A metabonomic approach to early prognostic evaluation of experimental sepsis

Journal of Infection

Volumn 56, Issue 6, 2008, Pages 474-481

  Xu, Ping bo ^a   Lin, Zhong ying ^b   Meng, Hai bing ^a   Yan, Shi kai ^c   Yang, Yun ^c   Liu, Xin ru ^b   Li, Jin bao ^a   Deng, Xiao ming ^a   Zhang, Wei dong ^b,c  

^a SECOND MILITARY MEDICAL UNIVERSITY   (China)

^b SECOND MILITARY MEDICAL UNIVERSITY   (China)

^c SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

HPLC MS; Metabonomics; Principle component analysis; Radial basis function neural network; Sepsis

Indexed keywords

DOCOSAHEXAENOIC ACID; DOCOSAPENTAENOIC ACID; LINOLEIC ACID; LINOLENIC ACID; OLEIC ACID; STEARIC ACID;

ACCURACY; ANIMAL EXPERIMENT; ANIMAL MODEL; ANIMAL TISSUE; ARTICLE; CONTROLLED STUDY; EXPERIMENTAL LIGATION; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; MALE; MASS SPECTROMETRY; METABOLOMICS; NONHUMAN; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; PROGNOSIS; RADIAL BASED FUNCTION; RAT; SEPSIS; SURVIVAL RATE;

ANIMALS; CHROMATOGRAPHY, HIGH PRESSURE LIQUID; MALE; MASS SPECTROMETRY; METABOLISM; PRINCIPAL COMPONENT ANALYSIS; PROGNOSIS; RANDOM ALLOCATION; RATS; RATS, SPRAGUE-DAWLEY; SEPSIS; SPECIFIC PATHOGEN-FREE ORGANISMS;

EID: 44649112396     PISSN: 01634453     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jinf.2008.03.011     Document Type: Article

References (43)

1. Martin G., Mannino D., Eaton S., and Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med 348 16 (2003) 1546-1554
2. Adrie C., Alberti C., Chaix-Couturier C., Azoulay E., De Lassence A., Cohen Y., et al. Epidemiology and economic evaluation of severe sepsis in France: age, severity, infection site, and place of acquisition (community, hospital, or intensive care unit) as determinants of workload and cost. J Crit Care 20 1 (2005) 46-58
3. Moerer O., Schmid A., Hofmann M., Herklotz A., Reinhart K., Werdan K., et al. Direct costs of severe sepsis in three German intensive care units based on retrospective electronic patient record analysis of resource use. Intensive Care Med 28 10 (2002) 1440-1446
4. Angus D.C., Linde-Zwirble W.T., Lidicker J., Clermont G., Carcillo J., and Pinsky M.R. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med 29 7 (2001) 1303-1310
5. Warren H. Strategies for the treatment of sepsis. N Engl J Med 336 13 (1997) 952-953
6. Parrillo J.E., Parker M.M., Natanson C., Suffredini A.F., Danner R.L., Cunnion R.E., et al. Septic shock in humans. Advances in the understanding of pathogenesis, cardiovascular dysfunction, and therapy. Ann Intern Med 113 3 (1990) 227-242
7. Pittet D., Rangel-Frausto S., Li N., Tarara D., and Costigan M. Systemic inflammatory response syndrome, sepsis, severe sepsis and septic shock: incidence, morbidities and outcomes in surgical ICU patients. Intensive Care Med 21 4 (1995) 302-309
8. Kollef M., Sherman G., Ward S., and Fraser V. Inadequate antimicrobial treatment of infections: a risk factor for hospital mortality among critically ill patients. Chest 115 2 (1999) 462-474
9. Holmes C.L., Russell J.A., and Walley K.R. Genetic polymorphisms in sepsis and septic shock: role in prognosis and potential for therapy. Chest 124 3 (2003) 1103-1115
10. Chen Q.X., Lv C., Huang L.X., Cheng B.L., Xie G.H., Wu S.J., et al. Genomic variations within DEFB1 are associated with the susceptibility to and the fatal outcome of severe sepsis in Chinese Han population. Genes Immun 8 5 (2007) 439-443
11. Walley K.R., and Russell J.A. Protein C -1641 AA is associated with decreased survival and more organ dysfunction in severe sepsis. Crit Care Med 35 1 (2007) 12-17
12. Opal S.M., Scannon P.J., Vincent J.L., White M., Carroll S.F., Palardy J.E., et al. Relationship between plasma levels of lipopolysaccharide (LPS) and LPS-binding protein in patients with severe sepsis and septic shock. J Infect Dis 180 5 (1999) 1584-1589
13. Povoa P., Coelho L., Almeida E., Fernandes A., Mealha R., Moreira P., et al. C-reactive protein as a marker of infection in critically ill patients. Clin Microbiol Infect 11 2 (2005) 101-108
14. Uzzan B., Cohen R., Nicolas P., Cucherat M., and Perret G.Y. Procalcitonin as a diagnostic test for sepsis in critically ill adults and after surgery or trauma: a systematic review and meta-analysis. Crit Care Med 34 7 (2006) 1996-2003
15. Dhainaut J.F., Shorr A.F., Marcias W.L., Kollef M.J., Levi M., Reinhart K., et al. Dynamic evolution of coagulopathy in the first day of severe sepsis: relationship with mortality and organ failure. Crit Care Med 33 2 (2005) 341-348
16. Morgenthaler N.G., Struck J., Christ-Crain M., Bergmann A., and Müller B. Pro-atrial natriuretic peptide is a prognostic marker in sepsis, similar to the APACHE P{cyrillic} score: an observational study. Crit Care 9 1 (2005) R37-R45
17. Hack C.E., De Groot E.R., Felt-Bersma R.J., Nuijens J.H., Strack van Schijndel R.J., Eerenberg-Belmer A.J., et al. Increased levels of interleukin-6 in sepsis. Blood 74 5 (1989) 1704-1710
18. Giannoudis P.V., Hildebrand F., and Pape H.C. Inflammatory serum markers in patients with multiple trauma. Can they predict outcome?. J Bone Joint Surg Br 86 3 (2004) 313-323
19. Tang B.M., Eslick G.D., Craig J.C., and McLean A.S. Accuracy of procalcitonin for sepsis diagnosis in critically ill patients: systematic review and meta-analysis. Lancet Infect Dis 7 3 (2007) 210-217
20. Dunn W.B., Bailey N.J., and Johnson H.E. Measuring the metabolome: current analytical technologies. Analyst 130 5 (2005) 606-625
21. Paige L.A., Mitchell M.W., Krishnan K.R., Kaddurah-Daouk R., and Steffens D.C. A preliminary metabolomic analysis of older adults with and without depression. Int J Geriatr Psychiatry 22 5 (2007) 418-423
22. Jones G.L., Sang E., Goddard C., Mortishire-Smith R.J., Sweatman J.N., Haselden J.N., et al. A functional analysis of mouse models of cardiac disease through metabolic profiling. J Biol Chem 280 9 (2005) 7530-7539
23. Dunn W.B., and Ellis D.I. Metabolomics: current analytical platforms and methodologies. Trends Anal Chem 24 4 (2005) 285-294
24. Weckwerth W., and Morgenthal K. Metabolomics: from pattern recognition to biological interpretation. Drug Discov Today 10 22 (2005) 1551-1558
25. Wang M., Lamers R.J., Korthout H.A., van Nesselrooij J.H., Witkamp R.F., van der Heijden R., et al. Metabolomics in the context of systems biology: bridging traditional Chinese medicine and molecular pharmacology. Phytother Res 19 3 (2005) 173-182
26. 1H NMR-based metabonomic techniques to distinguish between HIV-1 positive/AIDS patients on antiretroviral treatment and HIV-1 negative individuals. J Pharm Biomed Anal 41 4 (2006) 1442-1446
27. van Doorn M., Vogels J., Tas A., van Hoogdalem E.J., Burggraaf J., Cohen A., et al. Evaluation of metabolite profiles as biomarkers for the pharmacological effects of thiazolidinediones in Type 2 diabetes mellitus patients and healthy volunteers. Br J Clin Pharmacol 63 5 (2007) 562-574
28. Trygg J., Holmes E., and Lundstedt T. Chemometrics in metabonomics. J Proteome Res 6 2 (2007) 469-479
29. van der Greef J., and Smilde A.K. Symbiosis of chemometrics and metabolomics: past, present, and future. J Chemometr 19 (2005) 376-386
30. Wichterman K.A., Baue A.E., and Chaudry I.H. Sepsis and septic shock - a review of laboratory models and a proposal. J Surg Res 29 2 (1980) 189-201
31. Dieterle F., Schlotterbeck G., Ross A., Niederhauser U., and Senn H. Application of metabonomics in a compound ranking study in early drug development revealing drug-induced excretion of choline into urine. Chem Res Toxicol 19 9 (2006) 1175-1181
32. Dieterle F., Ross A., Schlotterbeck G., and Senn H. Metabolite projection analysis for fast identification of metabolites in metabonomics: application in an amiodarone study. Anal Chem 78 11 (2006) 3551-3561
33. Yap I.K.S., Clayton T.A., Tang H., Everett J.R., Hanton G., Provost J.P., et al. An integrated metabonomic approach to describe temporal metabolic disregulation induced in the rat by the model hepatotoxin allyl formate. J Proteome Res 5 10 (2006) 2675-2684
34. Brereton R.G. Chemometrics: data analysis for the laboratory and chemical plant (2003), John Wiley & Sons, London
35. Sarimveis H., Doganis P., and Alexandridis A. A classification technique based on radial basis function neural networks. Adv Eng Softw 37 4 (2006) 218-221
36. Samra J.S., Summers L.K., and Frayn K.N. Sepsis and fat metabolism. Br J Surg 83 9 (1996) 1186-1196
37. Martinez A., Chiolero R., Bollman M., Revelly J.P., Berger M., Cayeux C., et al. Assessment of adipose tissue metabolism by means of subcutaneous microdialysis in patients with sepsis or circulatory failure. Clin Physiol Funct Imaging 23 5 (2003) 286-292
38. Memon R.A., Feingold K.R., Moser A.H., Fuller J., and Grunfeld C. Regulation of fatty acid transport protein and fatty acid translocase mRNA levels by endotoxin and cytokines. Am J Physiol Endocrinol Metab 274 2 (1998) E210-E217
39. Brealey D., Brand M., Hargreaves I., Heales S., Land J., Smolenski R., et al. Association between mitochondrial dysfunction and severity and outcome of septic shock. Lancet 360 9328 (2002) 219-223
40. Calder P.C. n-3 Fatty acids, inflammation, and immunity: relevance to postsurgical and critically ill patients. Lipids 39 12 (2004) 1147-1161
41. Ren J., and Chung S.H. Anti-inflammatory effect of alpha-linolenic acid and its mode of action through the inhibition of nitric oxide production and inducible nitric oxide synthase gene expression via NF-kappaB and mitogen-activated protein kinase pathways. J Agric Food Chem 55 13 (2007) 5073-5080
42. Solakivi T., Jaakkola O., Kalela A., Pispa M., Salomäki A., Lehtimäki T., et al. Lipoprotein docosapentaenoic acid is associated with serum matrix metalloproteinase-9 concentration. Lipids Health Dis 4 1 (2005) 8
43. Kim Y.J., and Chung H.Y. Antioxidative and anti-inflammatory actions of docosahexaenoic acid and eicosapentaenoic acid in renal epithelial cells and macrophages. J Med Food 10 2 (2007) 225-231