A prospective observational cohort study to identify inflammatory biomarkers for the diagnosis and prognosis of patients with sepsis.

Biomarkers Disease severity Inflammation Sepsis

Journal

Journal of intensive care
ISSN: 2052-0492
Titre abrégé: J Intensive Care
Pays: England
ID NLM: 101627304

Informations de publication

Date de publication:
09 Mar 2022
Historique:
received: 12 09 2021
accepted: 21 02 2022
entrez: 10 3 2022
pubmed: 11 3 2022
medline: 11 3 2022
Statut: epublish

Résumé

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. 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. 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. 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. clinicaltrial.gov identifier NCT03841162.

Sections du résumé

BACKGROUND 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 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 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 CONCLUSIONS
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 BACKGROUND
clinicaltrial.gov identifier NCT03841162.

Identifiants

DOI: 10.1186/s40560-022-00602-x PMID: 35264246 PMC: PMC8905560
pubmed: 35264246
doi: 10.1186/s40560-022-00602-x
pii: 10.1186/s40560-022-00602-x
pmc: PMC8905560
doi:

Banques de données

ClinicalTrials.gov
['NCT03841162']

Types de publication

Journal Article

Langues

eng

Pagination

13

Subventions

Organisme : horizon 2020
ID : GA643137

Informations de copyright

© 2022. The Author(s).

Références

Nat Rev Dis Primers. 2016 Jun 30;2:16045
pubmed: 28117397
PLoS One. 2014 Apr 22;9(4):e95192
pubmed: 24755770
Curr Pharm Biotechnol. 2017;18(6):499-507
pubmed: 28571560
JAMA. 2016 Feb 23;315(8):801-10
pubmed: 26903338
Front Med (Lausanne). 2019 Oct 22;6:224
pubmed: 31750305
Clin Chim Acta. 2016 Sep 1;460:203-10
pubmed: 27387712
Open Forum Infect Dis. 2020 Dec 28;8(1):ofaa594
pubmed: 33511231
JAMA. 2019 May 28;321(20):2003-2017
pubmed: 31104070
Blood. 2006 Nov 1;108(9):2906-13
pubmed: 16849637
Crit Care Med. 2014 Apr;42(4):781-9
pubmed: 24335447
BMC Med. 2017 Sep 18;15(1):172
pubmed: 28918754
PLoS One. 2018 Oct 9;13(10):e0205327
pubmed: 30300408
J Glob Antimicrob Resist. 2017 Sep;10:204-212
pubmed: 28743646
Nat Rev Immunol. 2017 Jul;17(7):407-420
pubmed: 28436424
Crit Care Clin. 2018 Jan;34(1):139-152
pubmed: 29149935
Crit Care. 2010;14(1):R15
pubmed: 20144219
J Immunol Res. 2015;2015:510436
pubmed: 26258150
Intensive Care Med. 2004 Apr;30(4):605-11
pubmed: 14991094
Crit Rev Clin Lab Sci. 2013 Jan-Feb;50(1):23-36
pubmed: 23480440
Cell. 2020 Dec 10;183(6):1479-1495.e20
pubmed: 33171100
Neth J Med. 2018 Jan;76(1):4-13
pubmed: 29380739
Biomarkers. 2015 Mar;20(2):132-5
pubmed: 25578228
Sci Rep. 2021 Aug 19;11(1):16905
pubmed: 34413363
Crit Care Med. 2006 Jun;34(6):1589-96
pubmed: 16625125
Expert Rev Anti Infect Ther. 2013 Mar;11(3):265-75
pubmed: 23458767
Intensive Care Med. 2018 Jul;44(7):1061-1070
pubmed: 29959455
Crit Care. 2015 Jan 15;19:11
pubmed: 25928796
Crit Care Med. 2015 Oct;43(10):2049-2058
pubmed: 26086942
Am Surg. 2018 Jun 1;84(6):1058-1063
pubmed: 29981649
Clin Infect Dis. 2004 Jul 15;39(2):206-17
pubmed: 15307030
Clin Chim Acta. 2015 Feb 2;440:97-103
pubmed: 25447700
Immunity. 2020 Nov 17;53(5):1108-1122.e5
pubmed: 33128875

Auteurs

Valentino D'Onofrio (V)

Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium. valentino.donofrio@uhasselt.be.
Department of Infectious Diseases and Immunity, Jessa Hospital, Hasselt, Belgium. valentino.donofrio@uhasselt.be.
Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands. valentino.donofrio@uhasselt.be.

Dries Heylen (D)

Unit Health, Flemish Institute for Technological Research (VITO), Mol, Belgium.
Data Science Institute, Hasselt University, Hasselt, Belgium.

Murih Pusparum (M)

Unit Health, Flemish Institute for Technological Research (VITO), Mol, Belgium.
Data Science Institute, Hasselt University, Hasselt, Belgium.

Inge Grondman (I)

Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands.

Johan Vanwalleghem (J)

Department of Nephrology, Jessa Hospital, Hasselt, Belgium.

Agnes Meersman (A)

Emergency Department, Jessa Hospital, Hasselt, Belgium.

Reinoud Cartuyvels (R)

Department of Clinical Biology, Jessa Hospital, Hasselt, Belgium.

Peter Messiaen (P)

Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium.
Department of Infectious Diseases and Immunity, Jessa Hospital, Hasselt, Belgium.

Leo A B Joosten (LAB)

Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands.

Mihai G Netea (MG)

Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands.
Human Genomics Laboratory, Craiova University of Medicine and Pharmacy, Craiova, Romania.

Dirk Valkenborg (D)

Data Science Institute, Hasselt University, Hasselt, Belgium.

Gökhan Ertaylan (G)

Unit Health, Flemish Institute for Technological Research (VITO), Mol, Belgium.

Inge C Gyssens (IC)

Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium. inge.gyssens@radboudumc.nl.
Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands. inge.gyssens@radboudumc.nl.
ORCID: 0000-0002-9226-0752

Classifications MeSH