Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes.
Adult
Blood Coagulation
Body Mass Index
COVID-19
/ blood
Cytokines
/ blood
Extracellular Traps
/ immunology
Female
Hemoglobins
/ analysis
Humans
Male
Metabolome
Middle Aged
Muscular Atrophy
Neutrophils
/ immunology
Phenotype
Prognosis
SARS-CoV-2
Serum Albumin, Human
/ analysis
Severity of Illness Index
T-Lymphocytes
/ immunology
Valerates
/ blood
COVID-19
IP-10
LDGs
MCP-1
NETs
T cells
TRIM63
metabolomics
Journal
Frontiers in immunology
ISSN: 1664-3224
Titre abrégé: Front Immunol
Pays: Switzerland
ID NLM: 101560960
Informations de publication
Date de publication:
2021
2021
Historique:
received:
01
04
2021
accepted:
24
08
2021
entrez:
27
9
2021
pubmed:
28
9
2021
medline:
5
10
2021
Statut:
epublish
Résumé
Most 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). A 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. The 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. Herein, 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.
Sections du résumé
Background
Most 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).
Methods
A 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.
Results
The 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.
Conclusions
Herein, 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.
Identifiants
pubmed: 34566957
doi: 10.3389/fimmu.2021.689966
pmc: PMC8456081
doi:
Substances chimiques
Cytokines
0
Hemoglobins
0
Valerates
0
beta-hydroxyisovaleric acid
3F752311CD
Serum Albumin, Human
ZIF514RVZR
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
689966Informations de copyright
Copyright © 2021 Torres-Ruiz, Pérez-Fragoso, Maravillas-Montero, Llorente, Mejía-Domínguez, Páez-Franco, Romero-Ramírez, Sosa-Hernández, Cervantes-Díaz, Absalón-Aguilar, Nuñez-Aguirre, Juárez-Vega, Meza-Sánchez, Kleinberg-Bid, Hernández-Gilsoul, Ponce-de-León and Gómez-Martín.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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