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Volume 14 Supplement 2

Sepsis 2010

  • Poster presentation
  • Open Access

A novel molecular biomarker diagnostic for the early detection of sepsis

  • 1,
  • 2,
  • 3,
  • 4,
  • 4,
  • 5,
  • 1,
  • 1,
  • 2 and
  • 2
Critical Care201014 (Suppl 2) :P9

https://doi.org/10.1186/cc9112

  • Published:

Keywords

  • Exon Array
  • Gene Expression Marker
  • Evaluate Gene Expression
  • Endotoxemia Model
  • Great Clinical Utility

Introduction

Sepsis is a complex immunological response to infection characterized by a sinusoidal pattern that represents early hyperinflammatory signals [1] followed by severe and protracted immunosuppression, suggesting that a multimarker approach has the greatest clinical utility in early detection within a clinical environment focused on SIRS differentiation. Preclinical research using an equine endotoxemia model identified a panel of gene expression biomarkers that define the aberrant immune activity during early sepsis. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing.

Methods

This was a multicenter, prospective clinical trial conducted across four tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement [2] and had clinical evidence of systemic infection based on microbiology diagnoses (n = 27). Participants in the post-surgical (PS) group were recruited preoperatively and blood samples collected within 24 hours following surgery (n = 36). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n = 19). Each participant had minimally 5 ml PAXgene blood collected for RNA isolation and gene expression analyses. Affymetrix Exon array and multiplex tandem (MT)-PCR studies were conducted to evaluate gene expression using a set of molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine-learning diagnostic rule in which to predict sepsis outcomes.

Results

Based on preliminary exon array analyses comparing HC and sepsis groups, a panel of 42 gene expression markers was identified that linked to key innate immunity, cell cycle, endothelial, coagulation, and apoptotic pathways. When sepsis and PS groups were combined, the test had an ROC area >95%. Using subsets of these biomarkers in the MT-PCR assay, the ROC AUC for sepsis prediction was between 85 and 90%.

Conclusions

This novel molecular biomarker test has a clinically relevant sensitivity and specificity profile, and has the capacity for early detection of sepsis via the monitoring of critical care patients.

Declarations

Acknowledgements

DV is Director and Shareholder, Athlomics Pty Ltd. MT is Shareholder, Athlomics Pty Ltd. RB is Shareholder, Athlomics Pty Ltd. AS is Research Consultant, Athlomics Pty Ltd.

Authors’ Affiliations

(1)
Pathology, Mater Adult Hospital, Brisbane, Australia
(2)
Athlomics Pty Ltd,Immunobiology and Bioinformatics, Brisbane, Australia
(3)
Royal Brisbane & Women's Hospital, Intensive Care Medicine, Brisbane, Australia
(4)
Nepean Hospital, Intensive Care Medicine, Sydney, Australia
(5)
Wesley Hospital, Intensive Care Medicine, Brisbane, Australia

References

  1. Hotchkiss RS, Coopersmith CM, McDunn JE, Fergusan TA: Tilting toward immunosuppression. Nat Med 2009, 15: 496-497. 10.1038/nm0509-496PubMed CentralView ArticlePubMedGoogle Scholar
  2. American College of Chest Physicians/Society of Critical Care Medicine Consensus Conference: Definitions of sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. Crit Care Med 1992, 20: 864-874. 10.1097/00003246-199206000-00025View ArticleGoogle Scholar

Copyright

© BioMed Central Ltd 2010

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