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Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes - 12/08/23

Doi : 10.1016/j.rmed.2023.107331 
Nick Keur a, 1 , Maria Saridaki b, 1 , Isis Ricaño-Ponce a , Mihai G. Netea a, c, 2 , Evangelos J. Giamarellos-Bourboulis b, 2 , Vinod Kumar a, d, e, 2,
a Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands 
b 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Athens, Greece 
c Human Genomics Laboratory, Craiova University of Medicine and Pharmacy, Craiova, Romania 
d University of Groningen, University Medical Center Groningen, Department of Genetics, the Netherlands 
e Nitte (Deemed to Be University), Nitte University Centre for Science Education and Research (NUCSER), Deralakatte, Mangalore, India 

Corresponding author. Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenthe Netherlands

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Abstract

Background

The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) can present with a broad range of clinical manifestations, ranging from asymptomatic to severe multiple organ failure. The severity of the disease can vary depending on factors such as age, sex, ethnicity, and pre-existing medical conditions. Despite multiple efforts to identify reliable prognostic factors and biomarkers, the predictive capacity of these markers for clinical outcomes remains poor. Circulating proteins, which reflect the active mechanisms in an individual, can be easily measured in clinical practice and therefore may be useful as biomarkers for COVID-19 disease severity. In this study, we sought to identify protein biomarkers and endotypes for COVID-19 severity and evaluate their reproducibility in an independent cohort.

Methods

We investigated a cohort of 153 Greek patients with confirmed SARS-CoV-2 infection in which plasma protein levels were measured using the Olink Explore 1536 panel, which consists of 1472 proteins. We compared the protein profiles from severe and moderate COVID-19 patients to identify proteins associated with disease severity. To evaluate the reproducibility of our findings, we compared the protein profiles of 174 patients with comparable COVID-19 severities in a US COVID-19 cohort to identify proteins consistently correlated with COVID-19 severity in both groups.

Results

We identified 218 differentially regulated proteins associated with severity, 20 proteins were also replicated in an external cohort which we used for validation. Moreover, we performed unsupervised clustering of patients based on 97 proteins with the highest log2 fold changes in order to identify COVID-19 endotypes. Clustering of patients based on differentially regulated proteins revealed the presence of three clinical endotypes. While endotypes 2 and 3 were enriched for severe COVID-19 patients, endotypes 3 represented the most severe form of the disease.

Conclusions

These results suggest that identified circulating proteins may be useful for identifying COVID-19 patients with worse outcomes, and this potential utility may extend to other populations.

Trial registration

NCT04357366.

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Highlights

Biomarkers for COVID-19 severity and outcome were identified in two populations.
Proteomics predicted three endotypes of COVID-19 patients with different severity.
COVID-19 endotype-specific pathways help explain the COVID-19 patient heterogeneity.

Le texte complet de cet article est disponible en PDF.

Keywords : Proteomics, COVID-19, Biomarker, Cytokine, Clustering, Endotypes


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© 2023  The Author(s). Publié par Elsevier Masson SAS. Tous droits réservés.
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Vol 217

Article 107331- octobre 2023 Retour au numéro
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