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Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes
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 s...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10290733/ https://www.ncbi.nlm.nih.gov/pubmed/37364721 http://dx.doi.org/10.1016/j.rmed.2023.107331 |
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author | Keur, Nick Saridaki, Maria Ricaño-Ponce, Isis Netea, Mihai G. Giamarellos-Bourboulis, Evangelos J. Kumar, Vinod |
author_facet | Keur, Nick Saridaki, Maria Ricaño-Ponce, Isis Netea, Mihai G. Giamarellos-Bourboulis, Evangelos J. Kumar, Vinod |
author_sort | Keur, Nick |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10290733 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Author(s). Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102907332023-06-26 Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes Keur, Nick Saridaki, Maria Ricaño-Ponce, Isis Netea, Mihai G. Giamarellos-Bourboulis, Evangelos J. Kumar, Vinod Respir Med Original Research 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. The Author(s). Published by Elsevier Ltd. 2023-10 2023-06-25 /pmc/articles/PMC10290733/ /pubmed/37364721 http://dx.doi.org/10.1016/j.rmed.2023.107331 Text en © 2023 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Research Keur, Nick Saridaki, Maria Ricaño-Ponce, Isis Netea, Mihai G. Giamarellos-Bourboulis, Evangelos J. Kumar, Vinod Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes |
title | Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes |
title_full | Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes |
title_fullStr | Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes |
title_full_unstemmed | Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes |
title_short | Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes |
title_sort | analysis of inflammatory protein profiles in the circulation of covid-19 patients identifies patients with severe disease phenotypes |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10290733/ https://www.ncbi.nlm.nih.gov/pubmed/37364721 http://dx.doi.org/10.1016/j.rmed.2023.107331 |
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