Discovery and systematic assessment of early biomarkers that predict progression to severe COVID-19 disease.


Journal

Communications medicine
ISSN: 2730-664X
Titre abrégé: Commun Med (Lond)
Pays: England
ID NLM: 9918250414506676

Informations de publication

Date de publication:
12 Apr 2023
Historique:
received: 15 02 2022
accepted: 31 03 2023
medline: 12 4 2023
entrez: 11 4 2023
pubmed: 12 4 2023
Statut: epublish

Résumé

The clinical course of COVID-19 patients ranges from asymptomatic infection, via mild and moderate illness, to severe disease and even fatal outcome. Biomarkers which enable an early prediction of the severity of COVID-19 progression, would be enormously beneficial to guide patient care and early intervention prior to hospitalization. Here we describe the identification of plasma protein biomarkers using an antibody microarray-based approach in order to predict a severe cause of a COVID-19 disease already in an early phase of SARS-CoV-2 infection. To this end, plasma samples from two independent cohorts were analyzed by antibody microarrays targeting up to 998 different proteins. In total, we identified 11 promising protein biomarker candidates to predict disease severity during an early phase of COVID-19 infection coherently in both analyzed cohorts. A set of four (S100A8/A9, TSP1, FINC, IFNL1), and two sets of three proteins (S100A8/A9, TSP1, ERBB2 and S100A8/A9, TSP1, IFNL1) were selected using machine learning as multimarker panels with sufficient accuracy for the implementation in a prognostic test. Using these biomarkers, patients at high risk of developing a severe or critical disease may be selected for treatment with specialized therapeutic options such as neutralizing antibodies or antivirals. Early therapy through early stratification may not only have a positive impact on the outcome of individual COVID-19 patients but could additionally prevent hospitals from being overwhelmed in potential future pandemic situations. We aimed to identify components of the blood present during the early phase of SARS-CoV-2 infection that distinguish people who are likely to develop severe symptoms of COVID-19. Blood from people who later developed a mild or moderate course of disease were compared to blood from people who later had a severe or critical course of disease. Here, we identified a combination of three proteins that were present in the blood of patients with COVID-19 who later developed a severe or critical disease. Identifying the presence of these proteins in patients at an early stage of infection could enable physicians to treat these patients early on to avoid progression of the disease.

Sections du résumé

BACKGROUND BACKGROUND
The clinical course of COVID-19 patients ranges from asymptomatic infection, via mild and moderate illness, to severe disease and even fatal outcome. Biomarkers which enable an early prediction of the severity of COVID-19 progression, would be enormously beneficial to guide patient care and early intervention prior to hospitalization.
METHODS METHODS
Here we describe the identification of plasma protein biomarkers using an antibody microarray-based approach in order to predict a severe cause of a COVID-19 disease already in an early phase of SARS-CoV-2 infection. To this end, plasma samples from two independent cohorts were analyzed by antibody microarrays targeting up to 998 different proteins.
RESULTS RESULTS
In total, we identified 11 promising protein biomarker candidates to predict disease severity during an early phase of COVID-19 infection coherently in both analyzed cohorts. A set of four (S100A8/A9, TSP1, FINC, IFNL1), and two sets of three proteins (S100A8/A9, TSP1, ERBB2 and S100A8/A9, TSP1, IFNL1) were selected using machine learning as multimarker panels with sufficient accuracy for the implementation in a prognostic test.
CONCLUSIONS CONCLUSIONS
Using these biomarkers, patients at high risk of developing a severe or critical disease may be selected for treatment with specialized therapeutic options such as neutralizing antibodies or antivirals. Early therapy through early stratification may not only have a positive impact on the outcome of individual COVID-19 patients but could additionally prevent hospitals from being overwhelmed in potential future pandemic situations.
We aimed to identify components of the blood present during the early phase of SARS-CoV-2 infection that distinguish people who are likely to develop severe symptoms of COVID-19. Blood from people who later developed a mild or moderate course of disease were compared to blood from people who later had a severe or critical course of disease. Here, we identified a combination of three proteins that were present in the blood of patients with COVID-19 who later developed a severe or critical disease. Identifying the presence of these proteins in patients at an early stage of infection could enable physicians to treat these patients early on to avoid progression of the disease.

Autres résumés

Type: plain-language-summary (eng)
We aimed to identify components of the blood present during the early phase of SARS-CoV-2 infection that distinguish people who are likely to develop severe symptoms of COVID-19. Blood from people who later developed a mild or moderate course of disease were compared to blood from people who later had a severe or critical course of disease. Here, we identified a combination of three proteins that were present in the blood of patients with COVID-19 who later developed a severe or critical disease. Identifying the presence of these proteins in patients at an early stage of infection could enable physicians to treat these patients early on to avoid progression of the disease.

Identifiants

pubmed: 37041310
doi: 10.1038/s43856-023-00283-z
pii: 10.1038/s43856-023-00283-z
pmc: PMC10089829
doi:

Types de publication

Journal Article

Langues

eng

Pagination

51

Informations de copyright

© 2023. The Author(s).

Références

Engineering (Beijing). 2022 Oct;17:161-169
pubmed: 34150352
BMC Bioinformatics. 2010 Nov 12;11:556
pubmed: 21073702
J Med Virol. 2021 Feb;93(2):1078-1098
pubmed: 32776551
Am J Respir Crit Care Med. 2020 Dec 1;202(11):1509-1519
pubmed: 32866033
Expert Rev Clin Immunol. 2021 May;17(5):431-443
pubmed: 33750254
Nat Commun. 2021 Feb 18;12(1):1112
pubmed: 33602937
Postgrad Med. 2021 Jun;133(5):489-507
pubmed: 33245005
Cell. 2020 Sep 17;182(6):1401-1418.e18
pubmed: 32810439
Sci Rep. 2021 Oct 22;11(1):20870
pubmed: 34686725
Proteomics Clin Appl. 2013 Dec;7(11-12):802-12
pubmed: 24323458
Adv Immunol. 2014;121:191-211
pubmed: 24388216
Int J Environ Res Public Health. 2021 Feb 20;18(4):
pubmed: 33672761
Mol Cell Proteomics. 2010 Jun;9(6):1271-80
pubmed: 20164060
Cell Biol Toxicol. 2016 Jun;32(3):169-84
pubmed: 27095254
Pathogens. 2021 Apr 06;10(4):
pubmed: 33917609
Cell Mol Immunol. 2020 Sep;17(9):992-994
pubmed: 32620787
Mol Med. 2022 Apr 9;28(1):40
pubmed: 35397534
Cytokine. 2021 Apr;140:155438
pubmed: 33493861
J Proteomics. 2015 Oct 14;128:251-61
pubmed: 26232108
J Leukoc Biol. 2021 Jan;109(1):55-66
pubmed: 32930456
Curr Opin Immunol. 2006 Feb;18(1):39-48
pubmed: 16337366
J Autoimmun. 2020 May;109:102442
pubmed: 32253068
PLoS One. 2020 Aug 21;15(8):e0238160
pubmed: 32822430
JCI Insight. 2020 May 21;5(10):
pubmed: 32324595
J Interferon Cytokine Res. 2021 Apr;41(4):149-152
pubmed: 33885337
J Transl Med. 2020 Dec 3;18(1):457
pubmed: 33272291
J Med Virol. 2021 Oct;93(10):6008-6015
pubmed: 34232533
Mol Biol Rep. 2020 Oct;47(10):8301-8304
pubmed: 32920756
JCI Insight. 2021 Jan 11;6(1):
pubmed: 33232303
Int J Epidemiol. 2021 May 17;50(2):420-429
pubmed: 33683344
Viruses. 2021 Aug 12;13(8):
pubmed: 34452467
Med Hypotheses. 2020 Nov;144:110167
pubmed: 32795835
J Clin Med. 2021 Aug 27;10(17):
pubmed: 34501309
J Leukoc Biol. 2021 Jan;109(1):67-72
pubmed: 32869342
Antiviral Res. 2020 Aug;180:104860
pubmed: 32565134
Rev Med Virol. 2021 Jan;31(1):1-10
pubmed: 32845042
Adv Clin Exp Med. 2019 Nov;28(11):1561-1567
pubmed: 31596557
Commun Med (Lond). 2023 Apr 12;3(1):51
pubmed: 37041310
FEBS Lett. 2006 May 15;580(11):2637-45
pubmed: 16650408
World J Crit Care Med. 2021 Jul 9;10(4):132-150
pubmed: 34316448
J Clin Invest. 2021 Apr 15;131(8):
pubmed: 33635833
MMWR Morb Mortal Wkly Rep. 2020 Mar 27;69(12):343-346
pubmed: 32214079
Ir J Med Sci. 2022 Feb;191(1):59-64
pubmed: 33641087
Cell. 2020 Jul 9;182(1):59-72.e15
pubmed: 32492406

Auteurs

Katrin Hufnagel (K)

Sciomics GmbH, Neckargemünd, Baden-Württemberg, Germany.

Anahita Fathi (A)

University Medical Center Hamburg-Eppendorf, Institute for Infection Research and Vaccine Development (IIRVD), Hamburg, Germany.
Bernhard-Nocht-Institute for Tropical Medicine, Department for Clinical Immunology of Infectious Diseases, Hamburg, Germany.
German Center for Infection Research, partner site Hamburg-Lübeck-Borstel-Riems, Hamburg, Germany.
University Medical Center Hamburg-Eppendorf, First Department of Medicine, Division of Infectious Diseases, Hamburg, Germany.

Nadine Stroh (N)

Sciomics GmbH, Neckargemünd, Baden-Württemberg, Germany.

Marco Klein (M)

Sciomics GmbH, Neckargemünd, Baden-Württemberg, Germany.

Florian Skwirblies (F)

Sciomics GmbH, Neckargemünd, Baden-Württemberg, Germany.

Ramy Girgis (R)

Sciomics GmbH, Neckargemünd, Baden-Württemberg, Germany.

Christine Dahlke (C)

University Medical Center Hamburg-Eppendorf, Institute for Infection Research and Vaccine Development (IIRVD), Hamburg, Germany.
Bernhard-Nocht-Institute for Tropical Medicine, Department for Clinical Immunology of Infectious Diseases, Hamburg, Germany.
German Center for Infection Research, partner site Hamburg-Lübeck-Borstel-Riems, Hamburg, Germany.

Jörg D Hoheisel (JD)

Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Baden-Württemberg, Germany.

Camille Lowy (C)

Sciomics GmbH, Neckargemünd, Baden-Württemberg, Germany.

Ronny Schmidt (R)

Sciomics GmbH, Neckargemünd, Baden-Württemberg, Germany.

Anne Griesbeck (A)

Sciomics GmbH, Neckargemünd, Baden-Württemberg, Germany.

Uta Merle (U)

Department of Internal Medicine IV, University Hospital Heidelberg, Heidelberg, Germany.

Marylyn M Addo (MM)

University Medical Center Hamburg-Eppendorf, Institute for Infection Research and Vaccine Development (IIRVD), Hamburg, Germany.
Bernhard-Nocht-Institute for Tropical Medicine, Department for Clinical Immunology of Infectious Diseases, Hamburg, Germany.
German Center for Infection Research, partner site Hamburg-Lübeck-Borstel-Riems, Hamburg, Germany.

Christoph Schröder (C)

Sciomics GmbH, Neckargemünd, Baden-Württemberg, Germany. schroeder@sciomics.de.

Classifications MeSH