Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes
BackgroundMost of the explanatory and prognostic models of COVID-19 lack of a comprehensive assessment of the wide COVID-19 spectrum of abnormalities. The aim of this study was to unveil novel biological features to explain COVID-19 severity and prognosis (death and disease progression).MethodsA pre...
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Frontiers Media S.A.
2021-09-01
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Series: | Frontiers in Immunology |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2021.689966/full |
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Article |
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DOAJ |
language |
English |
format |
Article |
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DOAJ |
author |
Jiram Torres-Ruiz Jiram Torres-Ruiz Alfredo Pérez-Fragoso José Luis Maravillas-Montero Luis Llorente Nancy R. Mejía-Domínguez José Carlos Páez-Franco Sandra Romero-Ramírez Victor Andrés Sosa-Hernández Rodrigo Cervantes-Díaz Abdiel Absalón-Aguilar Miroslava Nuñez-Aguirre Guillermo Juárez-Vega David Meza-Sánchez Ari Kleinberg-Bid Thierry Hernández-Gilsoul Alfredo Ponce-de-León Diana Gómez-Martín Diana Gómez-Martín |
spellingShingle |
Jiram Torres-Ruiz Jiram Torres-Ruiz Alfredo Pérez-Fragoso José Luis Maravillas-Montero Luis Llorente Nancy R. Mejía-Domínguez José Carlos Páez-Franco Sandra Romero-Ramírez Victor Andrés Sosa-Hernández Rodrigo Cervantes-Díaz Abdiel Absalón-Aguilar Miroslava Nuñez-Aguirre Guillermo Juárez-Vega David Meza-Sánchez Ari Kleinberg-Bid Thierry Hernández-Gilsoul Alfredo Ponce-de-León Diana Gómez-Martín Diana Gómez-Martín Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes Frontiers in Immunology COVID-19 TRIM63 NETs LDGs metabolomics T cells |
author_facet |
Jiram Torres-Ruiz Jiram Torres-Ruiz Alfredo Pérez-Fragoso José Luis Maravillas-Montero Luis Llorente Nancy R. Mejía-Domínguez José Carlos Páez-Franco Sandra Romero-Ramírez Victor Andrés Sosa-Hernández Rodrigo Cervantes-Díaz Abdiel Absalón-Aguilar Miroslava Nuñez-Aguirre Guillermo Juárez-Vega David Meza-Sánchez Ari Kleinberg-Bid Thierry Hernández-Gilsoul Alfredo Ponce-de-León Diana Gómez-Martín Diana Gómez-Martín |
author_sort |
Jiram Torres-Ruiz |
title |
Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes |
title_short |
Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes |
title_full |
Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes |
title_fullStr |
Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes |
title_full_unstemmed |
Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes |
title_sort |
redefining covid-19 severity and prognosis: the role of clinical and immunobiotypes |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Immunology |
issn |
1664-3224 |
publishDate |
2021-09-01 |
description |
BackgroundMost of the explanatory and prognostic models of COVID-19 lack of a comprehensive assessment of the wide COVID-19 spectrum of abnormalities. The aim of this study was to unveil novel biological features to explain COVID-19 severity and prognosis (death and disease progression).MethodsA predictive model for COVID-19 severity in 121 patients was constructed by ordinal logistic regression calculating odds ratio (OR) with 95% confidence intervals (95% CI) for a set of clinical, immunological, metabolomic, and other biological traits. The accuracy and calibration of the model was tested with the area under the curve (AUC), Somer’s D, and calibration plot. Hazard ratios with 95% CI for adverse outcomes were calculated with a Cox proportional-hazards model.ResultsThe explanatory variables for COVID-19 severity were the body mass index (BMI), hemoglobin, albumin, 3-Hydroxyisovaleric acid, CD8+ effector memory T cells, Th1 cells, low-density granulocytes, monocyte chemoattractant protein-1, plasma TRIM63, and circulating neutrophil extracellular traps. The model showed an outstanding performance with an optimism-adjusted AUC of 0.999, and Somer’s D of 0.999. The predictive variables for adverse outcomes in COVID-19 were severe and critical disease diagnosis, BMI, lactate dehydrogenase, Troponin I, neutrophil/lymphocyte ratio, serum levels of IP-10, malic acid, 3, 4 di-hydroxybutanoic acid, citric acid, myoinositol, and cystine.ConclusionsHerein, we unveil novel immunological and metabolomic features associated with COVID-19 severity and prognosis. Our models encompass the interplay among innate and adaptive immunity, inflammation-induced muscle atrophy and hypoxia as the main drivers of COVID-19 severity. |
topic |
COVID-19 TRIM63 NETs LDGs metabolomics T cells |
url |
https://www.frontiersin.org/articles/10.3389/fimmu.2021.689966/full |
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doaj-d6199e7619e84774b21a2f3624a8a9e92021-09-08T05:59:55ZengFrontiers Media S.A.Frontiers in Immunology1664-32242021-09-011210.3389/fimmu.2021.689966689966Redefining COVID-19 Severity and Prognosis: The Role of Clinical and ImmunobiotypesJiram Torres-Ruiz0Jiram Torres-Ruiz1Alfredo Pérez-Fragoso2José Luis Maravillas-Montero3Luis Llorente4Nancy R. Mejía-Domínguez5José Carlos Páez-Franco6Sandra Romero-Ramírez7Victor Andrés Sosa-Hernández8Rodrigo Cervantes-Díaz9Abdiel Absalón-Aguilar10Miroslava Nuñez-Aguirre11Guillermo Juárez-Vega12David Meza-Sánchez13Ari Kleinberg-Bid14Thierry Hernández-Gilsoul15Alfredo Ponce-de-León16Diana Gómez-Martín17Diana Gómez-Martín18Department of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoEmergency Medicine Department, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoDepartment of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoDepartment of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoDepartment of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoEmergency Medicine Department, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoDepartment of Infectious Diseases and Microbiology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoDepartment of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoRed de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, MexicoBackgroundMost of the explanatory and prognostic models of COVID-19 lack of a comprehensive assessment of the wide COVID-19 spectrum of abnormalities. The aim of this study was to unveil novel biological features to explain COVID-19 severity and prognosis (death and disease progression).MethodsA predictive model for COVID-19 severity in 121 patients was constructed by ordinal logistic regression calculating odds ratio (OR) with 95% confidence intervals (95% CI) for a set of clinical, immunological, metabolomic, and other biological traits. The accuracy and calibration of the model was tested with the area under the curve (AUC), Somer’s D, and calibration plot. Hazard ratios with 95% CI for adverse outcomes were calculated with a Cox proportional-hazards model.ResultsThe explanatory variables for COVID-19 severity were the body mass index (BMI), hemoglobin, albumin, 3-Hydroxyisovaleric acid, CD8+ effector memory T cells, Th1 cells, low-density granulocytes, monocyte chemoattractant protein-1, plasma TRIM63, and circulating neutrophil extracellular traps. The model showed an outstanding performance with an optimism-adjusted AUC of 0.999, and Somer’s D of 0.999. The predictive variables for adverse outcomes in COVID-19 were severe and critical disease diagnosis, BMI, lactate dehydrogenase, Troponin I, neutrophil/lymphocyte ratio, serum levels of IP-10, malic acid, 3, 4 di-hydroxybutanoic acid, citric acid, myoinositol, and cystine.ConclusionsHerein, we unveil novel immunological and metabolomic features associated with COVID-19 severity and prognosis. Our models encompass the interplay among innate and adaptive immunity, inflammation-induced muscle atrophy and hypoxia as the main drivers of COVID-19 severity.https://www.frontiersin.org/articles/10.3389/fimmu.2021.689966/fullCOVID-19TRIM63NETsLDGsmetabolomicsT cells |