RESUMO
OBJECTIVES: The role of B cells in COVID-19, beyond the production of specific antibodies against SARS-CoV-2, is still not well understood. Here, we describe the novel landscape of circulating double-negative (DN) CD27- IgD- B cells in COVID-19 patients, representing a group of atypical and neglected subpopulations of this cell lineage. METHODS: Using multiparametric flow cytometry, we determined DN B cell subset amounts from 91 COVID-19 patients, correlated those with cytokines, clinical and laboratory parameters, and segregated them by principal components analysis. RESULTS: We detected significant increments in the DN2 and DN3 B cell subsets, while we found a relevant decrease in the DN1 B cell subpopulation, according to disease severity and patient outcomes. These DN cell numbers also appeared to correlate with pro- or anti-inflammatory signatures, respectively, and contributed to the segregation of the patients into disease severity groups. CONCLUSION: This study provides insights into DN B cell subsets' potential role in immune responses against SARS-CoV-2, particularly linked to the severity of COVID-19.
Assuntos
COVID-19/sangue , COVID-19/imunologia , Imunoglobulina D/sangue , SARS-CoV-2 , Membro 7 da Superfamília de Receptores de Fatores de Necrose Tumoral/sangue , Adulto , Idoso , Idoso de 80 Anos ou mais , Linfócitos B/citologia , COVID-19/diagnóstico , COVID-19/virologia , Linhagem da Célula , Biologia Computacional , Progressão da Doença , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Análise de Componente Principal , Prognóstico , Respiração Artificial , Índice de Gravidade de Doença , Adulto JovemAssuntos
Linfócitos B/imunologia , Linfócitos T CD4-Positivos/imunologia , Linfócitos T CD8-Positivos/imunologia , COVID-19/complicações , Área Sob a Curva , Linfócitos B/metabolismo , Biomarcadores/metabolismo , Linfócitos T CD4-Positivos/metabolismo , Linfócitos T CD8-Positivos/metabolismo , COVID-19/diagnóstico , COVID-19/imunologia , Estudos de Coortes , Feminino , Humanos , Masculino , Razão de Chances , Valor Preditivo dos Testes , Curva ROC , Fatores Sexuais , Fator A de Crescimento do Endotélio Vascular/sangue , Síndrome de COVID-19 Pós-AgudaRESUMO
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.