Novel clinical and immunological features associated with persistent post-acute sequelae of COVID-19 after six months of follow-up: a pilot study.

BACKGROUND: Currently, there is scant information regarding the features associated to the persistence of post-COVID-19 syndrome, which is the main aim of the present study. METHODS: A cohort study of 102 COVID-19 patients was conducted. The post-COVID-19 symptoms were assessed by a standardised questionnaire. Lymphocyte immunophenotyping was performed by flow cytometry and chemokines/cytokines, neutrophil extracellular traps, the tripartite motif 63, anti-cellular, and anti-SARS-CoV-2 IgG antibodies were addressed in serum. The primary outcome was the persistence of post-COVID-19 syndrome after six months follow-up. RESULTS: Thirteen patients (12.7%) developed the primary outcome and had a more frequent history of post-COVID-19 syndrome 3 months after infection onset (p = .044), increased levels of IL-1α (p = .011) and IP-10 (p = .037) and increased CD57 expression in CD8+ T cells (p = .003). There was a trend towards higher levels of IFN-γ (p = .051), IL-1ß (p = .062) and IL-6 (p = .087). The history of post COVID-19 in the previous 3 months, obesity, baseline serum MIP-1α and IP-10, and CD57 expression in CD8+ T cells were independently associated with the persistence of post-COVID-19 syndrome. CONCLUSION: Our data suggest an important relationship between a pro-inflammatory state mediated through metabolic pathways related to obesity and increased cellular senescence as a key element in the persistence of post-COVID-19 syndrome at six months of follow-up.

Clinical and immunological features associated to the development of a sustained immune humoral response in COVID-19 patients: Results from a cohort study.

Background: Until now, most of the research addressing long-term humoral responses in coronavirus disease 2019 (COVID-19) had only evaluated the serum titers of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgGs, without the assessment of the baseline antiviral clinical and immune profile, which is the aim of this study and may be the key factor leading to a broad and sustained antibody response. Methods: We included 103 patients with COVID-19. When the patients sought medical attention (baseline), a blood sample was drawn to perform immunophenotype of lymphocytes by flow cytometry. The patients were assessed 15 days after baseline and then every month until the third month, followed by a last visit 6 months after recruitment. We evaluated the anti-SARS-COV-2 IgG at all time points, and the serum levels of cytokines, chemokines, anti-cellular (AC) antibodies and neutrophil extracellular traps were also assessed during the follow-up. The primary outcome of the study was the presence of a sustained immune humoral response, defined as an anti-SARS-CoV-2 IgG titer >4.99 arbitrary units/mL in at least two consecutive measures. We used generalized lineal models to assess the features associated with this outcome and to assess the effect of the changes in the cytokines and chemokines throughout time on the development of a sustained humoral immune response. Results: At baseline the features associated to a sustained immune humoral response were the diagnosis of critical disease, absolute number of lymphocytes, serum IP-10, IL-4, IL-2, regulatory T cells, CD8+ T cells, and positive AC antibodies. Critical illness and the positivity of AC antibodies were associated with a sustained humoral immune response after 3 months, whilst critical illness and serum IL-13 were the explanatory variables after 6 months. Conclusion: A sustained immune humoral response is strongly related to critical COVID-19, which is characterized by the presence of AC antibodies, quantitative abnormalities in the T cell compartment, and the serum cytokines and chemokines during acute infection and throughout time.

Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes.

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.

Neutrophil Extracellular Traps Contribute to COVID-19 Hyperinflammation and Humoral Autoimmunity.

The coronavirus disease 2019 (COVID-19) is related to enhanced production of NETs, and autoimmune/autoinflammatory phenomena. We evaluated the proportion of low-density granulocytes (LDG) by flow cytometry, and their capacity to produce NETs was compared with that of conventional neutrophils. NETs and their protein cargo were quantified by confocal microscopy and ELISA. Antinuclear antibodies (ANA), anti-neutrophil cytoplasmic antibodies (ANCA) and the degradation capacity of NETs were addressed in serum. MILLIPLEX assay was used to assess the cytokine levels in macrophages' supernatant and serum. We found a higher proportion of LDG in severe and critical COVID-19 which correlated with severity and inflammatory markers. Severe/critical COVID-19 patients had higher plasmatic NE, LL-37 and HMGB1-DNA complexes, whilst ISG-15-DNA complexes were lower in severe patients. Sera from severe/critical COVID-19 patients had lower degradation capacity of NETs, which was reverted after adding hrDNase. Anti-NET antibodies were found in COVID-19, which correlated with ANA and ANCA positivity. NET stimuli enhanced the secretion of cytokines in macrophages. This study unveils the role of COVID-19 NETs as inducers of pro-inflammatory and autoimmune responses. The deficient degradation capacity of NETs may contribute to the accumulation of these structures and anti-NET antibodies are related to the presence of autoantibodies.

Metabolomics analysis reveals a modified amino acid metabolism that correlates with altered oxygen homeostasis in COVID-19 patients.

We identified the main changes in serum metabolites associated with severe (n = 46) and mild (n = 19) COVID-19 patients by gas chromatography coupled to mass spectrometry. The modified metabolic profiles were associated to an altered amino acid catabolism in hypoxic conditions. Noteworthy, three α-hydroxyl acids of amino acid origin increased with disease severity and correlated with altered oxygen saturation levels and clinical markers of lung damage. We hypothesize that the enzymatic conversion of α-keto-acids to α- hydroxyl-acids helps to maintain NAD recycling in patients with altered oxygen levels, highlighting the potential relevance of amino acid supplementation during SARS-CoV-2 infection.

B Cell Subsets as Severity-Associated Signatures in COVID-19 Patients.

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.