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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Main Authors: 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
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Immunology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2021.689966/full
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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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spelling 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