The 'analysis of gene expression and biomarkers for point-of-care decision support in Sepsis' study; temporal clinical parameter analysis and validation of early diagnostic biomarker signatures for severe inflammation andsepsis-SIRS discrimination

Front Immunol. 2024 Jan 25:14:1308530. doi: 10.3389/fimmu.2023.1308530. eCollection 2023.

Abstract

Introduction: Early diagnosis of sepsis and discrimination from SIRS is crucial for clinicians to provide appropriate care, management and treatment to critically ill patients. We describe identification of mRNA biomarkers from peripheral blood leukocytes, able to identify severe, systemic inflammation (irrespective of origin) and differentiate Sepsis from SIRS, in adult patients within a multi-center clinical study.

Methods: Participants were recruited in Intensive Care Units (ICUs) from multiple UK hospitals, including fifty-nine patients with abdominal sepsis, eighty-four patients with pulmonary sepsis, forty-two SIRS patients with Out-of-Hospital Cardiac Arrest (OOHCA), sampled at four time points, in addition to thirty healthy control donors. Multiple clinical parameters were measured, including SOFA score, with many differences observed between SIRS and sepsis groups. Differential gene expression analyses were performed using microarray hybridization and data analyzed using a combination of parametric and non-parametric statistical tools.

Results: Nineteen high-performance, differentially expressed mRNA biomarkers were identified between control and combined SIRS/Sepsis groups (FC>20.0, p<0.05), termed 'indicators of inflammation' (I°I), including CD177, FAM20A and OLAH. Best-performing minimal signatures e.g. FAM20A/OLAH showed good accuracy for determination of severe, systemic inflammation (AUC>0.99). Twenty entities, termed 'SIRS or Sepsis' (S°S) biomarkers, were differentially expressed between sepsis and SIRS (FC>2·0, p-value<0.05).

Discussion: The best performing signature for discriminating sepsis from SIRS was CMTM5/CETP/PLA2G7/MIA/MPP3 (AUC=0.9758). The I°I and S°S signatures performed variably in other independent gene expression datasets, this may be due to technical variation in the study/assay platform.

Keywords: SIRS; biomarker; diagnostic; mRNA signature; sepsis; severe inflammation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers
  • Chemokines
  • Gene Expression
  • Humans
  • Inflammation / diagnosis
  • Inflammation / genetics
  • MARVEL Domain-Containing Proteins
  • Point-of-Care Systems
  • RNA, Messenger
  • Sepsis* / diagnosis
  • Sepsis* / genetics
  • Systemic Inflammatory Response Syndrome* / diagnosis
  • Systemic Inflammatory Response Syndrome* / genetics

Substances

  • Biomarkers
  • RNA, Messenger
  • CMTM5 protein, human
  • Chemokines
  • MARVEL Domain-Containing Proteins

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This project was supported with funding from UKRI (previously Technology Strategy Board), Project number 101191. The Funder has no role in the acquisition, interpretation or presentation of the data and was not involved in the writing of the manuscript. Dr Szakmany was supported by the Health and Care Research Wales (formerly National Institute of Health and Social Care Research, Wales) Clinical Research Fellowship Grant 2010-2013.