Sepsis biomarkers: an omics perspective

Xiao Liu, Hui Ren, Daizhi Peng

Front. Med. ›› 2014, Vol. 8 ›› Issue (1) : 58-67.

PDF(161 KB)
Front. Med. All Journals
PDF(161 KB)
Front. Med. ›› 2014, Vol. 8 ›› Issue (1) : 58-67. DOI: 10.1007/s11684-014-0318-2
REVIEW
REVIEW

Sepsis biomarkers: an omics perspective

Author information +
History +

Abstract

Sepsis is a common cause of death in hospitalized patients worldwide. The early detection of sepsis remains a great challenge for clinicians, and delayed diagnosis frequently undermines treatment efforts, thereby contributing to high mortality. Omics technologies allow high-throughput screening of sepsis biomarkers. This review describes currently available and novel sepsis biomarkers in the context of genomics, transcriptomics, proteomics, and metabolomics. The combination of these technologies can help refine the diagnosis of sepsis. This review paper serves as a reference for future studies that employ an integrated, multi-omics approach to disease identification.

Keywords

sepsis / biomarker / genomics / transcriptomics / proteomics / metabolomics

Cite this article

Download citation ▾
Xiao Liu, Hui Ren, Daizhi Peng. Sepsis biomarkers: an omics perspective. Front Med, 2014, 8(1): 58‒67 https://doi.org/10.1007/s11684-014-0318-2
This is a preview of subscription content, contact us for subscripton.

References

[1]
Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, Sharma S, Suppes R, Feinstein D, Zanotti S, Taiberg L, Gurka D, Kumar A, Cheang M. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med2006; 34(6): 1589–1596
CrossRef Pubmed Google scholar
[2]
Reinhart K, Bauer M, Riedemann NC, Hartog CS. New approaches to sepsis: molecular diagnostics and biomarkers. Clin Microbiol Rev2012; 25(4): 609–634
CrossRef Pubmed Google scholar
[3]
Cohen J. The immunopathogenesis of sepsis. Nature2002; 420(6917): 885–891
CrossRef Pubmed Google scholar
[4]
Harbarth S, Holeckova K, Froidevaux C, Pittet D, Ricou B, Grau GE, Vadas L, Pugin J; Geneva Sepsis Network.. Diagnostic value of procalcitonin, interleukin-6, and interleukin-8 in critically ill patients admitted with suspected sepsis. Am J Respir Crit Care Med2001; 164(3): 396–402
CrossRef Pubmed Google scholar
[5]
Simon L, Gauvin F, Amre DK, Saint-Louis P, Lacroix J. Serum procalcitonin and C-reactive protein levels as markers of bacterial infection: a systematic review and meta-analysis. Clin Infect Dis2004; 39(2): 206–217
CrossRef Pubmed Google scholar
[6]
Bozza FA, Salluh JI, Japiassu AM, Soares M, Assis EF, Gomes RN, Bozza MT, Castro-Faria-Neto HC, Bozza PT. Cytokine profiles as markers of disease severity in sepsis: a multiplex analysis. Crit Care2007; 11(2): R49
CrossRef Pubmed Google scholar
[7]
Vaschetto R, Nicola S, Olivieri C, Boggio E, Piccolella F, Mesturini R, Damnotti F, Colombo D, Navalesi P, Della Corte F, Dianzani U, Chiocchetti A. Serum levels of osteopontin are increased in SIRS and sepsis. Intensive Care Med2008; 34(12): 2176–2184
CrossRef Pubmed Google scholar
[8]
Brenner T, Rosenhagen C, Steppan J, Lichtenstern C, Weitz J, Bruckner T, Martin EO, Hoffmann U, Weigand MA, Hofer S. Redox responses in patients with sepsis: high correlation of thioredoxin-1 and macrophage migration inhibitory factor plasma levels. Mediators Inflamm2010; 2010: 985614
CrossRef Pubmed Google scholar
[9]
Bae JS. Role of high mobility group box 1 in inflammatory disease: focus on sepsis. Arch Pharm Res2012; 35(9): 1511–1523
CrossRef Pubmed Google scholar
[10]
Wu Y, Wang F, Fan X, Bao R, Bo L, Li J, Deng X. Accuracy of plasma sTREM-1 for sepsis diagnosis in systemic inflammatory patients: a systematic review and meta-analysis. Crit Care2012; 16(6): R229
CrossRef Pubmed Google scholar
[11]
Backes Y, van der Sluijs KF, Mackie DP, Tacke F, Koch A, Tenhunen JJ, Schultz MJ. Usefulness of suPAR as a biological marker in patients with systemic inflammation or infection: a systematic review. Intensive Care Med2012; 38(9): 1418–1428
CrossRef Pubmed Google scholar
[12]
Cohen J. The immunopathogenesis of sepsis. Nature2002; 420(6917): 885–891
CrossRef Pubmed Google scholar
[13]
Lobo SM, Lobo FR, Bota DP, Lopes-Ferreira F, Soliman HM, Mélot C, Vincent JL. C-reactive protein levels correlate with mortality and organ failure in critically ill patients. Chest2003; 123(6): 2043–2049
CrossRef Pubmed Google scholar
[14]
Komiya K, Ishii H, Teramoto S, Takahashi O, Yamamoto H, Oka H, Umeki K, Kadota J.Plasma C-reactive protein levels are associated with mortality in elderly with acute lung injury. J Crit Care2012; 27(5): 524 e521–526
[15]
Levy MM, Fink MP, Marshall JC, Abraham E, Angus D, Cook D, Cohen J, Opal SM, Vincent JL, Ramsay G; SCCM/ESICM/ACCP/ATS/SIS. 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Crit Care Med2003; 31(4): 1250–1256
CrossRef Pubmed Google scholar
[16]
Wacker C, Prkno A, Brunkhorst FM, Schlattmann P. Procalcitonin as a diagnostic marker for sepsis: a systematic review and meta-analysis. Lancet Infect Dis2013; 13(5): 426–435
CrossRef Pubmed Google scholar
[17]
Kofoed K, Andersen O, Kronborg G, Tvede M, Petersen J, Eugen-Olsen J, Larsen K. Use of plasma C-reactive protein, procalcitonin, neutrophils, macrophage migration inhibitory factor, soluble urokinase-type plasminogen activator receptor, and soluble triggering receptor expressed on myeloid cells-1 in combination to diagnose infections: a prospective study. Crit Care 2007; 11(2): R38
CrossRef Pubmed Google scholar
[18]
Xiong C, McKeel DW, Jr., Miller JP, Morris JC. Combining correlated diagnostic tests: application to neuropathologic diagnosis of Alzheimer's disease. Medical decision making: an international journal of the Society for Medical Decision Making, 2004, 24(6): 659–669
[19]
Gibot S, Béné MC, Noel R, Massin F, Guy J, Cravoisy A, Barraud D, De Carvalho Bittencourt M, Quenot JP, Bollaert PE, Faure G, Charles PE. Combination biomarkers to diagnose sepsis in the critically ill patient. Am J Respir Crit Care Med2012; 186(1): 65–71
CrossRef Pubmed Google scholar
[20]
Wong HR. Genetics and genomics in pediatric septic shock. Crit Care Med2012; 40(5): 1618–1626
CrossRef Pubmed Google scholar
[21]
Sutherland AM, Walley KR, Manocha S, Russell JA. The association of interleukin 6 haplotype clades with mortality in critically ill adults. Arch Intern Med2005; 165(1): 75–82
CrossRef Pubmed Google scholar
[22]
Thompson CM, Holden TD, Rona G, Laxmanan B, Black RA, O’Keefe GE, Wurfel MM. Toll-like receptor 1 polymorphisms and associated outcomes in sepsis after traumatic injury: a candidate gene association study. Ann Surg2014; 259(1): 179–185
CrossRef Pubmed Google scholar
[23]
Cornell TT, Wynn J, Shanley TP, Wheeler DS, Wong HR. Mechanisms and regulation of the gene-expression response to sepsis. Pediatrics2010; 125(6): 1248–1258
CrossRef Pubmed Google scholar
[24]
de Aguiar BB, Girardi I, Paskulin DD, de Franca E, Dornelles C, Dias FS, Bonorino C, Alho CS. CD14 expression in the first 24h of sepsis: effect of –260C→T CD14 SNP. Immunol Invest2008; 37(8): 752–769
CrossRef Pubmed Google scholar
[25]
Fallavena PR, Borges TJ, Paskulin DD, Paludo FJO, Goetze TB, de Oliveira JR, Nóbrega OT, Dias FS, Alho CS. The influences of CD14 –260C→T polymorphism on survival in ICU critically ill patients. Immunol Invest2009; 38(8): 797–811
CrossRef Pubmed Google scholar
[26]
Heesen M, Bloemeke B, Schade U, Obertacke U, Majetschak M. The –260 C→T promoter polymorphism of the lipopolysaccharide receptor CD14 and severe sepsis in trauma patients. Intensive Care Med2002; 28(8): 1161–1163
CrossRef Pubmed Google scholar
[27]
Barber RC, Aragaki CC, Rivera-Chavez FA, Purdue GF, Hunt JL, Horton JW. TLR4 and TNF-α polymorphisms are associated with an increased risk for severe sepsis following burn injury. J Med Genet2004; 41(11): 808–813
CrossRef Pubmed Google scholar
[28]
Barber RC, Aragaki CC, Rivera-Chavez FA, Purdue GF, Hunt JL, Horton JW. TLR4 and TNF-α polymorphisms are associated with an increased risk for severe sepsis following burn injury. J Med Genet2004; 41(11): 808–813
CrossRef Pubmed Google scholar
[29]
Zeng L, Gu W, Zhang AQ, Zhang M, Zhang LY, Du DY, Huang SN, Jiang JX. A functional variant of lipopolysaccharide binding protein predisposes to sepsis and organ dysfunction in patients with major trauma. Ann Surg2012; 255(1): 147–157
CrossRef Pubmed Google scholar
[30]
Cardinal-Fernández P, Ferruelo A, El-Assar M, Santiago C, Gómez-Gallego F, Martín-Pellicer A, Frutos-Vivar F, Peñuelas O, Nin N, Esteban A, Lorente JA. Genetic predisposition to acute kidney injury induced by severe sepsis. J Crit Care2013; 28(4): 365–370
CrossRef Pubmed Google scholar
[31]
Baier RJ, Loggins J, Yanamandra K. IL-10, IL-6 and CD14 polymorphisms and sepsis outcome in ventilated very low birth weight infants. BMC Med2006; 4(1): 10
CrossRef Pubmed Google scholar
[32]
Jilma B, Marsik C, Kovar F, Wagner OF, Jilma-Stohlawetz P, Endler G. The single nucleotide polymorphism Ser128Arg in the E-selectin gene is associated with enhanced coagulation during human endotoxemia. Blood2005; 105(6): 2380–2383
CrossRef Pubmed Google scholar
[33]
Geishofer G, Binder A, Müller M, Zöhrer B, Resch B, Müller W, Faber J, Finn A, Endler G, Mannhalter C, Zenz W; Central European Meningococcal Genetic Study Group. 4G/5G promoter polymorphism in the plasminogen-activator-inhibitor-1 gene in children with systemic meningococcaemia. Eur J Pediatr2005; 164(8): 486–490
CrossRef Pubmed Google scholar
[34]
Gunderson KL, Steemers FJ, Lee G, Mendoza LG, Chee MS. A genome-wide scalable SNP genotyping assay using microarray technology. Nat Genet2005; 37(5): 549–554
CrossRef Pubmed Google scholar
[35]
Hoffmann TJ, Kvale MN, Hesselson SE, Zhan Y, Aquino C, Cao Y, Cawley S, Chung E, Connell S, Eshragh J, Ewing M, Gollub J, Henderson M, Hubbell E, Iribarren C, Kaufman J, Lao RZ, Lu Y, Ludwig D, Mathauda GK, McGuire W, Mei G, Miles S, Purdy MM, Quesenberry C, Ranatunga D, Rowell S, Sadler M, Shapero MH, Shen L, Shenoy TR, Smethurst D, Van den Eeden SK, Walter L, Wan E, Wearley R, Webster T, Wen CC, Weng L, Whitmer RA, Williams A, Wong SC, Zau C, Finn A, Schaefer C, Kwok PY, Risch N. Next generation genome-wide association tool: design and coverage of a high-throughput European-optimized SNP array. Genomics2011; 98(2): 79–89
CrossRef Pubmed Google scholar
[36]
Arcaroli J, Fessler MB, Abraham E. Genetic polymorphisms and sepsis. Shock2005; 24(4): 300–312
CrossRef Pubmed Google scholar
[37]
Berger SL, Kouzarides T, Shiekhattar R, Shilatifard A. An operational definition of epigenetics. Genes Dev2009; 23(7): 781–783
CrossRef Pubmed Google scholar
[38]
Delcuve GP, Rastegar M, Davie JR. Epigenetic control. J Cell Physiol2009; 219(2): 243–250
CrossRef Pubmed Google scholar
[39]
Wen H, Dou Y, Hogaboam CM, Kunkel SL. Epigenetic regulation of dendritic cell-derived interleukin-12 facilitates immunosuppression after a severe innate immune response. Blood2008; 111(4): 1797–1804
CrossRef Pubmed Google scholar
[40]
Bierne H, Hamon M, Cossart P. Epigenetics and bacterial infections. Cold Spring Harb Perspect Med2012; 2(12): a010272
CrossRef Pubmed Google scholar
[41]
Laudanski K. Adoptive transfer of naïve dendritic cells in resolving post-sepsis long-term immunosuppression. Med Hypotheses2012; 79(4): 478–480
CrossRef Pubmed Google scholar
[42]
Boomer JS, To K, Chang KC, Takasu O, Osborne DF, Walton AH, Bricker TL, Jarman SD 2nd, Kreisel D, Krupnick AS, Srivastava A, Swanson PE, Green JM, Hotchkiss RS. Immunosuppression in patients who die of sepsis and multiple organ failure. JAMA2011; 306(23): 2594–2605
CrossRef Pubmed Google scholar
[43]
Carson WF, Cavassani KA, Dou Y, Kunkel SL. Epigenetic regulation of immune cell functions during post-septic immunosuppression. Epigenetics2011; 6(3): 273–283
CrossRef Pubmed Google scholar
[44]
Wang X, Wang Y, Peng D, Huang W, Zhou X, Fu G. Changes in the inositol lipid signal system and effects on the secretion of TNF-α by macrophages in severely scalded mice. Burns2011; 37(8): 1378–1385
CrossRef Pubmed Google scholar
[45]
Wang Y, Peng D, Huang W, Zhou X, Liu J, Fang Y. Mechanism of altered TNF-α expression by macrophage and the modulatory effect of Panax notoginseng saponins in scald mice. Burns2006; 32(7): 846–852
CrossRef Pubmed Google scholar
[46]
Liu Y, Lin JD, Xiao XJ, Zhang BL, Lin H. An investigation of changes in gene expression profile of heart tissue in a rat sepsis model. Chin Crit Care Med (Zhongguo Wei Zhong Bing Ji Jiu Yi Xue)2009; 21(3): 155–159 (in Chinese)
Pubmed
[47]
Li ZJ, Li YP, Gai HR, Xue YL, Feng XZ. Research of gene expression profile of liver tissue in rat sepsis model. Chin Crit Care Med (Zhongguo Wei Zhong Bing Ji Jiu Yi Xue)2007; 19(3): 156–159 (in Chinese)
Pubmed
[48]
Cobb JP, Laramie JM, Stormo GD, Morrissey JJ, Shannon WD, Qiu Y, Karl IE, Buchman TG, Hotchkiss RS. Sepsis gene expression profiling: murine splenic compared with hepatic responses determined by using complementary DNA microarrays. Crit Care Med2002; 30(12): 2711–2721
CrossRef Pubmed Google scholar
[49]
Li L, Wang XP, Wu K. Change of gene expression spectra of leucocyte in sepsis mice. Chin J Emerg Med (Zhongguo Ji Zhen Yi Xue Za Zhi)2005; 14(2): 122–126 (in Chinese)
[50]
Lukaszewski RA, Yates AM, Jackson MC, Swingler K, Scherer JM, Simpson AJ, Sadler P, McQuillan P, Titball RW, Brooks TJ, Pearce MJ. Presymptomatic prediction of sepsis in intensive care unit patients. Clin Vaccine Immunol2008; 15(7): 1089–1094
CrossRef Pubmed Google scholar
[51]
Sutherland A, Thomas M, Brandon RA, Brandon RB, Lipman J, Tang B, McLean A, Pascoe R, Price G, Nguyen T, Stone G, Venter D. Development and validation of a novel molecular biomarker diagnostic test for the early detection of sepsis. Crit Care2011; 15(3): R149
CrossRef Pubmed Google scholar
[52]
Johnson SB, Lissauer M, Bochicchio GV, Moore R, Cross AS, Scalea TM. Gene expression profiles differentiate between sterile SIRS and early sepsis. Ann Surg2007; 245(4): 611–621
CrossRef Pubmed Google scholar
[53]
Wong HR. Clinical review: Sepsis and septic shock- the potential of gene arrays. Crit Care2012; 16(1): 204
CrossRef Google scholar
[54]
Reid G, Kirschner MB, van Zandwijk N. Circulating microRNAs: association with disease and potential use as biomarkers. Crit Rev Oncol Hematol2011; 80(2): 193–208
CrossRef Pubmed Google scholar
[55]
Chen X, Ba Y, Ma L, Cai X, Yin Y, Wang K, Guo J, Zhang Y, Chen J, Guo X, Li Q, Li X, Wang W, Zhang Y, Wang J, Jiang X, Xiang Y, Xu C, Zheng P, Zhang J, Li R, Zhang H, Shang X, Gong T, Ning G, Wang J, Zen K, Zhang J, Zhang CY. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res2008; 18(10): 997–1006
CrossRef Pubmed Google scholar
[56]
Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O’Briant KC, Allen A, Lin DW, Urban N, Drescher CW, Knudsen BS, Stirewalt DL, Gentleman R, Vessella RL, Nelson PS, Martin DB, Tewari M. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA2008; 105(30): 10513–10518
CrossRef Pubmed Google scholar
[57]
Lawrie CH, Gal S, Dunlop HM, Pushkaran B, Liggins AP, Pulford K, Banham AH, Pezzella F, Boultwood J, Wainscoat JS, Hatton CS, Harris AL. Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma. Br J Haematol2008; 141(5): 672–675
CrossRef Pubmed Google scholar
[58]
Hu Z, Chen X, Zhao Y, Tian T, Jin G, Shu Y, Chen Y, Xu L, Zen K, Zhang C, Shen H. Serum microRNA signatures identified in a genome-wide serum microRNA expression profiling predict survival of non-small-cell lung cancer. J Clin Oncol2010; 28(10): 1721–1726
CrossRef Pubmed Google scholar
[59]
Zhang Y, Liao Y, Wang D, He Y, Cao D, Zhang F, Dou K. Altered expression levels of miRNAs in serum as sensitive biomarkers for early diagnosis of traumatic injury. J Cell Biochem2011; 112(9): 2435–2442
CrossRef Pubmed Google scholar
[60]
Lorenzen JM, Kielstein JT, Hafer C, Gupta SK, Kümpers P, Faulhaber-Walter R, Haller H, Fliser D, Thum T. Circulating miR-210 predicts survival in critically ill patients with acute kidney injury. Clin J Am Soc Nephrol2011; 6(7): 1540–1546
CrossRef Pubmed Google scholar
[61]
Kong XY, Du YQ, Li L, Liu JQ, Wang GK, Zhu JQ, Man XH, Gong YF, Xiao LN, Zheng YZ, Deng SX, Gu JJ, Li ZS. Plasma miR-216a as a potential marker of pancreatic injury in a rat model of acute pancreatitis. World J Gastroenterol2010; 16(36): 4599–4604
CrossRef Pubmed Google scholar
[62]
Cermelli S, Ruggieri A, Marrero JA, Ioannou GN, Beretta L. Circulating microRNAs in patients with chronic hepatitis C and non-alcoholic fatty liver disease. PLoS ONE2011; 6(8): e23937
CrossRef Pubmed Google scholar
[63]
Vasilescu C, Rossi S, Shimizu M, Tudor S, Veronese A, Ferracin M, Nicoloso MS, Barbarotto E, Popa M, Stanciulea O, Fernandez MH, Tulbure D, Bueso-Ramos CE, Negrini M, Calin GA. MicroRNA fingerprints identify miR-150 as a plasma prognostic marker in patients with sepsis. PLoS ONE2009; 4(10): e7405
CrossRef Pubmed Google scholar
[64]
Zeng XL, Zhang SY, Zhang JF, Li FM, Ma XL, Mi YH. Expression of microRNA-150 in peripheral blood leukocytes in sepsis patients and its clinical significance. Chin J Respir Crit Care Med (Zhongguo Hu Xi Yu Wei Zhong Jian Hu Za Zhi)2011; 4(10): 360–364 (in Chinese)
[65]
Zeng XL, Zhang SY, Zhang JF, Yuan H, Wang Y. Expression of microRNA-143 in sepsis and its clinical significance. J Chin Pract Diag Ther (Zhonghua Shi Yong Zhen Duan Yu Zhi Liao Za Zhi)2011; 11: 1063–1066 (in Chinese)
[66]
Wang H, Meng K, Chen W, Feng D, Jia Y, Xie L. Serum miR-574-5p: a prognostic predictor of sepsis patients. Shock2012; 37(3): 263–267
CrossRef Pubmed Google scholar
[67]
Wang JF, Yu ML, Yu G, Bian JJ, Deng XM, Wan XJ, Zhu KM. Serum miR-146a and miR-223 as potential new biomarkers for sepsis. Biochem Biophys Res Commun2010; 394(1): 184–188
CrossRef Pubmed Google scholar
[68]
Peng X, Gralinski L, Armour CD, Ferris MT, Thomas MJ, Proll S, Bradel-Tretheway BG, Korth MJ, Castle JC, Biery MC, Bouzek HK, Haynor DR, Frieman MB, Heise M, Raymond CK, Baric RS, Katze MG. Unique signatures of long noncoding RNA expression in response to virus infection and altered innate immune signaling. MBio2010; 1(5): e00206-10, e00206-18
CrossRef Pubmed Google scholar
[69]
Siqueira-Batista R, de Mendonça EG, Patrícia Gomes A, Roger Vitorino R, Miyadahira R, Alvarez-Perez MC, de Almeida Oliveira MG. Proteomic updates on sepsis. Rev Assoc Med Bras2012; 58(3): 376–382
CrossRef Pubmed Google scholar
[70]
Zeng JZ, Zhang PH, Li LL, Ren LC, Liang PF, Huang XY. Proteomic study of peripheral blood lymphocytes of rabbits with severe burn and Pseudomonas aeruginosa sepsis. Chin Crit Care Med (Zhongguo Wei Zhong Bing Ji Jiu Yi Xue)2009; 21(8): 455–459 (in Chinese)
Pubmed
[71]
He XD, Zou Q, Chen ZD, Yan PE. Proteomic analysis of neutrophils of rats with Acinetobacter baumannii sepsis. Chin J Microbiol Immunol (Zhonghua Wei Sheng Wu Xue He Mian Yi Xue Za Zhi)2012; 32(5): 385–394 (in Chinese)
[72]
Hattori N, Oda S, Sadahiro T, Nakamura M, Abe R, Shinozaki K, Nomura F, Tomonaga T, Matsushita K, Kodera Y, Sogawa K, Satoh M, Hirasawa H. YKL-40 identified by proteomic analysis as a biomarker of sepsis. Shock2009; 32(4): 393–400
CrossRef Pubmed Google scholar
[73]
Paugam-Burtz C, Albuquerque M, Baron G, Bert F, Voitot H, Delefosse D, Dondero F, Sommacale D, Francoz C, Hanna N, Belghiti J, Ravaud P, Bedossa P, Mantz J, Paradis V. Plasma proteome to look for diagnostic biomarkers of early bacterial sepsis after liver transplantation: a preliminary study. Anesthesiology2010; 112(4): 926–935
CrossRef Pubmed Google scholar
[74]
Xu PB, Lin ZY, Meng HB, Yan SK, Yang Y, Liu XR, Li JB, Deng XM, Zhang WD. A metabonomic approach to early prognostic evaluation of experimental sepsis. J Infect2008; 56(6): 474–481
CrossRef Pubmed Google scholar
[75]
Izquierdo-García JL, Nin N, Ruíz-Cabello J, Rojas Y, de Paula M, López-Cuenca S, Morales L, Martínez-Caro L, Fernández-Segoviano P, Esteban A, Lorente JA. A metabolomic approach for diagnosis of experimental sepsis. Intensive Care Med2011; 37(12): 2023–2032
CrossRef Pubmed Google scholar
[76]
Lehmann LE, Hunfeld KP, Emrich T, Haberhausen G, Wissing H, Hoeft A, Stüber F. A multiplex real-time PCR assay for rapid detection and differentiation of 25 bacterial and fungal pathogens from whole blood samples. Med Microbiol Immunol (Berl)2008; 197(3): 313–324
CrossRef Pubmed Google scholar
[77]
Kim J, Gao L, Tan K. Multi-analyte network markers for tumor prognosis. PLoS ONE2012; 7(12): e52973
CrossRef Pubmed Google scholar

Acknowledgements

This review was supported by grants from the Supporting Program for Science and Technology Research of China (2009BAI87B03), the Medical Project of the Ministry of Health of China (201202002), and the Open Program Fund of State Key Laboratory of Trauma, Burns, and Combined Injury (SKLKF201311).
Compliance with ethics guidelines
Xiao Liu, Hui Ren, and Daizhi Peng declare that they have no conflicts of interest. This manuscript is a review article and does not involve a research protocol requiring approval by the relevant institutional review board or ethics committee.

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
AI Summary AI Mindmap
PDF(161 KB)

Accesses

Citations

Detail

Sections
Recommended

/