Skip to main content
SpringerLink
Log in

Early Diagnosis of Sepsis: Is an Integrated Omics Approach the Way Forward?

  • Review Article
  • Published:
Molecular Diagnosis & Therapy Aims and scope Submit manuscript

Abstract

Sepsis remains one of the leading causes of death in the USA and it is expected to get worse as the population ages. Moreover, the standard of care, which recommends aggressive treatment with appropriate antibiotics, has led to an increase in multiple drug-resistant organisms. There is a dire need for the development of new antibiotics, improved antibiotic stewardship, and therapies that treat the host response. Development of new sepsis therapeutics has been a disappointment as no drugs are currently approved to treat the various complications from sepsis. Much of the failure has been blamed on animal models that do not accurately reflect the course of the disease. However, recent improvements in metabolomic, transcriptomic, genomic, and proteomic platforms have allowed for a broad-spectrum look at molecular changes in the host response using clinical samples. Integration of these multi-omic datasets allows researchers to perform systems biology approaches to identify novel pathophysiology of the disease. In this review, we highlight what is currently known about sepsis and how integrative omics has identified new diagnostic and predictive models of sepsis as well as novel mechanisms. These changes may improve patient care as well as guide future preclinical analysis of sepsis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801–10. doi:10.1001/jama.2016.0287.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Fleischmann C, Scherag A, Adhikari NK, Hartog CS, Tsaganos T, Schlattmann P, et al. Assessment of global incidence and mortality of hospital-treated sepsis. Current estimates and limitations. Am J Respir Crit Care Med. 2016;193(3):259–72. doi:10.1164/rccm.201504-0781OC.

    Article  CAS  PubMed  Google Scholar 

  3. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001;29(7):1303–10.

    Article  CAS  PubMed  Google Scholar 

  4. Angus DC, van der Poll T. Severe sepsis and septic shock. N Engl J Med. 2013;369(9):840–51. doi:10.1056/NEJMra1208623.

    Article  CAS  PubMed  Google Scholar 

  5. Wong HR. Intensive care medicine in 2050: precision medicine. Intensive Care Med. 2017. doi:10.1007/s00134-017-4727-y (Epub 2017 Feb 24).

    PubMed  Google Scholar 

  6. Winters BD, Eberlein M, Leung J, Needham DM, Pronovost PJ, Sevransky JE. Long-term mortality and quality of life in sepsis: a systematic review. Crit Care Med. 2010;38(5):1276–83. doi:10.1097/CCM.0b013e3181d8cc1d.

    Article  PubMed  Google Scholar 

  7. Wischmeyer PE, San-Millan I. Winning the war against ICU-acquired weakness: new innovations in nutrition and exercise physiology. Crit Care. 2015;19(Suppl 3):S6. doi:10.1186/cc14724.

    PubMed  PubMed Central  Google Scholar 

  8. Battle CE, Davies G, Evans PA. Long term health-related quality of life in survivors of sepsis in South West Wales: an epidemiological study. PLoS One. 2014;9(12):e116304. doi:10.1371/journal.pone.0116304.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Puthucheary ZA, Rawal J, McPhail M, Connolly B, Ratnayake G, Chan P, et al. Acute skeletal muscle wasting in critical illness. JAMA. 2013;310(15):1591–600. doi:10.1001/jama.2013.278481.

    Article  CAS  PubMed  Google Scholar 

  10. Rocheteau P, Chatre L, Briand D, Mebarki M, Jouvion G, Bardon J, et al. Sepsis induces long-term metabolic and mitochondrial muscle stem cell dysfunction amenable by mesenchymal stem cell therapy. Nat Commun. 2015;6:10145. doi:10.1038/ncomms10145.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Morris PE, Griffin L, Berry M, Thompson C, Hite RD, Winkelman C, et al. Receiving early mobility during an intensive care unit admission is a predictor of improved outcomes in acute respiratory failure. Am J Med Sci. 2011;341(5):373–7. doi:10.1097/MAJ.0b013e31820ab4f6.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Morris PE, Berry MJ, Files DC, Thompson JC, Hauser J, Flores L, et al. Standardized rehabilitation and hospital length of stay among patients with acute respiratory failure: a randomized clinical trial. JAMA. 2016;315(24):2694–702. doi:10.1001/jama.2016.7201.

    Article  CAS  PubMed  Google Scholar 

  13. Rivers E, Nguyen B, Havstad S, Ressler J, Muzzin A, Knoblich B, et al. Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med. 2001;345(19):1368–77. doi:10.1056/NEJMoa010307.

    Article  CAS  PubMed  Google Scholar 

  14. Mikkelsen ME, Miltiades AN, Gaieski DF, Goyal M, Fuchs BD, Shah CV, et al. Serum lactate is associated with mortality in severe sepsis independent of organ failure and shock. Crit Care Med. 2009;37(5):1670–7. doi:10.1097/CCM.0b013e31819fcf68.

    Article  CAS  PubMed  Google Scholar 

  15. Liu V, Escobar GJ, Greene JD, Soule J, Whippy A, Angus DC, et al. Hospital deaths in patients with sepsis from 2 independent cohorts. JAMA. 2014;312(1):90–2. doi:10.1001/jama.2014.5804.

    Article  CAS  PubMed  Google Scholar 

  16. Shankar-Hari M, Phillips GS, Levy ML, Seymour CW, Liu VX, Deutschman CS, et al. Developing a new definition and assessing new clinical criteria for septic shock: for the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):775–87. doi:10.1001/jama.2016.0289.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Fleming-Dutra KE, Hersh AL, Shapiro DJ, Bartoces M, Enns EA, File TM Jr, et al. Prevalence of inappropriate antibiotic prescriptions among us ambulatory care visits, 2010–2011. JAMA. 2016;315(17):1864–73. doi:10.1001/jama.2016.4151.

    Article  CAS  PubMed  Google Scholar 

  18. Bratzler DW, Houck PM, Richards C, Steele L, Dellinger EP, Fry DE, et al. Use of antimicrobial prophylaxis for major surgery: baseline results from the National Surgical Infection Prevention Project. Arch Surg. 2005;140(2):174–82. doi:10.1001/archsurg.140.2.174.

    Article  PubMed  Google Scholar 

  19. Nizet V. Stopping superbugs, maintaining the microbiota. Sci Transl Med. 2015;7(295):295ed8. doi:10.1126/scitranslmed.aab2373.

  20. Ho YL, Sales VV, Joelsons D. Are early antibiotics important for everyone? Shock. 2017;47(1S Suppl 1):26–9. doi:10.1097/SHK.0000000000000696.

  21. Ting JY, Synnes A, Roberts A, Deshpandey A, Dow K, Yoon EW, et al. Association between antibiotic use and neonatal mortality and morbidities in very low-birth-weight infants without culture-proven sepsis or necrotizing enterocolitis. JAMA Pediatr. 2016;170(12):1181–7. doi:10.1001/jamapediatrics.2016.2132.

    Article  PubMed  Google Scholar 

  22. Hranjec T, Rosenberger LH, Swenson B, Metzger R, Flohr TR, Politano AD, et al. Aggressive versus conservative initiation of antimicrobial treatment in critically ill surgical patients with suspected intensive-care-unit-acquired infection: a quasi-experimental, before and after observational cohort study. Lancet Infect Dis. 2012;12(10):774–80. doi:10.1016/S1473-3099(12)70151-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Hranjec T, Sawyer RG. Conservative initiation of antimicrobial treatment in ICU patients with suspected ICU-acquired infection: more haste less speed. Curr Opin Crit Care. 2013;19(5):461–4. doi:10.1097/MCC.0b013e328364d525.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Seok J, Warren HS, Cuenca AG, Mindrinos MN, Baker HV, Xu W, Inflammation and Host Response to Injury, Large Scale Collaborative Research Program, et al. Genomic responses in mouse models poorly mimic human inflammatory diseases. Proc Natl Acad Sci USA. 2013;110(9):3507–12. doi:10.1073/pnas.1222878110.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kingsley SM, Bhat BV. Differential paradigms in animal models of sepsis. Curr Infect Dis Rep. 2016;18(9):26. doi:10.1007/s11908-016-0535-8.

    Article  PubMed  Google Scholar 

  26. Huber-Lang M, Barratt-Due A, Pischke SE, Sandanger O, Nilsson PH, Nunn MA, et al. Double blockade of CD14 and complement C5 abolishes the cytokine storm and improves morbidity and survival in polymicrobial sepsis in mice. J Immunol. 2014;192(11):5324–31. doi:10.4049/jimmunol.1400341.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Opal SM, Dellinger RP, Vincent JL, Masur H, Angus DC. The next generation of sepsis clinical trial designs: what is next after the demise of recombinant human activated protein C? Crit Care Med. 2014;42(7):1714–21. doi:10.1097/CCM.0000000000000325.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Hotchkiss RS, Monneret G, Payen D. Immunosuppression in sepsis: a novel understanding of the disorder and a new therapeutic approach. Lancet Infect Dis. 2013;13(3):260–8. doi:10.1016/S1473-3099(13)70001-X.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Shukla P, Rao GM, Pandey G, Sharma S, Mittapelly N, Shegokar R, et al. Therapeutic interventions in sepsis: current and anticipated pharmacological agents. Br J Pharmacol. 2014;171(22):5011–31. doi:10.1111/bph.12829.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Cohen J, Vincent JL, Adhikari NK, Machado FR, Angus DC, Calandra T, et al. Sepsis: a roadmap for future research. Lancet Infect Dis. 2015;15(5):581–614. doi:10.1016/S1473-3099(15)70112-X.

    Article  PubMed  Google Scholar 

  31. Patil NK, Bohannon JK, Sherwood ER. Immunotherapy: a promising approach to reverse sepsis-induced immunosuppression. Pharmacol Res. 2016;111:688–702. doi:10.1016/j.phrs.2016.07.019.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Heming N, Lamothe L, Ambrosi X, Annane D. Emerging drugs for the treatment of sepsis. Expert Opin Emerg Drugs. 2016;21(1):27–37. doi:10.1517/14728214.2016.1132700.

    Article  CAS  PubMed  Google Scholar 

  33. Singer M. Biomarkers in sepsis. Curr Opin Pulm Med. 2013;19(3):305–9. doi:10.1097/MCP.0b013e32835f1b49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Tsalik EL, Jaggers LB, Glickman SW, Langley RJ, van Velkinburgh JC, Park LP, et al. Discriminative value of inflammatory biomarkers for suspected sepsis. J Emerg Med. 2012;43(1):97–106. doi:10.1016/j.jemermed.2011.05.072.

    Article  PubMed  Google Scholar 

  35. Langley RJ, Tsalik EL, 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(195):195ra95. doi:10.1126/scitranslmed.3005893.

  36. Rogers AJ, McGeachie M, Baron RM, Gazourian L, Haspel JA, Nakahira K, et al. Metabolomic derangements are associated with mortality in critically ill adult patients. PLoS One. 2014;9(1):e87538. doi:10.1371/journal.pone.0087538.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. 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;190(4):445–55. doi:10.1164/rccm.201404-0624OC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Tsalik EL, Langley RJ, Dinwiddie DL, Miller NA, Yoo B, van Velkinburgh JC, et al. An integrated transcriptome and expressed variant analysis of sepsis survival and death. Genome Med. 2014;6(11):111. doi:10.1186/s13073-014-0111-5.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Tsalik EL, Willig LK, Rice BJ, van Velkinburgh JC, Mohney RP, McDunn JE, et al. Renal systems biology of patients with systemic inflammatory response syndrome. Kidney Int. 2015;88(4):804–14. doi:10.1038/ki.2015.150.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kamisoglu K, Haimovich B, Calvano SE, Coyle SM, Corbett SA, Langley RJ, et al. Human metabolic response to systemic inflammation: assessment of the concordance between experimental endotoxemia and clinical cases of sepsis/SIRS. Crit Care. 2015;19:71. doi:10.1186/s13054-015-0783-2.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Tsalik EL, Henao R, Nichols M, Burke T, Ko ER, McClain MT, et al. Host gene expression classifiers diagnose acute respiratory illness etiology. Sci Transl Med. 2016;8(322):322ra11. doi:10.1126/scitranslmed.aad6873.

  42. Hurd PJ, Nelson CJ. Advantages of next-generation sequencing versus the microarray in epigenetic research. Brief Funct Genomic Proteomic. 2009;8(3):174–83. doi:10.1093/bfgp/elp013.

    Article  CAS  PubMed  Google Scholar 

  43. Langlais D, Fodil N, Gros P. Genetics of infectious and inflammatory diseases: overlapping discoveries from association and exome-sequencing studies. Annu Rev Immunol. 2016. doi:10.1146/annurev-immunol-051116-052442 (Epub 2016 Dec 1).

    PubMed  Google Scholar 

  44. Tada H, Kawashiri MA, Konno T, Yamagishi M, Hayashi K. Common and rare variant association study for plasma lipids and coronary artery disease. J Atheroscler Thromb. 2016;23(3):241–56. doi:10.5551/jat.31393.

    Article  CAS  PubMed  Google Scholar 

  45. Kingsmore SF, Lindquist IE, Mudge J, Gessler DD, Beavis WD. Genome-wide association studies: progress and potential for drug discovery and development. Nat Rev Drug Discov. 2008;7(3):221–30. doi:10.1038/nrd2519.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Bashiardes S, Zilberman-Schapira G, Elinav E. Use of metatranscriptomics in microbiome research. Bioinform Biol Insights. 2016;10:19–25. doi:10.4137/BBI.S34610.

    PubMed  PubMed Central  Google Scholar 

  47. Kingsmore SF, Petrikin J, Willig LK, Guest E. Emergency medical genomes: a breakthrough application of precision medicine. Genome Med. 2015;7(1):82. doi:10.1186/s13073-015-0201-z.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Castellana S, Mazza T. Congruency in the prediction of pathogenic missense mutations: state-of-the-art web-based tools. Brief Bioinform. 2013;14(4):448–59. doi:10.1093/bib/bbt013.

    Article  CAS  PubMed  Google Scholar 

  49. Mardis ER. The $1,000 genome, the $100,000 analysis? Genome Med. 2010;2(11):84. doi:10.1186/gm205.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Markley JL, Bruschweiler R, Edison AS, Eghbalnia HR, Powers R, Raftery D, et al. The future of NMR-based metabolomics. Curr Opin Biotechnol. 2017;43:34–40. doi:10.1016/j.copbio.2016.08.001.

    Article  CAS  PubMed  Google Scholar 

  51. Johnson CH, Ivanisevic J, Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol. 2016;17(7):451–9. doi:10.1038/nrm.2016.25.

    Article  CAS  PubMed  Google Scholar 

  52. Duarte TT, Spencer CT. Personalized proteomics: the future of precision medicine. Proteomes. 2016;4(4):29. doi:10.3390/proteomes4040029.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Thiviyanathan V, Gorenstein DG. Aptamers and the next generation of diagnostic reagents. Proteomics Clin Appl. 2012;6(11–12):563–73. doi:10.1002/prca.201200042.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Tighe PJ, Ryder RR, Todd I, Fairclough LC. ELISA in the multiplex era: potentials and pitfalls. Proteomics Clin Appl. 2015;9(3–4):406–22. doi:10.1002/prca.201400130.

    Article  CAS  PubMed  Google Scholar 

  55. Sharma NK, Salomao R. Sepsis through the eyes of proteomics: the progress in the last decade. Shock. 2017;47(1S Suppl 1):17-25. doi:10.1097/SHK.0000000000000698.

  56. Chiu CY. Viral pathogen discovery. Curr Opin Microbiol. 2013;16(4):468–78. doi:10.1016/j.mib.2013.05.001.

    Article  CAS  PubMed  Google Scholar 

  57. Berg MG, Lee D, Coller K, Frankel M, Aronsohn A, Cheng K, et al. Discovery of a novel human pegivirus in blood associated with hepatitis C virus co-infection. PLoS Pathog. 2015;11(12):e1005325. doi:10.1371/journal.ppat.1005325.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Dhas DB, Ashmi AH, Bhat BV, Kalaivani S, Parija SC. Comparison of genomic DNA methylation pattern among septic and non-septic newborns - an epigenome wide association study. Genom Data. 2015;3:36–40. doi:10.1016/j.gdata.2014.11.004.

    Article  PubMed  Google Scholar 

  59. Weiterer S, Uhle F, Lichtenstern C, Siegler BH, Bhuju S, Jarek M, et al. Sepsis induces specific changes in histone modification patterns in human monocytes. PLoS One. 2015;10(3):e0121748. doi:10.1371/journal.pone.0121748.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Pastukh V, Roberts JT, Clark DW, Bardwell GC, Patel M, Al-Mehdi AB, et al. An oxidative DNA “damage” and repair mechanism localized in the VEGF promoter is important for hypoxia-induced VEGF mRNA expression. Am J Physiol Lung Cell Mol Physiol. 2015;309(11):L1367–75. doi:10.1152/ajplung.00236.2015.

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Ho J, Chan H, Wong SH, Wang MH, Yu J, Xiao Z, et al. The involvement of regulatory non-coding RNAs in sepsis: a systematic review. Crit Care. 2016;20(1):383. doi:10.1186/s13054-016-1555-3.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Bauer M, Reinhart K. Molecular diagnostics of sepsis–where are we today? Int J Med Microbiol. 2010;300(6):411–3. doi:10.1016/j.ijmm.2010.04.006.

    Article  CAS  PubMed  Google Scholar 

  63. Tsalik EL, Jones D, Nicholson B, Waring L, Liesenfeld O, Park LP, et al. Multiplex PCR to diagnose bloodstream infections in patients admitted from the emergency department with sepsis. J Clin Microbiol. 2010;48(1):26–33. doi:10.1128/JCM.01447-09.

    Article  CAS  PubMed  Google Scholar 

  64. Warhurst G, Dunn G, Chadwick P, Blackwood B, McAuley D, Perkins GD, et al. Rapid detection of health-care-associated bloodstream infection in critical care using multipathogen real-time polymerase chain reaction technology: a diagnostic accuracy study and systematic review. Health Technol Assess. 2015;19(35):1–142. doi:10.3310/hta19350.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Ko ER, Yang WE, McClain MT, Woods CW, Ginsburg GS, Tsalik EL. What was old is new again: using the host response to diagnose infectious disease. Expert Rev Mol Diagn. 2015;15(9):1143–58. doi:10.1586/14737159.2015.1059278.

    Article  CAS  PubMed  Google Scholar 

  66. Tang BM, Huang SJ, McLean AS. Genome-wide transcription profiling of human sepsis: a systematic review. Crit Care. 2010;14(6):R237. doi:10.1186/cc9392.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Mahajan P, Kuppermann N, Mejias A, Suarez N, Chaussabel D, Casper TC, et al. Association of RNA biosignatures with bacterial infections in febrile infants aged 60 days or younger. JAMA. 2016;316(8):846–57. doi:10.1001/jama.2016.9207.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Herberg JA, Kaforou M, Wright VJ, Shailes H, Eleftherohorinou H, Hoggart CJ, et al. Diagnostic test accuracy of a 2-transcript host RNA signature for discriminating bacterial vs viral infection in febrile children. JAMA. 2016;316(8):835–45. doi:10.1001/jama.2016.11236.

    Article  PubMed  Google Scholar 

  69. Sweeney TE, Wong HR, Khatri P. Robust classification of bacterial and viral infections via integrated host gene expression diagnostics. Sci Transl Med. 2016;8(346):346ra91. doi:10.1126/scitranslmed.aaf7165.

  70. Sweeney TE, Shidham A, Wong HR, Khatri P. A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set. Sci Transl Med. 2015;7(287):287ra71. doi:10.1126/scitranslmed.aaa5993.

  71. Niemz A, Ferguson TM, Boyle DS. Point-of-care nucleic acid testing for infectious diseases. Trends Biotechnol. 2011;29(5):240–50. doi:10.1016/j.tibtech.2011.01.007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Otero RM, Nguyen HB, Huang DT, Gaieski DF, Goyal M, Gunnerson KJ, et al. Early goal-directed therapy in severe sepsis and septic shock revisited: concepts, controversies, and contemporary findings. Chest. 2006;130(5):1579–95.

    Article  PubMed  Google Scholar 

  73. Loiacono LA, Shapiro DS. Detection of hypoxia at the cellular level. Crit Care Clin. 2010;26(2):409–21. doi:10.1016/j.ccc.2009.12.001.

    Article  CAS  PubMed  Google Scholar 

  74. Singer M. The role of mitochondrial dysfunction in sepsis-induced multi-organ failure. Virulence. 2014;5(1):66–72. doi:10.4161/viru.26907.

    Article  PubMed  Google Scholar 

  75. 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(4):383–90.

    Article  PubMed  PubMed Central  Google Scholar 

  76. 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(195):195ra95. doi:10.1126/scitranslmed.3005893.

  77. Seymour CW, Yende S, Scott MJ, Pribis J, Mohney RP, Bell LN, et al. Metabolomics in pneumonia and sepsis: an analysis of the GenIMS cohort study. Intensive Care Med. 2013;39(8):1423–34. doi:10.1007/s00134-013-2935-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Neugebauer S, Giamarellos-Bourboulis EJ, Pelekanou A, Marioli A, Baziaka F, Tsangaris I, et al. Metabolite profiles in sepsis: developing prognostic tools based on the type of infection. Crit Care Med. 2016;44(9):1649–62. doi:10.1097/CCM.0000000000001740.

    Article  CAS  PubMed  Google Scholar 

  79. Ferrario M, Cambiaghi A, Brunelli L, Giordano S, Caironi P, Guatteri L, et al. Mortality prediction in patients with severe septic shock: a pilot study using a target metabolomics approach. Sci Rep. 2016;6:20391. doi:10.1038/srep20391.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Houten SM, Wanders RJ. A general introduction to the biochemistry of mitochondrial fatty acid beta-oxidation. J Inherit Metab Dis. 2010;33(5):469–77. doi:10.1007/s10545-010-9061-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Wiel E, Lebuffe G, Robin E, Gasan G, Corseaux D, Tavernier B, et al. Pretreatment with peroxysome proliferator-activated receptor alpha agonist fenofibrate protects endothelium in rabbit Escherichia coli endotoxin-induced shock. Intensive Care Med. 2005;31(9):1269–79. doi:10.1007/s00134-005-2730-1.

    Article  PubMed  Google Scholar 

  82. Kapoor A, Shintani Y, Collino M, Osuchowski MF, Busch D, Patel NS, et al. Protective role of peroxisome proliferator-activated receptor-beta/delta in septic shock. Am J Respir Crit Care Med. 2010;182(12):1506–15. doi:10.1164/rccm.201002-0240OC.

    Article  CAS  PubMed  Google Scholar 

  83. Zingarelli B, Piraino G, Hake PW, O’Connor M, Denenberg A, Fan H, et al. Peroxisome proliferator-activated receptor δ regulates inflammation via NF-κB signaling in polymicrobial sepsis. Am J Pathol. 2010;177(4):1834–47. doi:10.2353/ajpath.2010.091010.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Wu WT, Lee CC, Lee CJ, Subeq YM, Lee RP, Hsu BG. Rosiglitazone ameliorates endotoxin-induced organ damage in conscious rats. Biol Res Nurs. 2011;13(1):38–43. doi:10.1177/1099800409353358.

    Article  CAS  PubMed  Google Scholar 

  85. Standage SW, Caldwell CC, Zingarelli B, Wong HR. Reduced peroxisome proliferator-activated receptor alpha expression is associated with decreased survival and increased tissue bacterial load in sepsis. Shock. 2012;37(2):164–9. doi:10.1097/SHK.0b013e31823f1a00.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Smeding L, Leong-Poi H, Hu P, Shan Y, Haitsma JJ, Horvath E, et al. Salutary effect of resveratrol on sepsis-induced myocardial depression. Crit Care Med. 2012;40(6):1896–907. doi:10.1097/CCM.0b013e31824e1370.

    Article  CAS  PubMed  Google Scholar 

  87. Bermejo-Martin JF, Andaluz-Ojeda D, Almansa R, Gandia F, Gomez-Herreras JI, Gomez-Sanchez E, et al. Defining immunological dysfunction in sepsis: A requisite tool for precision medicine. J Infect. 2016;72(5):525–36. doi:10.1016/j.jinf.2016.01.010.

    Article  PubMed  Google Scholar 

  88. Hotchkiss RS, Monneret G, Payen D. Sepsis-induced immunosuppression: from cellular dysfunctions to immunotherapy. Nat Rev Immunol. 2013;13(12):862–74. doi:10.1038/nri3552.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Chen BB, Coon TA, Glasser JR, Zou C, Ellis B, Das T, et al. E3 ligase subunit Fbxo15 and PINK1 kinase regulate cardiolipin synthase 1 stability and mitochondrial function in pneumonia. Cell Rep. 2014;7(2):476–87. doi:10.1016/j.celrep.2014.02.048.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Ray NB, Durairaj L, Chen BB, McVerry BJ, Ryan AJ, Donahoe M, et al. Dynamic regulation of cardiolipin by the lipid pump Atp8b1 determines the severity of lung injury in experimental pneumonia. Nat Med. 2010;16(10):1120–7. doi:10.1038/nm.2213.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Nakahira K, Kyung SY, Rogers AJ, Gazourian L, Youn S, Massaro AF, et al. Circulating mitochondrial DNA in patients in the ICU as a marker of mortality: derivation and validation. PLoS Med. 2013;10(12):e1001577. doi:10.1371/journal.pmed.1001577 (discussion e1001577).

  92. Simmons JD, Freno DR, Muscat CA, Obiako B, Lee YL, Pastukh VM, et al. Mitochondrial DNA damage associated molecular patterns in ventilator-associated pneumonia: prevention and reversal by intratracheal DNase I. J Trauma Acute Care Surg. 2017;82(1):120–5. doi:10.1097/TA.0000000000001269.

    Article  CAS  PubMed  Google Scholar 

  93. Kuck JL, Obiako BO, Gorodnya OM, Pastukh VM, Kua J, Simmons JD, et al. Mitochondrial DNA damage-associated molecular patterns mediate a feed-forward cycle of bacteria-induced vascular injury in perfused rat lungs. Am J Physiol Lung Cell Mol Physiol. 2015;308(10):L1078–85. doi:10.1152/ajplung.00015.2015.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Schafer ST, Franken L, Adamzik M, Schumak B, Scherag A, Engler A, et al. Mitochondrial DNA: an endogenous trigger for immune paralysis. Anesthesiology. 2016;124(4):923–33. doi:10.1097/ALN.0000000000001008.

    Article  PubMed  CAS  Google Scholar 

  95. Tannahill GM, Curtis AM, Adamik J, Palsson-McDermott EM, McGettrick AF, Goel G, et al. Succinate is an inflammatory signal that induces IL-1beta through HIF-1alpha. Nature. 2013;496(7444):238–42. doi:10.1038/nature11986.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Cheng SC, Scicluna BP, Arts RJ, Gresnigt MS, Lachmandas E, Giamarellos-Bourboulis EJ, et al. Broad defects in the energy metabolism of leukocytes underlie immunoparalysis in sepsis. Nat Immunol. 2016;17(4):406–13. doi:10.1038/ni.3398.

    Article  CAS  PubMed  Google Scholar 

  97. Liu TF, Vachharajani V, Millet P, Bharadwaj MS, Molina AJ, McCall CE. Sequential actions of SIRT1-RELB-SIRT3 coordinate nuclear-mitochondrial communication during immunometabolic adaptation to acute inflammation and sepsis. J Biol Chem. 2015;290(1):396–408. doi:10.1074/jbc.M114.566349.

    Article  CAS  PubMed  Google Scholar 

  98. Vachharajani VT, Liu T, Brown CM, Wang X, Buechler NL, Wells JD, et al. SIRT1 inhibition during the hypoinflammatory phenotype of sepsis enhances immunity and improves outcome. J Leukoc Biol. 2014;96(5):785–96. doi:10.1189/jlb.3MA0114-034RR.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  99. Herridge MS, Tansey CM, Matte A, Tomlinson G, Diaz-Granados N, Cooper A, et al. Functional disability 5 years after acute respiratory distress syndrome. N Engl J Med. 2011;364(14):1293–304. doi:10.1056/NEJMoa1011802.

    Article  CAS  PubMed  Google Scholar 

  100. Wang X, Gu H, Qin D, Yang L, Huang W, Essandoh K, et al. Exosomal miR-223 contributes to mesenchymal stem cell-elicited cardioprotection in polymicrobial sepsis. Sci Rep. 2015;5:13721. doi:10.1038/srep13721.

    Article  PubMed  PubMed Central  Google Scholar 

  101. Bone RC, Balk RA, Cerra FB, Dellinger RP, Fein AM, Knaus WA, et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest. 1992;101(6):1644–55.

    Article  CAS  PubMed  Google Scholar 

  102. Sorensen TI, Nielsen GG, Andersen PK, Teasdale TW. Genetic and environmental influences on premature death in adult adoptees. N Engl J Med. 1988;318(12):727–32. doi:10.1056/NEJM198803243181202.

    Article  CAS  PubMed  Google Scholar 

  103. Hartel C, Schultz C, Herting E, Gopel W. Genetic association studies in VLBW infants exemplifying susceptibility to sepsis–recent findings and implications for future research. Acta Paediatr. 2007;96(2):158–65.

    Article  PubMed  Google Scholar 

  104. Jepson AP, Banya WA, Sisay-Joof F, Hassan-King M, Bennett S, Whittle HC. Genetic regulation of fever in Plasmodium falciparum malaria in Gambian twin children. J Infect Dis. 1995;172(1):316–9.

    Article  CAS  PubMed  Google Scholar 

  105. Densen P, Weiler JM, Griffiss JM, Hoffmann LG. Familial properdin deficiency and fatal meningococcemia. Correction of the bactericidal defect by vaccination. N Engl J Med. 1987;316(15):922–6. doi:10.1056/NEJM198704093161506.

    Article  CAS  PubMed  Google Scholar 

  106. Smirnova I, Mann N, Dols A, Derkx HH, Hibberd ML, Levin M, et al. Assay of locus-specific genetic load implicates rare Toll-like receptor 4 mutations in meningococcal susceptibility. Proc Natl Acad Sci USA. 2003;100(10):6075–80. doi:10.1073/pnas.10316051001031605100.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Drennan MB, Nicolle D, Quesniaux VJ, Jacobs M, Allie N, Mpagi J, et al. Toll-like receptor 2-deficient mice succumb to Mycobacterium tuberculosis infection. Am J Pathol. 2004;164(1):49–57. doi:10.1016/S0002-9440(10)63095-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Liu R, Paxton WA, Choe S, Ceradini D, Martin SR, Horuk R, et al. Homozygous defect in HIV-1 coreceptor accounts for resistance of some multiply-exposed individuals to HIV-1 infection. Cell. 1996;86(3):367–77 (pii: S0092-8674(00)80110-5).

    Article  CAS  PubMed  Google Scholar 

  109. Samson M, Libert F, Doranz BJ, Rucker J, Liesnard C, Farber CM, et al. Resistance to HIV-1 infection in caucasian individuals bearing mutant alleles of the CCR-5 chemokine receptor gene. Nature. 1996;382(6593):722–5. doi:10.1038/382722a0.

    Article  CAS  PubMed  Google Scholar 

  110. Skamene E, Schurr E, Gros P. Infection genomics: Nramp1 as a major determinant of natural resistance to intracellular infections. Annu Rev Med. 1998;49:275–87. doi:10.1146/annurev.med.49.1.275.

    Article  CAS  PubMed  Google Scholar 

  111. Arcaroli J, Fessler MB, Abraham E. Genetic polymorphisms and sepsis. Shock. 2005;24(4):300–12. doi:10.1097/01.shk.0000180621.52058.e1.

    Article  CAS  PubMed  Google Scholar 

  112. Lin MT, Albertson TE. Genomic polymorphisms in sepsis. Crit Care Med. 2004;32(2):569–79. doi:10.1097/01.CCM.0000110878.49476.42.

    Article  CAS  PubMed  Google Scholar 

  113. Majetschak M, Obertacke U, Schade FU, Bardenheuer M, Voggenreiter G, Bloemeke B, et al. Tumor necrosis factor gene polymorphisms, leukocyte function, and sepsis susceptibility in blunt trauma patients. Clin Diagn Lab Immunol. 2002;9(6):1205–11.

    CAS  PubMed  PubMed Central  Google Scholar 

  114. Mira JP, Cariou A, Grall F, Delclaux C, Losser MR, Heshmati F, et al. Association of TNF2, a TNF-alpha promoter polymorphism, with septic shock susceptibility and mortality: a multicenter study. JAMA. 1999;282(6):561–8. doi:10.1001/jama.282.6.561.

    Article  CAS  PubMed  Google Scholar 

  115. Botstein D, Risch N. Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nat Genet. 2003;33(Suppl):228–37. doi:10.1038/ng1090ng1090.

    Article  CAS  PubMed  Google Scholar 

  116. Freimer N, Sabatti C. The use of pedigree, sib-pair and association studies of common diseases for genetic mapping and epidemiology. Nat Genet. 2004;36(10):1045–51. doi:10.1038/ng1433ng1433.

    Article  CAS  PubMed  Google Scholar 

  117. Hill AV. Aspects of genetic susceptibility to human infectious diseases. Annu Rev Genet. 2006;40:469–86. doi:10.1146/annurev.genet.40.110405.090546.

    Article  CAS  PubMed  Google Scholar 

  118. Gorlov IP, Gorlova OY, Frazier ML, Spitz MR, Amos CI. Evolutionary evidence of the effect of rare variants on disease etiology. Clin Genet. 2011;79(3):199–206. doi:10.1111/j.1399-0004.2010.01535.x.

    Article  CAS  PubMed  Google Scholar 

  119. Dewey FE, Murray MF, Overton JD, Habegger L, Leader JB, Fetterolf SN, et al. Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study. Science. 2016;354(6319):aaf6814. doi:10.1126/science.aaf6814.

  120. Walley KR, Thain KR, Russell JA, Reilly MP, Meyer NJ, Ferguson JF, et al. PCSK9 is a critical regulator of the innate immune response and septic shock outcome. Sci Transl Med. 2014;6(258):258ra143. doi:10.1126/scitranslmed.3008782.

  121. Zeng C, Guo X, Long J, Kuchenbaecker KB, Droit A, Michailidou K, et al. Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus. Breast Cancer Res. 2016;18(1):64. doi:10.1186/s13058-016-0718-0.

    Article  PubMed  PubMed Central  Google Scholar 

  122. Krumsiek J, Suhre K, Evans AM, Mitchell MW, Mohney RP, Milburn MV, et al. Mining the unknown: a systems approach to metabolite identification combining genetic and metabolic information. PLoS Genet. 2012;8(10):e1003005. doi:10.1371/journal.pgen.1003005.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Petersen AK, Zeilinger S, Kastenmuller G, Romisch-Margl W, Brugger M, Peters A, et al. Epigenetics meets metabolomics: an epigenome-wide association study with blood serum metabolic traits. Hum Mol Genet. 2014;23(2):534–45. doi:10.1093/hmg/ddt430.

    Article  CAS  PubMed  Google Scholar 

  124. O’Dwyer MJ, Dempsey F, Crowley V, Kelleher DP, McManus R, Ryan T. Septic shock is correlated with asymmetrical dimethyl arginine levels, which may be influenced by a polymorphism in the dimethylarginine dimethylaminohydrolase II gene: a prospective observational study. Crit Care. 2006;10(5):R139. doi:10.1186/cc5053.

    Article  PubMed  PubMed Central  Google Scholar 

  125. Leiper J, Gordon A. Plasma asymmetric dimethylarginine (ADMA) association with risk of death in septic shock—subgroup analysis of patients from the VANISH trial [abstract] A104]. Critical Care: Sepsis Translational Insights. American Thoracic Society 2016 International Conference, May 13–18, 2016, San Francisco. Am J Respir Crit Care Med. 2016;193:A2723-A.

  126. Leiper J, Gordon A. The rs805305 SNP of dimethylarginine dimethylaminohydrolase 2(DDAH2) is associated with reduced duration of shock, improved mortality and an elevated plasma ADMA:SDMA ratio in septic shock - subgroup analysis of patients from the VANISH trial [abstract]. A104. Critical Care: Sepsis Translational Insights. American Thoracic Society 2016 International Conference, May 13–18, 2016, San Francisco. Am J Respir Crit Care Med. 2016;193:A7800-A.

  127. Wang Z, Lambden S, Taylor V, Sujkovic E, Nandi M, Tomlinson J, et al. Pharmacological inhibition of DDAH1 improves survival, haemodynamics and organ function in experimental septic shock. Biochem J. 2014;460(2):309–16. doi:10.1042/BJ20131666.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Pharmacology, University of South Alabama, Mobile, AL, USA

    Raymond J. Langley

  2. Division of Critical Care Medicine, Cincinnati Children’s Hospital Medical Center and Cincinnati Children’s Research Foundation, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA

    Hector R. Wong

  3. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA

    Hector R. Wong

Authors
  1. Raymond J. Langley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hector R. Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hector R. Wong.

Ethics declarations

Conflict of interest

RJL and HRW declare that they have no competing interests.

Funding

RJL is supported by the National Institutes of Health (NIH) (UL1TR001417) and the Defense Advanced Research Projects and the Army Research Office (W911NF-15-1-0107); HRW is supported by the NIH (R01GM099773 and R01GM108025).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Langley, R.J., Wong, H.R. Early Diagnosis of Sepsis: Is an Integrated Omics Approach the Way Forward?. Mol Diagn Ther 21, 525–537 (2017). https://doi.org/10.1007/s40291-017-0282-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40291-017-0282-z

Search

Navigation