Cargando…
Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19
The associations between clinical phenotypes of coronavirus disease 2019 (COVID-19) and the host inflammatory response during the transition from peak illness to convalescence are not yet well understood. Blood plasma samples were collected from 129 adult SARS-CoV-2 positive inpatient and outpatient...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9795438/ https://www.ncbi.nlm.nih.gov/pubmed/36577783 http://dx.doi.org/10.1038/s41598-022-26965-7 |
_version_ | 1784860261658656768 |
---|---|
author | Blair, Paul W. Brandsma, Joost Chenoweth, Josh Richard, Stephanie A. Epsi, Nusrat J. Mehta, Rittal Striegel, Deborah Clemens, Emily G. Alharthi, Sultanah Lindholm, David A. Maves, Ryan C. Larson, Derek T. Mende, Katrin Colombo, Rhonda E. Ganesan, Anuradha Lalani, Tahaniyat Colombo, Christopher J. Malloy, Allison A. Snow, Andrew L. Schully, Kevin L. Lanteri, Charlotte Simons, Mark P. Dumler, John S. Tribble, David Burgess, Timothy Pollett, Simon Agan, Brian K. Clark, Danielle V. |
author_facet | Blair, Paul W. Brandsma, Joost Chenoweth, Josh Richard, Stephanie A. Epsi, Nusrat J. Mehta, Rittal Striegel, Deborah Clemens, Emily G. Alharthi, Sultanah Lindholm, David A. Maves, Ryan C. Larson, Derek T. Mende, Katrin Colombo, Rhonda E. Ganesan, Anuradha Lalani, Tahaniyat Colombo, Christopher J. Malloy, Allison A. Snow, Andrew L. Schully, Kevin L. Lanteri, Charlotte Simons, Mark P. Dumler, John S. Tribble, David Burgess, Timothy Pollett, Simon Agan, Brian K. Clark, Danielle V. |
author_sort | Blair, Paul W. |
collection | PubMed |
description | The associations between clinical phenotypes of coronavirus disease 2019 (COVID-19) and the host inflammatory response during the transition from peak illness to convalescence are not yet well understood. Blood plasma samples were collected from 129 adult SARS-CoV-2 positive inpatient and outpatient participants between April 2020 and January 2021, in a multi-center prospective cohort study at 8 military hospitals across the United States. Plasma inflammatory protein biomarkers were measured in samples from 15 to 28 days post symptom onset. Topological Data Analysis (TDA) was used to identify patterns of inflammation, and associations with peak severity (outpatient, hospitalized, ICU admission or death), Charlson Comorbidity Index (CCI), and body mass index (BMI) were evaluated using logistic regression. The study population (n = 129, 33.3% female, median 41.3 years of age) included 77 outpatient, 31 inpatient, 16 ICU-level, and 5 fatal cases. Three distinct inflammatory biomarker clusters were identified and were associated with significant differences in peak disease severity (p < 0.001), age (p < 0.001), BMI (p < 0.001), and CCI (p = 0.001). Host-biomarker profiles stratified a heterogeneous population of COVID-19 patients during the transition from peak illness to convalescence, and these distinct inflammatory patterns were associated with comorbid disease and severe illness due to COVID-19. |
format | Online Article Text |
id | pubmed-9795438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97954382022-12-28 Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19 Blair, Paul W. Brandsma, Joost Chenoweth, Josh Richard, Stephanie A. Epsi, Nusrat J. Mehta, Rittal Striegel, Deborah Clemens, Emily G. Alharthi, Sultanah Lindholm, David A. Maves, Ryan C. Larson, Derek T. Mende, Katrin Colombo, Rhonda E. Ganesan, Anuradha Lalani, Tahaniyat Colombo, Christopher J. Malloy, Allison A. Snow, Andrew L. Schully, Kevin L. Lanteri, Charlotte Simons, Mark P. Dumler, John S. Tribble, David Burgess, Timothy Pollett, Simon Agan, Brian K. Clark, Danielle V. Sci Rep Article The associations between clinical phenotypes of coronavirus disease 2019 (COVID-19) and the host inflammatory response during the transition from peak illness to convalescence are not yet well understood. Blood plasma samples were collected from 129 adult SARS-CoV-2 positive inpatient and outpatient participants between April 2020 and January 2021, in a multi-center prospective cohort study at 8 military hospitals across the United States. Plasma inflammatory protein biomarkers were measured in samples from 15 to 28 days post symptom onset. Topological Data Analysis (TDA) was used to identify patterns of inflammation, and associations with peak severity (outpatient, hospitalized, ICU admission or death), Charlson Comorbidity Index (CCI), and body mass index (BMI) were evaluated using logistic regression. The study population (n = 129, 33.3% female, median 41.3 years of age) included 77 outpatient, 31 inpatient, 16 ICU-level, and 5 fatal cases. Three distinct inflammatory biomarker clusters were identified and were associated with significant differences in peak disease severity (p < 0.001), age (p < 0.001), BMI (p < 0.001), and CCI (p = 0.001). Host-biomarker profiles stratified a heterogeneous population of COVID-19 patients during the transition from peak illness to convalescence, and these distinct inflammatory patterns were associated with comorbid disease and severe illness due to COVID-19. Nature Publishing Group UK 2022-12-28 /pmc/articles/PMC9795438/ /pubmed/36577783 http://dx.doi.org/10.1038/s41598-022-26965-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Blair, Paul W. Brandsma, Joost Chenoweth, Josh Richard, Stephanie A. Epsi, Nusrat J. Mehta, Rittal Striegel, Deborah Clemens, Emily G. Alharthi, Sultanah Lindholm, David A. Maves, Ryan C. Larson, Derek T. Mende, Katrin Colombo, Rhonda E. Ganesan, Anuradha Lalani, Tahaniyat Colombo, Christopher J. Malloy, Allison A. Snow, Andrew L. Schully, Kevin L. Lanteri, Charlotte Simons, Mark P. Dumler, John S. Tribble, David Burgess, Timothy Pollett, Simon Agan, Brian K. Clark, Danielle V. Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19 |
title | Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19 |
title_full | Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19 |
title_fullStr | Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19 |
title_full_unstemmed | Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19 |
title_short | Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19 |
title_sort | distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9795438/ https://www.ncbi.nlm.nih.gov/pubmed/36577783 http://dx.doi.org/10.1038/s41598-022-26965-7 |
work_keys_str_mv | AT blairpaulw distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT brandsmajoost distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT chenowethjosh distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT richardstephaniea distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT epsinusratj distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT mehtarittal distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT striegeldeborah distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT clemensemilyg distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT alharthisultanah distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT lindholmdavida distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT mavesryanc distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT larsonderekt distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT mendekatrin distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT colomborhondae distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT ganesananuradha distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT lalanitahaniyat distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT colombochristopherj distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT malloyallisona distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT snowandrewl distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT schullykevinl distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT lantericharlotte distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT simonsmarkp distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT dumlerjohns distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT tribbledavid distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT burgesstimothy distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT pollettsimon distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT aganbriank distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT clarkdaniellev distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 AT distinctbloodinflammatorybiomarkerclustersstratifyhostphenotypesduringthemiddlephaseofcovid19 |