{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T04:45:38Z","timestamp":1792644338570,"version":"4.5.0"},"reference-count":102,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T00:00:00Z","timestamp":1706140800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Nineteen high-performance, differentially expressed mRNA biomarkers were identified between control and combined SIRS\/Sepsis groups (FC&amp;gt;20.0, p&amp;lt;0.05), termed \u2018indicators of inflammation\u2019 (I\u00b0I), including CD177, FAM20A and OLAH. Best-performing minimal signatures e.g. FAM20A\/OLAH showed good accuracy for determination of severe, systemic inflammation (AUC&amp;gt;0.99). Twenty entities, termed \u2018SIRS or Sepsis\u2019 (S\u00b0S) biomarkers, were differentially expressed between sepsis and SIRS (FC&amp;gt;2\u00b70, p-value&amp;lt;0.05).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>The best performing signature for discriminating sepsis from SIRS was CMTM5\/CETP\/PLA2G7\/MIA\/MPP3 (AUC=0.9758). The I\u00b0I and S\u00b0S signatures performed variably in other independent gene expression datasets, this may be due to technical variation in the study\/assay platform.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2023.1308530","type":"journal-article","created":{"date-parts":[[2024,1,24]],"date-time":"2024-01-24T23:36:51Z","timestamp":1706139411000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["The \u2018analysis of gene expression and biomarkers for point-of-care decision support in Sepsis\u2018 study; temporal clinical parameter analysis and validation of early diagnostic biomarker signatures for severe inflammation andsepsis-SIRS 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