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Critical Care
Published in: Critical Care 1/2015

Open Access 01-12-2015 | Research

Integration of metabolic and inflammatory mediator profiles as a potential prognostic approach for septic shock in the intensive care unit

Authors: Beata Mickiewicz, Patrick Tam, Craig N Jenne, Caroline Leger, Josee Wong, Brent W Winston, Christopher Doig, Paul Kubes, Hans J Vogel, for the Alberta Sepsis Network

Published in: Critical Care | Issue 1/2015

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Abstract

Introduction

Septic shock is a major life-threatening condition in critically ill patients and it is well known that early recognition of septic shock and expedient initiation of appropriate treatment improves patient outcome. Unfortunately, to date no single compound has shown sufficient sensitivity and specificity to be used as a routine biomarker for early diagnosis and prognosis of septic shock in the intensive care unit (ICU). Therefore, the identification of new diagnostic tools remains a priority for increasing the survival rate of ICU patients. In this study, we have evaluated whether a combined nuclear magnetic resonance spectroscopy-based metabolomics and a multiplex cytokine/chemokine profiling approach could be used for diagnosis and prognostic evaluation of septic shock patients in the ICU.

Methods

Serum and plasma samples were collected from septic shock patients and ICU controls (ICU patients with the systemic inflammatory response syndrome but not suspected of having an infection). 1H Nuclear magnetic resonance spectra were analyzed and quantified using the targeted profiling methodology. The analysis of the inflammatory mediators was performed using human cytokine and chemokine assay kits.

Results

By using multivariate statistical analysis we were able to distinguish patient groups and detect specific metabolic and cytokine/chemokine patterns associated with septic shock and its mortality. These metabolites and cytokines/chemokines represent candidate biomarkers of the human response to septic shock and have the potential to improve early diagnosis and prognosis of septic shock.

Conclusions

Our findings show that integration of quantitative metabolic and inflammatory mediator data can be utilized for the diagnosis and prognosis of septic shock in the ICU.
Appendix
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Literature
1.
Slade E, Tamber PS, Vincent JL. The Surviving Sepsis Campaign: raising awareness to reduce mortality. Crit Care. 2003;7:1–2.PubMedPubMedCentral
2.
Dellinger RP, Carlet JM, Masur H, Gerlach H, Calandra T, Cohen J, et al. Surviving Sepsis Campaign guidelines for management of severe sepsis and septic shock. Crit Care Med. 2004;32:858–73.PubMed
3.
4.
Marshall JC, Vincent JL, Fink MP, Cook DJ, Rubenfeld G, Foster D, et al. Measures, markers, and mediators: toward a staging system for clinical sepsis. A report of the Fifth Toronto Sepsis Roundtable, Toronto, Ontario, Canada, October 25–26, 2000. Crit Care Med. 2003;31:1560–7.PubMed
5.
Bakker J, Coffernils M, Leon M, Gris P, Vincent JL. Blood lactate levels are superior to oxygen-derived variables in predicting outcome in human septic shock. Chest. 1991;99:956–62.PubMed
6.
Chiarla C, Giovannini I, Siegel JH, Boldrini G, Castagneto M. The relationship between plasma taurine and other amino acid levels in human sepsis. J Nutr. 2000;130:2222–7.PubMed
7.
Faix JD. Established and novel biomarkers of sepsis. Biomark Med. 2011;5:117–30.PubMed
8.
Holmes CL, Russell JA, Walley KR. Genetic polymorphisms in sepsis and septic shock: role in prognosis and potential for therapy. Chest. 2003;124:1103–15.PubMed
9.
Levy MM, Dellinger RP, Townsend SR, Linde-Zwirble WT, Marshall JC, Bion J, et al. The Surviving Sepsis Campaign: results of an international guideline-based performance improvement program targeting severe sepsis. Crit Care Med. 2010;38:367–74.PubMed
10.
Hoerr V, Zbytnuik L, Leger C, Tam PP, Kubes P, Vogel HJ. Gram-negative and Gram-positive bacterial infections give rise to a different metabolic response in a mouse model. J Proteome Res. 2012;11:3231–45.PubMedPubMedCentral
11.
Izquierdo-Garcia JL, Nin N, Ruiz-Cabello J, Rojas Y, de Paula M, Lopez-Cuenca S, et al. A metabolomic approach for diagnosis of experimental sepsis. Intensive Care Med. 2011;37:2023–32.PubMed
12.
Lin ZY, Xu PB, Yan SK, Meng HB, Yang GJ, Dai WX, et al. A metabonomic approach to early prognostic evaluation of experimental sepsis by (1)H NMR and pattern recognition. NMR Biomed. 2009;22:601–8.PubMed
13.
Mickiewicz B, Vogel HJ, Wong HR, Winston BW. Metabolomics as a novel approach for early diagnosis of pediatric septic shock and its mortality. Am J Respir Crit Care Med. 2013;187:967–76.PubMedPubMedCentral
14.
Mickiewicz B, Duggan GE, Winston BW, Doig C, Kubes P, Vogel HJ. Metabolic profiling of serum samples by 1H nuclear magnetic resonance spectroscopy as a potential diagnostic approach for septic shock. Crit Care Med. 2014;42:1140–9.PubMed
15.
Prabhakar U, Eirikis E, Davis HM. Simultaneous quantification of proinflammatory cytokines in human plasma using the LabMAP assay. J Immunol Methods. 2002;260:207–18.PubMed
16.
Bozza FA, Salluh JI, Japiassu AM, Soares M, Assis EF, Gomes RN, et al. Cytokine profiles as markers of disease severity in sepsis: a multiplex analysis. Crit Care. 2007;11:R49.PubMedPubMedCentral
17.
Lvovschi V, Arnaud L, Parizot C, Freund Y, Juillien G, Ghillani-Dalbin P, et al. Cytokine profiles in sepsis have limited relevance for stratifying patients in the emergency department: a prospective observational study. PLoS One. 2011;6:e28870.PubMedPubMedCentral
18.
Fjell CD, Thair S, Hsu JL, Walley KR, Russell JA, Boyd J. Cytokines and signaling molecules predict clinical outcomes in sepsis. PLoS One. 2013;8:e79207.PubMedPubMedCentral
19.
Saric J, Li JV, Swann JR, Utzinger J, Calvert G, Nicholson JK, et al. Integrated cytokine and metabolic analysis of pathological responses to parasite exposure in rodents. J Proteome Res. 2010;9:2255–64.PubMedPubMedCentral
20.
Bernard GR, Artigas A, Brigham KL, Carlet J, Falke K, Hudson L, et al. The American-European Consensus Conference on ARDS. Definitions, mechanisms, relevant outcomes, and clinical trial coordination. Am J Respir Crit Care Med. 1994;149:818–24.PubMed
21.
Levy MM, Fink MP, Marshall JC, Abraham E, Angus D, Cook D, et al. 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Crit Care Med. 2003;31:1250–6.PubMed
22.
Nicholson JK, Foxall PJ, Spraul M, Farrant RD, Lindon JC. 750 MHz 1H and 1H-13C NMR spectroscopy of human blood plasma. Anal Chem. 1995;67:793–811.PubMed
23.
Weljie AM, Newton J, Mercier P, Carlson E, Slupsky CM. Targeted profiling: quantitative analysis of 1H NMR metabolomics data. Anal Chem. 2006;78:4430–42.PubMed
24.
van den Berg RA, Hoefsloot HC, Westerhuis JA, Smilde AK, van der Werf MJ. Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics. 2006;7:142.PubMedPubMedCentral
25.
Eriksson L, Johansson E, Kettaneh-Wold N, Trygg J, Wikstrom C, Wold S. Multi- and megavariate data analysis part I: basic principles and applications. Umeå, Sweden: Umetrics AB; 2006.
26.
Trygg J, Wold S. Orthogonal projections to latent structures (O-PLS). J Chemometrics. 2002;16:119–28.
27.
Hosmer DW, Lemeshow S. Applied logistic regression. New York: Wiley; 2000.
28.
Picard RR, Cook DR. Cross-validation of regression models. J Am Stat Assoc. 1984;79:575–83.
29.
Trygg J, Holmes E, Lundstedt T. Chemometrics in metabonomics. J Proteome Res. 2007;6:469–79.PubMed
30.
Metz CE. Basic principles of ROC analysis. Semin Nucl Med. 1978;8:283–98.PubMed
31.
Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13:818–29.PubMed
32.
Vincent JL, de Mendonca A, Cantraine F, Moreno R, Takala J, Suter PM, et al. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on “sepsis-related problems” of the European Society of Intensive Care Medicine. Crit Care Med. 1998;26:1793–800.PubMed
33.
Cerra FB, Caprioli J, Siegel JH, McMenamy RR, Border JR. Proline metabolism in sepsis, cirrhosis and general surgery. The peripheral energy deficit. Ann Surg. 1979;190:577–86.PubMedPubMedCentral
34.
Landaas S, Jakobs C. The occurrence of 2-hydroxyisovaleric acid in patients with lactic acidosis and ketoacidosis. Clin Chim Acta. 1977;78:489–93.PubMed
35.
Mao H, Wang H, Wang B, Liu X, Gao H, Xu M, et al. Systemic metabolic changes of traumatic critically ill patients revealed by an NMR-based metabonomic approach. J Proteome Res. 2009;8:5423–30.PubMed
36.
Wishart DS, Knox C, Guo AC, Eisner R, Young N, Gautam B, et al. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res. 2009;37:D603–10.PubMed
37.
Wolfe RR, Shaw JH, Durkot MJ. Energy metabolism in trauma and sepsis: the role of fat. Prog Clin Biol Res. 1983;111:89–109.PubMed
38.
Wannemacher Jr RW, Klainer AS, Dinterman RE, Beisel WR. The significance and mechanism of an increased serum phenylalanine-tyrosine ratio during infection. Am J Clin Nutr. 1976;29:997–1006.PubMed
39.
Punyadeera C, Schneider EM, Schaffer D, Hsu HY, Joos TO, Kriebel F, et al. A biomarker panel to discriminate between systemic inflammatory response syndrome and sepsis and sepsis severity. J Emerg Trauma Shock. 2010;3:26–35.PubMedPubMedCentral
40.
Sekine K, Fujishima S, Aikawa N. Plasma hepatocyte growth factor is increased in early-phase sepsis. J Infect Chemother. 2004;10:110–4.PubMed
41.
Gracie JA, Robertson SE, McInnes IB. Interleukin-18. J Leukoc Biol. 2003;73:213–24.PubMed
42.
Corbett GT, Roy A, Pahan K. Gemfibrozil, a lipid-lowering drug, upregulates IL-1 receptor antagonist in mouse cortical neurons: implications for neuronal self-defense. J Immunol. 2012;189:1002–13.PubMed
43.
Dinarello CA. The role of the interleukin-1-receptor antagonist in blocking inflammation mediated by interleukin-1. N Engl J Med. 2000;343:732–4.PubMed
44.
Rubinstein MP, Kovar M, Purton JF, Cho JH, Boyman O, Surh CD, et al. Converting IL-15 to a superagonist by binding to soluble IL-15R{alpha}. Proc Natl Acad Sci U S A. 2006;103:9166–71.PubMedPubMedCentral
45.
Arend WP, Malyak M, Guthridge CJ, Gabay C. Interleukin-1 receptor antagonist: role in biology. Annu Rev Immunol. 1998;16:27–55.PubMed
46.
Saito K, Wagatsuma T, Toyama H, Ejima Y, Hoshi K, Shibusawa M, et al. Sepsis is characterized by the increases in percentages of circulating CD4 + CD25+ regulatory T cells and plasma levels of soluble CD25. Tohoku J Exp Med. 2008;216:61–8.PubMed
47.
Faure M, Chone F, Mettraux C, Godin JP, Bechereau F, Vuichoud J, et al. Threonine utilization for synthesis of acute phase proteins, intestinal proteins, and mucins is increased during sepsis in rats. J Nutr. 2007;137:1802–7.PubMed
48.
Freund H, Atamian S, Holroyde J, Fischer JE. Plasma amino acids as predictors of the severity and outcome of sepsis. Ann Surg. 1979;190:571–6.PubMedPubMedCentral
49.
Freund HR, Ryan Jr JA, Fischer JE. Amino acid derangements in patients with sepsis: treatment with branched chain amino acid rich infusions. Ann Surg. 1978;188:423–30.PubMedPubMedCentral
50.
Poeze M, Luiking YC, Breedveld P, Manders S, Deutz NE. Decreased plasma glutamate in early phases of septic shock with acute liver dysfunction is an independent predictor of survival. Clin Nutr. 2008;27:523–30.PubMed
51.
Langley RJ, Tsalik EL, van Velkinburgh JC, Glickman SW, Rice BJ, Wang C, et al. An integrated clinico-metabolomic model improves prediction of death in sepsis. Sci Transl Med. 2013;5:195ra195.
Metadata
Title
Integration of metabolic and inflammatory mediator profiles as a potential prognostic approach for septic shock in the intensive care unit
Authors
Beata Mickiewicz
Patrick Tam
Craig N Jenne
Caroline Leger
Josee Wong
Brent W Winston
Christopher Doig
Paul Kubes
Hans J Vogel
for the Alberta Sepsis Network
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Critical Care / Issue 1/2015
Electronic ISSN: 1364-8535
DOI
https://doi.org/10.1186/s13054-014-0729-0

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