Download PDF
J Pediatr Intensive Care 2019; 08(01): 011-016
DOI: 10.1055/s-0038-1677537
Review Article
Georg Thieme Verlag KG Stuttgart · New York

Sepsis Biomarkers

Hector R. Wong
1   Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, Ohio, United States
2   Department of Pediatrics, University of Cincinnati College of Medicine, University of Cincinnati, Cincinnati, Ohio, United States
› Author Affiliations
Further Information

Publication History

05 December 2018

12 December 2018

Publication Date:
11 January 2019 (online)

    Permissions and Reprints

Abstract

Sepsis-related biomarkers have a variety of potential applications. The most well-known application is to differentiate patients with signs of systemic inflammation caused by infection, from those with systemic inflammation due to a non-infectious cause. This application is important for timely and judicious prescription of antibiotics. Apart from diagnostic applications, biomarkers can also be used to identify patients with sepsis who are at risk for poor outcome and to subgroup patients with sepsis based on biological commonalities. The latter two applications embody the concepts of prognostic and predictive enrichment, which are fundamental to precision medicine. This review will elaborate on these concepts, provide relevant examples, and discuss important considerations in the process of biomarkers discovery and development.

Keywords

biomarkers - sepsis - diagnostic
 

  • References

  • 1 Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001; 69 (03) 89-95
    CrossrefPubMedGoogle Scholar
  • 2 Marshall JC, Reinhart K. ; International Sepsis Forum. Biomarkers of sepsis. Crit Care Med 2009; 37 (07) 2290-2298
    CrossrefPubMedGoogle Scholar
  • 3 Temple R. Enrichment of clinical study populations. Clin Pharmacol Ther 2010; 88 (06) 774-778
    PubMedGoogle Scholar
  • 4 Ramilo O, Rodriguez-Fernandez R, Mejias A. Promise and limitations of procalcitonin to identify bacterial infections in the pediatric intensive care unit. J Pediatr 2016; 179: 7-9
    CrossrefPubMedGoogle Scholar
  • 5 Pierce R, Bigham MT, Giuliano Jr JS. Use of procalcitonin for the prediction and treatment of acute bacterial infection in children. Curr Opin Pediatr 2014; 26 (03) 292-298
    CrossrefPubMedGoogle Scholar
  • 6 Tang BM, Eslick GD, Craig JC, McLean AS. Accuracy of procalcitonin for sepsis diagnosis in critically ill patients: systematic review and meta-analysis. Lancet Infect Dis 2007; 7 (03) 210-217
    CrossrefPubMedGoogle Scholar
  • 7 Lautz AJ, Dziorny AC, Denson AR. , et al. Value of procalcitonin measurement for early evidence of severe bacterial infections in the pediatric intensive care unit. J Pediatr 2016; 179: 74-81.e2
    CrossrefPubMedGoogle Scholar
  • 8 Schuetz P, Müller B, Christ-Crain M. , et al. Procalcitonin to initiate or discontinue antibiotics in acute respiratory tract infections. Cochrane Database Syst Rev 2012; (09) CD007498
    PubMedGoogle Scholar
  • 9 Prkno A, Wacker C, Brunkhorst FM, Schlattmann P. Procalcitonin-guided therapy in intensive care unit patients with severe sepsis and septic shock--a systematic review and meta-analysis. Crit Care 2013; 17 (06) R291
    CrossrefPubMedGoogle Scholar
  • 10 Kopterides P, Siempos II, Tsangaris I, Tsantes A, Armaganidis A. Procalcitonin-guided algorithms of antibiotic therapy in the intensive care unit: a systematic review and meta-analysis of randomized controlled trials. Crit Care Med 2010; 38 (11) 2229-2241
    CrossrefPubMedGoogle Scholar
  • 11 Schuetz P, Chiappa V, Briel M, Greenwald JL. Procalcitonin algorithms for antibiotic therapy decisions: a systematic review of randomized controlled trials and recommendations for clinical algorithms. Arch Intern Med 2011; 171 (15) 1322-1331
    CrossrefPubMedGoogle Scholar
  • 12 Matthaiou DK, Ntani G, Kontogiorgi M, Poulakou G, Armaganidis A, Dimopoulos G. An ESICM systematic review and meta-analysis of procalcitonin-guided antibiotic therapy algorithms in adult critically ill patients. Intensive Care Med 2012; 38 (06) 940-949
    CrossrefPubMedGoogle Scholar
  • 13 Heyland DK, Johnson AP, Reynolds SC, Muscedere J. Procalcitonin for reduced antibiotic exposure in the critical care setting: a systematic review and an economic evaluation. Crit Care Med 2011; 39 (07) 1792-1799
    CrossrefPubMedGoogle Scholar
  • 14 Schuetz P, Albrich W, Mueller B. Procalcitonin for diagnosis of infection and guide to antibiotic decisions: past, present and future. BMC Med 2011; 9: 107
    CrossrefPubMedGoogle Scholar
  • 15 Sandquist M, Wong HR. Biomarkers of sepsis and their potential value in diagnosis, prognosis and treatment. Expert Rev Clin Immunol 2014; 10 (10) 1349-1356
    CrossrefPubMedGoogle Scholar
  • 16 Jacobs L, Wong HR. Emerging infection and sepsis biomarkers: will they change current therapies?. Expert Rev Anti Infect Ther 2016; 14 (10) 929-941
    CrossrefPubMedGoogle Scholar
  • 17 Wong HR, Cvijanovich NZ, Hall M. , et al. Interleukin-27 is a novel candidate diagnostic biomarker for bacterial infection in critically ill children. Crit Care 2012; 16 (05) R213
    CrossrefPubMedGoogle Scholar
  • 18 Hanna WJ, Berrens Z, Langner T, Lahni P, Wong HR. Interleukin-27: a novel biomarker in predicting bacterial infection among the critically ill. Crit Care 2015; 19: 378
    CrossrefPubMedGoogle Scholar
  • 19 Wong HR, Liu KD, Kangelaris KN, Lahni P, Calfee CS. Performance of interleukin-27 as a sepsis diagnostic biomarker in critically ill adults. J Crit Care 2014; 29 (05) 718-722
    CrossrefPubMedGoogle Scholar
  • 20 Wong HR, Lindsell CJ, Lahni P, Hart KW, Gibot S. Interleukin 27 as a sepsis diagnostic biomarker in critically ill adults. Shock 2013; 40 (05) 382-386
    CrossrefPubMedGoogle Scholar
  • 21 Gibot S, Béné MC, Noel R. , et al. Combination biomarkers to diagnose sepsis in the critically ill patient. Am J Respir Crit Care Med 2012; 186 (01) 65-71
    CrossrefPubMedGoogle Scholar
  • 22 Sweeney TE, Khatri P. Comprehensive validation of the FAIM3: PLAC8 ratio in time-matched public gene expression data. Am J Respir Crit Care Med 2015; 192 (10) 1260-1261
    CrossrefPubMedGoogle Scholar
  • 23 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
    CrossrefPubMedGoogle Scholar
  • 24 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
    CrossrefPubMedGoogle Scholar
  • 25 Mahajan P, Kuppermann N, Mejias A. , et al; Pediatric Emergency Care Applied Research Network (PECARN). Association of RNA biosignatures with bacterial infections in febrile infants aged 60 days or younger. JAMA 2016; 316 (08) 846-857
    CrossrefPubMedGoogle Scholar
  • 26 Herberg JA, Kaforou M, Wright VJ. , et al; IRIS Consortium. Diagnostic test accuracy of a 2-transcript host RNA signature for discriminating bacterial vs viral infection in febrile children. JAMA 2016; 316 (08) 835-845
    CrossrefPubMedGoogle Scholar
  • 27 Wong HR, Cvijanovich N, Wheeler DS. , et al. Interleukin-8 as a stratification tool for interventional trials involving pediatric septic shock. Am J Respir Crit Care Med 2008; 178 (03) 276-282
    CrossrefPubMedGoogle Scholar
  • 28 Calfee CS, Thompson BT, Parsons PE, Ware LB, Matthay MA, Wong HR. Plasma interleukin-8 is not an effective risk stratification tool for adults with vasopressor-dependent septic shock. Crit Care Med 2010; 38 (06) 1436-1441
    CrossrefPubMedGoogle Scholar
  • 29 Wynn JL, Cvijanovich NZ, Allen GL. , et al. The influence of developmental age on the early transcriptomic response of children with septic shock. Mol Med 2011; 17 (11-12): 1146-1156
    CrossrefPubMedGoogle Scholar
  • 30 Wynn J, Cornell TT, Wong HR, Shanley TP, Wheeler DS. The host response to sepsis and developmental impact. Pediatrics 2010; 125 (05) 1031-1041
    CrossrefPubMedGoogle Scholar
  • 31 Alder MN, Lindsell CJ, Wong HR. The pediatric sepsis biomarker risk model: potential implications for sepsis therapy and biology. Expert Rev Anti Infect Ther 2014; 12 (07) 809-816
    CrossrefPubMedGoogle Scholar
  • 32 Wong HR, Salisbury S, Xiao Q. , et al. The pediatric sepsis biomarker risk model. Crit Care 2012; 16 (05) R174
    CrossrefPubMedGoogle Scholar
  • 33 Kaplan JM, Wong HR. Biomarker discovery and development in pediatric critical care medicine. Pediatr Crit Care Med 2011; 12 (02) 165-173
    CrossrefPubMedGoogle Scholar
  • 34 Wong HR, Weiss SL, Giuliano Jr JS. , et al. Testing the prognostic accuracy of the updated pediatric sepsis biomarker risk model. PLoS One 2014; 9 (01) e86242
    CrossrefPubMedGoogle Scholar
  • 35 Wong HR, Cvijanovich NZ, Anas N. , et al. Pediatric sepsis biomarker risk model-II: redefining the pediatric sepsis biomarker risk model with septic shock phenotype. Crit Care Med 2016; 44 (11) 2010-2017
    CrossrefPubMedGoogle Scholar
  • 36 Wong HR, Weiss SL, Giuliano Jr JS. , et al. The temporal version of the pediatric sepsis biomarker risk model. PLoS One 2014; 9 (03) e92121
    CrossrefPubMedGoogle Scholar
  • 37 Wong HR, Cvijanovich NZ, Anas N. , et al. Prospective testing and redesign of a temporal biomarker based risk model for patients with septic shock: implications for septic shock biology. EBioMedicine 2015; 2 (12) 2087-2093
    CrossrefPubMedGoogle Scholar
  • 38 Abulebda K, Cvijanovich NZ, Thomas NJ. , et al. Post-ICU admission fluid balance and pediatric septic shock outcomes: a risk-stratified analysis. Crit Care Med 2014; 42 (02) 397-403
    CrossrefPubMedGoogle Scholar
  • 39 Atkinson SJ, Cvijanovich NZ, Thomas NJ. , et al. Corticosteroids and pediatric septic shock outcomes: a risk stratified analysis. PLoS One 2014; 9 (11) e112702
    CrossrefPubMedGoogle Scholar
  • 40 Wong HR, Cvijanovich N, Lin R. , et al. Identification of pediatric septic shock subclasses based on genome-wide expression profiling. BMC Med 2009; 7: 34
    CrossrefPubMedGoogle Scholar
  • 41 Davenport EE, Burnham KL, Radhakrishnan J. , et al. Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study. Lancet Respir Med 2016; 4 (04) 259-271
    CrossrefPubMedGoogle Scholar
  • 42 Wong HR, Cvijanovich NZ, Allen GL. , et al. Validation of a gene expression-based subclassification strategy for pediatric septic shock. Crit Care Med 2011; 39 (11) 2511-2517
    CrossrefPubMedGoogle Scholar
  • 43 Wong HR, Wheeler DS, Tegtmeyer K. , et al. Toward a clinically feasible gene expression-based subclassification strategy for septic shock: proof of concept. Crit Care Med 2010; 38 (10) 1955-1961
    CrossrefPubMedGoogle Scholar
  • 44 Hotchkiss RS, Sherwood ER. Immunology. Getting sepsis therapy right. Science 2015; 347 (6227): 1201-1202
    CrossrefPubMedGoogle Scholar
  • 45 Menon K, Wong HR. Corticosteroids in pediatric shock: a call to arms. Pediatr Crit Care Med 2015; 16 (08) e313-e317
    CrossrefPubMedGoogle Scholar
  • 46 Wong HR, Cvijanovich NZ, Anas N. , et al. Developing a clinically feasible personalized medicine approach to pediatric septic shock. Am J Respir Crit Care Med 2015; 191 (03) 309-315
    CrossrefPubMedGoogle Scholar
  • 47 Wong HR, Sweeney TE, Lindsell CJ. Simplification of a septic shock endotyping strategy for clinical application. Am J Respir Crit Care Med 2017; 195 (02) 263-265
    CrossrefPubMedGoogle Scholar
  • 48 Wong HR, Atkinson SJ, Cvijanovich NZ. , et al. Combining prognostic and predictive enrichment strategies to identify children with septic shock responsive to corticosteroids. Crit Care Med 2016; 44 (10) e1000-e1003
    CrossrefPubMedGoogle Scholar
  • 49 Alder MN, Opoka AM, Lahni P, Hildeman DA, Wong HR. Olfactomedin-4 is a candidate marker for a pathogenic neutrophil subset in septic shock. Crit Care Med 2017; 45 (04) e426-e432
    CrossrefPubMedGoogle Scholar
  • 50 Grover PK, Hardingham JE, Cummins AG. Stem cell marker olfactomedin 4: critical appraisal of its characteristics and role in tumorigenesis. Cancer Metastasis Rev 2010; 29 (04) 761-775
    CrossrefPubMedGoogle Scholar
  • 51 Snyder DA, Rivers AM, Yokoe H, Menco BP, Anholt RR. Olfactomedin: purification, characterization, and localization of a novel olfactory glycoprotein. Biochemistry 1991; 30 (38) 9143-9153
    CrossrefPubMedGoogle Scholar
  • 52 Yu L, Wang L, Chen S. Olfactomedin 4, a novel marker for the differentiation and progression of gastrointestinal cancers. Neoplasma 2011; 58 (01) 9-13
    CrossrefPubMedGoogle Scholar
  • 53 Clemmensen SN, Bohr CT, Rørvig S. , et al. Olfactomedin 4 defines a subset of human neutrophils. J Leukoc Biol 2012; 91 (03) 495-500
    CrossrefPubMedGoogle Scholar
  • 54 Kangelaris KN, Prakash A, Liu KD. , et al. Increased expression of neutrophil-related genes in patients with early sepsis-induced ARDS. Am J Physiol Lung Cell Mol Physiol 2015; 308 (11) L1102-L1113
    CrossrefPubMedGoogle Scholar
  • 55 Brand HK, Ahout IM, de Ridder D. , et al. Olfactomedin 4 serves as a marker for disease severity in pediatric respiratory syncytial virus (RSV) infection. PLoS One 2015; 10 (07) e0131927
    CrossrefPubMedGoogle Scholar
  • 56 Basu RK, Standage SW, Cvijanovich NZ. , et al. Identification of candidate serum biomarkers for severe septic shock-associated kidney injury via microarray. Crit Care 2011; 15 (06) R273
    CrossrefPubMedGoogle Scholar
  • 57 Wong HR, Cvijanovich NZ, Anas N. , et al. A multibiomarker-based model for estimating the risk of septic acute kidney injury. Crit Care Med 2015; 43 (08) 1646-1653
    CrossrefPubMedGoogle Scholar
  • 58 Liu W, Yan M, Liu Y. , et al. Olfactomedin 4 down-regulates innate immunity against Helicobacter pylori infection. Proc Natl Acad Sci U S A 2010; 107 (24) 11056-11061
    CrossrefPubMedGoogle Scholar
  • 59 Liu W, Yan M, Liu Y, McLeish KR, Coleman Jr WG, Rodgers GP. Olfactomedin 4 inhibits cathepsin C-mediated protease activities, thereby modulating neutrophil killing of Staphylococcus aureus and Escherichia coli in mice. J Immunol 2012; 189 (05) 2460-2467
    CrossrefPubMedGoogle Scholar
  • 60 Liu W, Yan M, Sugui JA. , et al. Olfm4 deletion enhances defense against Staphylococcus aureus in chronic granulomatous disease. J Clin Invest 2013; 123 (09) 3751-3755
    CrossrefPubMedGoogle Scholar
  • 61 Pierrakos C, Vincent JL. Sepsis biomarkers: a review. Crit Care 2010; 14 (01) R15
    CrossrefPubMedGoogle Scholar
  • 62 Rifai N, Gillette MA, Carr SA. Protein biomarker discovery and validation: the long and uncertain path to clinical utility. Nat Biotechnol 2006; 24 (08) 971-983
    CrossrefPubMedGoogle Scholar
  • 63 Eckerle M, Lahni P, Wong H. Estimating the probability of bacterial infection using a novel biomarker among pediatric patients in the emergency department. Biomarkers 2016; 21 (05) 404-408
    CrossrefPubMedGoogle Scholar
  • 64 Maslove DM, Wong HR. Gene expression profiling in sepsis: timing, tissue, and translational considerations. Trends Mol Med 2014; 20 (04) 204-213
    CrossrefPubMedGoogle Scholar