title: Development and validation of a novel molecular biomarker diagnostic test for the early detection of sepsis.
abstract: BACKGROUND
  Sepsis is a complex immunological response to infection characterized by early hyper-inflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on Systemic Inflammatory Response Syndrome (SIRS) differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. 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 multi-centre, prospective clinical trial conducted across four tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n = 27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n = 38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n = 20). Each participant had minimally 5 ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. Affymetrix array and multiplex tandem (MT)-PCR studies were conducted to evaluate transcriptional profiles in circulating white blood cells applying a set of 42 molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine learning diagnostic rule to predict sepsis outcomes.
  
  
  RESULTS
  Based on preliminary microarray analyses comparing HC and sepsis groups, a panel of 42-gene expression markers were identified that represented key innate and adaptive immune function, cell cycling, WBC differentiation, extracellular remodelling and immune modulation pathways. Comparisons against GEO data confirmed the definitive separation of the sepsis cohort. Quantitative PCR results suggest the capacity for this test to differentiate severe systemic inflammation from HC is 92%. The area under the curve (AUC) receiver operator characteristics (ROC) curve findings demonstrated sepsis prediction within a mixed inflammatory population, was between 86 and 92%.
  
  
  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.
authors.affiliation: Division of Immunobiology and Bioinformatics, Athlomics Pty Ltd, Jephson Street, Toowong, QLD 4066, Australia. Allison.Sutherland@athlomics.com
authors.forename: Allison
authors.initials: A
authors.lastname: Sutherland
authors.forename: Mervyn
authors.initials: M
authors.lastname: Thomas
authors.forename: Roslyn A
authors.initials: RA
authors.lastname: Brandon
authors.forename: Richard B
authors.initials: RB
authors.lastname: Brandon
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Lipman
authors.forename: Benjamin
authors.initials: B
authors.lastname: Tang
authors.forename: Anthony
authors.initials: A
authors.lastname: McLean
authors.forename: Ranald
authors.initials: R
authors.lastname: Pascoe
authors.forename: Gareth
authors.initials: G
authors.lastname: Price
authors.forename: Thu
authors.initials: T
authors.lastname: Nguyen
authors.forename: Glenn
authors.initials: G
authors.lastname: Stone
authors.forename: Deon
authors.initials: D
authors.lastname: Venter
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000818:Animals; D015415:Biomarkers / Q000378:metabolism; D015331:Cohort Studies; D003955:Diagnostic Tests, Routine / Q000592:standards* / Q000639:trends; D042241:Early Diagnosis; D005260:Female; D020869:Gene Expression Profiling; D006736:Horses; D006801:Humans; D018836:Inflammation Mediators / Q000378:metabolism*; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D040081:Protein Array Analysis / Q000592:standards / Q000639:trends; D018805:Sepsis / Q000175:diagnosis* / Q000235:genetics* / Q000473:pathology; D055815:Young Adult
chemical_list: D015415:Biomarkers; D018836:Inflammation Mediators