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Published in: Critical Care 1/2015

Open Access 01-12-2015 | Research

Human metabolic response to systemic inflammation: assessment of the concordance between experimental endotoxemia and clinical cases of sepsis/SIRS

Authors: Kubra Kamisoglu, Beatrice Haimovich, Steve E Calvano, Susette M Coyle, Siobhan A Corbett, Raymond J Langley, Stephen F Kingsmore, Ioannis P Androulakis

Published in: Critical Care | Issue 1/2015

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Abstract

Introduction

Two recent, independent, studies conducted novel metabolomics analyses relevant to human sepsis progression; one was a human model of endotoxin (lipopolysaccharide (LPS)) challenge (experimental endotoxemia) and the other was community acquired pneumonia and sepsis outcome diagnostic study (CAPSOD). The purpose of the present study was to assess the concordance of metabolic responses to LPS and community-acquired sepsis.

Methods

We tested the hypothesis that the patterns of metabolic response elicited by endotoxin would agree with those in clinical sepsis. Alterations in the plasma metabolome of the subjects challenged with LPS were compared with those of sepsis patients who had been stratified into two groups: sepsis patients with confirmed infection and non-infected patients who exhibited systemic inflammatory response syndrome (SIRS) criteria. Common metabolites between endotoxemia and both these groups were individually identified, together with their direction of change and functional classifications.

Results

Response to endotoxemia at the metabolome level elicited characteristics that agree well with those observed in sepsis patients despite the high degree of variability in the response of these patients. Moreover, some distinct features of SIRS have been identified. Upon stratification of sepsis patients based on 28-day survival, the direction of change in 21 of 23 metabolites was the same in endotoxemia and sepsis survival groups.

Conclusions

The observed concordance in plasma metabolomes of LPS-treated subjects and sepsis survivors strengthens the relevance of endotoxemia to clinical research as a physiological model of community-acquired sepsis, and gives valuable insights into the metabolic changes that constitute a homeostatic response. Furthermore, recapitulation of metabolic differences between sepsis non-survivors and survivors in LPS-treated subjects can enable further research on the development and assessment of rational clinical therapies to prevent sepsis mortality. Compared with earlier studies which focused exclusively on comparing transcriptional dynamics, the distinct metabolomic responses to systemic inflammation with or without confirmed infection, suggest that the metabolome is much better at differentiating these pathophysiologies. Finally, the metabolic changes in the recovering patients shift towards the LPS-induced response pattern strengthening the notion that the metabolic, as well as transcriptional responses, characteristic to the endotoxemia model represent necessary and “healthy” responses to infectious stimuli.
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Literature
1.
go back to reference 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.CrossRef 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.CrossRef
2.
go back to reference Hall MJ, Williams SN, DeFrances CJ, Golosinskiy A. Inpatient care for septicemia or sepsis: a challenge for patients and hospitals. NCHS Data Brief. 2011;62:1–8. Hall MJ, Williams SN, DeFrances CJ, Golosinskiy A. Inpatient care for septicemia or sepsis: a challenge for patients and hospitals. NCHS Data Brief. 2011;62:1–8.
3.
go back to reference Angus DC, van der Poll T. Severe sepsis and septic shock. N Engl J Med. 2013;369:840–51.CrossRef Angus DC, van der Poll T. Severe sepsis and septic shock. N Engl J Med. 2013;369:840–51.CrossRef
4.
go back to reference Lagu T, Rothberg MB, Shieh MS, Pekow PS, Steingrub JS, Lindenauer PK. Hospitalizations, costs, and outcomes of severe sepsis in the United States 2003 to 2007. Crit Care Med. 2012;40:754–61.CrossRef Lagu T, Rothberg MB, Shieh MS, Pekow PS, Steingrub JS, Lindenauer PK. Hospitalizations, costs, and outcomes of severe sepsis in the United States 2003 to 2007. Crit Care Med. 2012;40:754–61.CrossRef
5.
go back to reference Reinhart K, Bauer M, Riedemann NC, Hartog CS. New approaches to sepsis: molecular diagnostics and biomarkers. Clin Microbiol Rev. 2012;25:609–34.CrossRef Reinhart K, Bauer M, Riedemann NC, Hartog CS. New approaches to sepsis: molecular diagnostics and biomarkers. Clin Microbiol Rev. 2012;25:609–34.CrossRef
6.
go back to reference Rittirsch D, Hoesel LM, Ward PA. The disconnect between animal models of sepsis and human sepsis. J Leukoc Biol. 2007;81:137–43.CrossRef Rittirsch D, Hoesel LM, Ward PA. The disconnect between animal models of sepsis and human sepsis. J Leukoc Biol. 2007;81:137–43.CrossRef
7.
go back to reference Deitch EA. Animal models of sepsis and shock: a review and lessons learned. Shock. 1998;9:1–11.CrossRef Deitch EA. Animal models of sepsis and shock: a review and lessons learned. Shock. 1998;9:1–11.CrossRef
8.
go back to reference Buras JA, Holzmann B, Sitkovsky M. Animal models of sepsis: setting the stage. Nat Rev Drug Discov. 2005;4:854–65.CrossRef Buras JA, Holzmann B, Sitkovsky M. Animal models of sepsis: setting the stage. Nat Rev Drug Discov. 2005;4:854–65.CrossRef
9.
go back to reference Munford RS. Detoxifying endotoxin: time, place and person. J Endotoxin Res. 2005;11:69–84.PubMed Munford RS. Detoxifying endotoxin: time, place and person. J Endotoxin Res. 2005;11:69–84.PubMed
10.
go back to reference Wolff SM. Biological effects of bacterial endotoxins in man. J Infect Dis. 1973;128:259–64.CrossRef Wolff SM. Biological effects of bacterial endotoxins in man. J Infect Dis. 1973;128:259–64.CrossRef
11.
go back to reference Andreasen AS, Krabbe KS, Krogh-Madsen R, Taudorf S, Pedersen BK, Moller K. Human endotoxemia as a model of systemic inflammation. Curr Med Chem. 2008;15:1697–705.CrossRef Andreasen AS, Krabbe KS, Krogh-Madsen R, Taudorf S, Pedersen BK, Moller K. Human endotoxemia as a model of systemic inflammation. Curr Med Chem. 2008;15:1697–705.CrossRef
12.
13.
go back to reference Lowry SF. Human endotoxemia: a model for mechanistic insight and therapeutic targeting. Shock. 2005;24:94–100.CrossRef Lowry SF. Human endotoxemia: a model for mechanistic insight and therapeutic targeting. Shock. 2005;24:94–100.CrossRef
14.
go back to reference Calvano SE, Coyle SM. Experimental human endotoxemia: a model of the systemic inflammatory response syndrome? Surg Infect (Larchmt). 2012;13:293–9.CrossRef Calvano SE, Coyle SM. Experimental human endotoxemia: a model of the systemic inflammatory response syndrome? Surg Infect (Larchmt). 2012;13:293–9.CrossRef
15.
go back to reference Haimovich B, Reddell MT, Calvano JE, Calvano SE, Macor MA, Coyle SM, et al. A novel model of common Toll-like receptor 4- and injury-induced transcriptional themes in human leukocytes. Crit Care. 2010;14:R177.CrossRef Haimovich B, Reddell MT, Calvano JE, Calvano SE, Macor MA, Coyle SM, et al. A novel model of common Toll-like receptor 4- and injury-induced transcriptional themes in human leukocytes. Crit Care. 2010;14:R177.CrossRef
16.
go back to reference Calvano SE, Xiao W, Richards DR, Felciano RM, Baker HV, Cho RJ, et al. A network-based analysis of systemic inflammation in humans. Nature. 2005;437:1032–7.CrossRef Calvano SE, Xiao W, Richards DR, Felciano RM, Baker HV, Cho RJ, et al. A network-based analysis of systemic inflammation in humans. Nature. 2005;437:1032–7.CrossRef
17.
go back to reference Nguyen TT, Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. Computational identification of transcriptional regulators in human endotoxemia. PLoS One. 2011;6:e18889.CrossRef Nguyen TT, Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. Computational identification of transcriptional regulators in human endotoxemia. PLoS One. 2011;6:e18889.CrossRef
18.
go back to reference Foteinou P, Calvano S, Lowry S, Androulakis I. Modeling endotoxin-induced systemic inflammation using an indirect response approach. Math Biosci. 2009;217:27–42.CrossRef Foteinou P, Calvano S, Lowry S, Androulakis I. Modeling endotoxin-induced systemic inflammation using an indirect response approach. Math Biosci. 2009;217:27–42.CrossRef
19.
go back to reference Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. A physiological model for autonomic heart rate regulation in human endotoxemia. Shock. 2011;35:229.CrossRef Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. A physiological model for autonomic heart rate regulation in human endotoxemia. Shock. 2011;35:229.CrossRef
20.
go back to reference Scheff JD, Mavroudis PD, Calvano SE, Lowry SF, Androulakis IP. Modeling autonomic regulation of cardiac function and heart rate variability in human endotoxemia. Physiol Genomics. 2011;43:951–64.CrossRef Scheff JD, Mavroudis PD, Calvano SE, Lowry SF, Androulakis IP. Modeling autonomic regulation of cardiac function and heart rate variability in human endotoxemia. Physiol Genomics. 2011;43:951–64.CrossRef
21.
go back to reference Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. Multiscale model for the assessment of autonomic dysfunction in human endotoxemia. Physiol Genomics. 2010;42:5–19.CrossRef Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. Multiscale model for the assessment of autonomic dysfunction in human endotoxemia. Physiol Genomics. 2010;42:5–19.CrossRef
22.
go back to reference Scheff JD, Mavroudis PD, Foteinou PT, Calvano SE, Androulakis IP. Modeling physiologic variability in human endotoxemia. Crit Rev Biomed Eng. 2012;40:313–22.CrossRef Scheff JD, Mavroudis PD, Foteinou PT, Calvano SE, Androulakis IP. Modeling physiologic variability in human endotoxemia. Crit Rev Biomed Eng. 2012;40:313–22.CrossRef
23.
go back to reference Scheff JD, Calvano SE, Lowry SF, Androulakis IP. Modeling the influence of circadian rhythms on the acute inflammatory response. J Theor Biol. 2010;264:1068–76.CrossRef Scheff JD, Calvano SE, Lowry SF, Androulakis IP. Modeling the influence of circadian rhythms on the acute inflammatory response. J Theor Biol. 2010;264:1068–76.CrossRef
24.
go back to reference Scheff JD, Mavroudis PD, Calvano SE, Androulakis IP. Translational applications of evaluating physiologic variability in human endotoxemia. J Clin Monit Comput. 2013;27:405–15.CrossRef Scheff JD, Mavroudis PD, Calvano SE, Androulakis IP. Translational applications of evaluating physiologic variability in human endotoxemia. J Clin Monit Comput. 2013;27:405–15.CrossRef
25.
go back to reference Kamisoglu K, Sleight KE, Calvano SE, Coyle SM, Corbett SA, Androulakis IP. Temporal metabolic profiling of plasma during endotoxemia in humans. Shock. 2013;40:519–26.CrossRef Kamisoglu K, Sleight KE, Calvano SE, Coyle SM, Corbett SA, Androulakis IP. Temporal metabolic profiling of plasma during endotoxemia in humans. Shock. 2013;40:519–26.CrossRef
26.
go back to reference Kosmides AK, Kamisoglu K, Calvano SE, Corbett SA, Androulakis IP. Metabolomic fingerprinting: challenges and opportunities. Crit Rev Biomed Eng. 2013;41:205–21.CrossRef Kosmides AK, Kamisoglu K, Calvano SE, Corbett SA, Androulakis IP. Metabolomic fingerprinting: challenges and opportunities. Crit Rev Biomed Eng. 2013;41:205–21.CrossRef
27.
go back to reference Kamisoglu K, Calvano SE, Coyle S, Corbett SA, Androulakis IP. Integrated transcriptional and metabolic profiling in human endotoxemia. Shock. 2014;42:499–508.CrossRef Kamisoglu K, Calvano SE, Coyle S, Corbett SA, Androulakis IP. Integrated transcriptional and metabolic profiling in human endotoxemia. Shock. 2014;42:499–508.CrossRef
28.
go back to reference 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. 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.
29.
go back to reference Evans AM, DeHaven CD, Barrett T, Mitchell M, Milgram E. Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Anal Chem. 2009;81:6656–67.CrossRef Evans AM, DeHaven CD, Barrett T, Mitchell M, Milgram E. Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Anal Chem. 2009;81:6656–67.CrossRef
30.
go back to reference Talwar S, Munson PJ, Barb J, Fiuza C, Cintron AP, Logun C, et al. Gene expression profiles of peripheral blood leukocytes after endotoxin challenge in humans. Physiol Genomics. 2006;25:203–15.CrossRef Talwar S, Munson PJ, Barb J, Fiuza C, Cintron AP, Logun C, et al. Gene expression profiles of peripheral blood leukocytes after endotoxin challenge in humans. Physiol Genomics. 2006;25:203–15.CrossRef
31.
go back to reference Leys C, Ley C, Klein O, Bernard P, Licata L. Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J Exp Soc Psychol. 2013;49:764–6.CrossRef Leys C, Ley C, Klein O, Bernard P, Licata L. Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J Exp Soc Psychol. 2013;49:764–6.CrossRef
32.
go back to reference Hampel FR. The influence curve and its role in robust estimation. J Am Stat Assoc. 1974;69:383–93.CrossRef Hampel FR. The influence curve and its role in robust estimation. J Am Stat Assoc. 1974;69:383–93.CrossRef
33.
go back to reference Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. 1995;57:289–300. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. 1995;57:289–300.
34.
go back to reference Visser T, Pillay J, Pickkers P, Leenen LP, Koenderman L. Homology in systemic neutrophil response induced by human experimental endotoxemia and by trauma. Shock. 2012;37:145–51.CrossRef Visser T, Pillay J, Pickkers P, Leenen LP, Koenderman L. Homology in systemic neutrophil response induced by human experimental endotoxemia and by trauma. Shock. 2012;37:145–51.CrossRef
35.
go back to reference Glickman SW, Cairns CB, Otero RM, Woods CW, Tsalik EL, Langley RJ, et al. Disease progression in hemodynamically stable patients presenting to the emergency department with sepsis. Acad Emerg Med. 2010;17:383–90.CrossRef Glickman SW, Cairns CB, Otero RM, Woods CW, Tsalik EL, Langley RJ, et al. Disease progression in hemodynamically stable patients presenting to the emergency department with sepsis. Acad Emerg Med. 2010;17:383–90.CrossRef
36.
go back to reference Straub RH, Vogl D, Gross V, Lang B, Scholmerich J, Andus T. Association of humoral markers of inflammation and dehydroepiandrosterone sulfate or cortisol serum levels in patients with chronic inflammatory bowel disease. Am J Gastroenterol. 1998;93:2197–202.CrossRef Straub RH, Vogl D, Gross V, Lang B, Scholmerich J, Andus T. Association of humoral markers of inflammation and dehydroepiandrosterone sulfate or cortisol serum levels in patients with chronic inflammatory bowel disease. Am J Gastroenterol. 1998;93:2197–202.CrossRef
37.
go back to reference Seok J, Warren HS, Cuenca AG, Mindrinos MN, Baker HV, Xu W, et al. Genomic responses in mouse models poorly mimic human inflammatory diseases. Proc Natl Acad Sci U S A. 2013;110:3507–12.CrossRef Seok J, Warren HS, Cuenca AG, Mindrinos MN, Baker HV, Xu W, et al. Genomic responses in mouse models poorly mimic human inflammatory diseases. Proc Natl Acad Sci U S A. 2013;110:3507–12.CrossRef
38.
go back to reference Matzinger P. The danger model: a renewed sense of self. Science. 2002;296:301–5.CrossRef Matzinger P. The danger model: a renewed sense of self. Science. 2002;296:301–5.CrossRef
39.
go back to reference Cain D, del Arroyo A, Ackland G. Uncontrolled sepsis: a systematic review of translational immunology studies in intensive care medicine. ICMx. 2014;2:1–25.CrossRef Cain D, del Arroyo A, Ackland G. Uncontrolled sepsis: a systematic review of translational immunology studies in intensive care medicine. ICMx. 2014;2:1–25.CrossRef
40.
go back to reference Maslove DM, Wong HR. Gene expression profiling in sepsis: timing, tissue, and translational considerations. Trends Mol Med. 2014;20:204–13.CrossRef Maslove DM, Wong HR. Gene expression profiling in sepsis: timing, tissue, and translational considerations. Trends Mol Med. 2014;20:204–13.CrossRef
41.
go back to reference Osuchowski MF, Remick DG, Lederer JA, Lang CH, Aasen AO, Aibiki M, et al. Abandon the mouse research ship? Not just yet! Shock. 2014;41:463–75.CrossRef Osuchowski MF, Remick DG, Lederer JA, Lang CH, Aasen AO, Aibiki M, et al. Abandon the mouse research ship? Not just yet! Shock. 2014;41:463–75.CrossRef
Metadata
Title
Human metabolic response to systemic inflammation: assessment of the concordance between experimental endotoxemia and clinical cases of sepsis/SIRS
Authors
Kubra Kamisoglu
Beatrice Haimovich
Steve E Calvano
Susette M Coyle
Siobhan A Corbett
Raymond J Langley
Stephen F Kingsmore
Ioannis P Androulakis
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/s13054-015-0783-2

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