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The coronavirus disease 2019 (COVID-19) survivors are frequently observed to present persistent symptoms constituting what has been called "post-acute COVID-19 syndrome" (PACS) or "long COVID-19". Some clinical risk factors have been identified to be associated with PACS development; however, specific mechanisms responsible for PACS pathology remain unknown. This study investigates clinical, immunological, and metabolomic risk factors associated with post-acute COVID-19 syndrome (PACS) in 51 patients, assessed 7-19 months after acute infection. Among the participants, 62.7% were male and 37.2% were female, with an average age of 47.8 years. At the follow-up, 37.2% met the criteria for PACS, revealing significant differences in immunological and metabolomic profiles at the time of acute infection. Patients with PACS were characterized by elevated levels of mature low-density granulocytes (LDGs), interleukin-8 (IL-8), pyruvate, pseudouridine, and cystine. Baseline multivariate analysis showed increased pyruvate and decreased alpha tocopherol levels. At follow-up, there was a decrease in absolute B lymphocytes and an increase in non-classical monocytes and 3-hydroxyisovaleric acid levels. These findings suggest that specific immunological and metabolomic markers during acute infection can help identify patients at higher risk of developing persistent PACS.

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., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

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., Competing Interests: 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., (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.)

The immune response plays a critical role in the pathophysiology of SARS-CoV-2 infection ranging from protection to tissue damage and all occur in the development of acute respiratory distress syndrome (ARDS). ARDS patients display elevated levels of inflammatory cytokines and innate immune cells, and T and B cell lymphocytes have been implicated in this dysregulated immune response. Mast cells are abundant resident cells of the respiratory tract and are able to release different inflammatory mediators rapidly following stimulation. Recently, mast cells have been associated with tissue damage during viral infections, but their role in SARS-CoV-2 infection remains unclear. In this study, we examined the profile of mast cell activation markers in the serum of COVID-19 patients. We noticed that SARS-CoV-2-infected patients showed increased carboxypeptidase A3 (CPA3) and decreased serotonin levels in their serum when compared with symptomatic SARS-CoV-2-negative patients. CPA3 levels correlated with C-reactive protein, the number of circulating neutrophils, and quick SOFA. CPA3 in serum was a good biomarker for identifying severe COVID-19 patients, whereas serotonin was a good predictor of SARS-CoV-2 infection. In summary, our results show that serum CPA3 and serotonin levels are relevant biomarkers during SARS-CoV-2 infection. This suggests that mast cells and basophils are relevant players in the inflammatory response in COVID-19 and may represent targets for therapeutic intervention., (©2021 Society for Leukocyte Biology.)

Background: SARS-CoV-2 infection represents a global health problem that has affected millions of people. The fine host immune response and its association with the disease course have not yet been fully elucidated. Consequently, we analyze circulating B cell subsets and their possible relationship with COVID-19 features and severity., Methods: Using a multiparametric flow cytometric approach, we determined B cell subsets frequencies from 52 COVID-19 patients, grouped them by hierarchical cluster analysis, and correlated their values with clinical data., Results: The frequency of CD19 + B cells is increased in severe COVID-19 compared to mild cases. Specific subset frequencies such as transitional B cell subsets increase in mild/moderate cases but decrease with the severity of the disease. Memory B compartment decreased in severe and critical cases, and antibody-secreting cells are increased according to the severity of the disease. Other non-typical subsets such as double-negative B cells also showed significant changes according to disease severity. Globally, these differences allow us to identify severity-associated patient clusters with specific altered subsets. Finally, respiratory parameters, biomarkers of inflammation, and clinical scores exhibited correlations with some of these subpopulations., Conclusions: The severity of COVID-19 is accompanied by changes in the B cell subpopulations, either immature or terminally differentiated. Furthermore, the existing relationship of B cell subset frequencies with clinical and laboratory parameters suggest that these lymphocytes could serve as potential biomarkers and even active participants in the adaptive antiviral response mounted against SARS-CoV-2., Competing Interests: 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., (Copyright © 2020 Sosa-Hernández, Torres-Ruíz, Cervantes-Díaz, Romero-Ramírez, Páez-Franco, Meza-Sánchez, Juárez-Vega, Pérez-Fragoso, Ortiz-Navarrete, Ponce-de-León, Llorente, Berrón-Ruiz, Mejía-Domínguez, Gómez-Martín and Maravillas-Montero.)