. 2014 Aug 15;190(4):445–455.

Published In

Am J Respir Crit Care Med

DOI

EISSN

1535-4970

Publication Date

August 15, 2014

Volume

190

Issue

4

Start / End Page

445 / 455

Location

United States

Related Subject Headings

  • Transcriptome
  • Systemic Inflammatory Response Syndrome
  • Respiratory System
  • Metabolomics
  • Male
  • Macaca
  • Humans
  • Female
  • Early Diagnosis
  • Disease Models, Animal