Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/37158
Title: A prospective observational cohort study to identify inflammatory biomarkers for the diagnosis and prognosis of patients with sepsis
Authors: D'ONOFRIO, Valentino 
HEYLEN, Dries 
PUSPARUM, Murih 
Grondman, Inge
VANWALLEGHEM, Johan 
Meersman , Agnes
Cartuyvels, Reinoud
MESSIAEN, Peter 
Joosten, Leo A. B.
Netea, Mihai G.
VALKENBORG, Dirk 
Ertaylan, Gokhan
GYSSENS, Inge 
Issue Date: 2022
Publisher: BMC
Source: Journal of Intensive Care, 10 (1) (Art N° 13)
Abstract: Background Sepsis is a life-threatening organ dysfunction. A fast diagnosis is crucial for patient management. Proteins that are synthesized during the inflammatory response can be used as biomarkers, helping in a rapid clinical assessment or an early diagnosis of infection. The aim of this study was to identify biomarkers of inflammation for the diagnosis and prognosis of infection in patients with suspected sepsis. Methods In total 406 episodes were included in a prospective cohort study. Plasma was collected from all patients with suspected sepsis, for whom blood cultures were drawn, in the emergency department (ED), the department of infectious diseases, or the haemodialysis unit on the first day of a new episode. Samples were analysed using a 92-plex proteomic panel based on a proximity extension assay with oligonucleotide-labelled antibody probe pairs (OLink, Uppsala, Sweden). Supervised and unsupervised differential expression analyses and pathway enrichment analyses were performed to search for inflammatory proteins that were different between patients with viral or bacterial sepsis and between patients with worse or less severe outcome. Results Supervised differential expression analysis revealed 21 proteins that were significantly lower in circulation of patients with viral infections compared to patients with bacterial infections. More strongly, higher expression levels were observed for 38 proteins in patients with high SOFA scores (> 4), and for 21 proteins in patients with worse outcome. These proteins are mostly involved in pathways known to be activated early in the inflammatory response. Unsupervised, hierarchical clustering confirmed that inflammatory response was more strongly related to disease severity than to aetiology. Conclusion Several differentially expressed inflammatory proteins were identified that could be used as biomarkers for sepsis. These proteins are mostly related to disease severity. Within the setting of an emergency department, they could be used for outcome prediction, patient monitoring, and directing diagnostics. Trail registration number: clinicaltrial.gov identifier NCT03841162.
Notes: D'Onofrio, V; Gyssens, IC (corresponding author), Hasselt Univ, Fac Med & Life Sci, Martelarenlaan 42, B-3500 Hasselt, Belgium.; D'Onofrio, V (corresponding author), Jessa Hosp, Dept Infect Dis & Immun, Hasselt, Belgium.; D'Onofrio, V; Gyssens, IC (corresponding author), Radboud Univ Nijmegen, Med Ctr, Dept Internal Med, Geert Grootepl Zuid 10, NL-6525 GA Nijmegen, Netherlands.; D'Onofrio, V; Gyssens, IC (corresponding author), Radboud Univ Nijmegen, Med Ctr, Radboud Ctr Infect Dis, Geert Grootepl Zuid 10, NL-6525 GA Nijmegen, Netherlands.
valentino.donofrio@uhasselt.be; inge.gyssens@radboudumc.nl
Keywords: Biomarkers;Sepsis;Inflammation;Disease severity
Document URI: http://hdl.handle.net/1942/37158
ISSN: 2052-0492
e-ISSN: 2052-0492
DOI: 10.1186/s40560-022-00602-x
ISI #: WOS:000766561100002
Rights: The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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