High Titers of Low Affinity Antibodies in COVID-19 Patients Are Associated With Disease Severity.

Background: Almost 2 years from the beginning of the coronavirus disease 2019 (COVID-19) pandemic, there is still a lot unknown how the humoral response affects disease progression. In this study, we investigated humoral antibody responses against specific SARS-CoV2 proteins, their strength of binding, and their relationship with COVID severity and clinical information. Furthermore, we studied the interactions of the specific receptor-binding domain (RBD) in more depth by characterizing specific antibody response to a peptide library. Materials and Methods: We measured specific antibodies of isotypes IgM, IgG, and IgA, as well as their binding strength against the SARS-CoV2 antigens RBD, NCP, S1, and S1S2 in sera of 76 COVID-19 patients using surface plasmon resonance imaging. In addition, these samples were analyzed using a peptide epitope mapping assay, which consists of a library of peptides originating from the RBD. Results: A positive association was observed between disease severity and IgG antibody titers against all SARS-CoV2 proteins and additionally for IgM and IgA antibodies directed against RBD. Interestingly, in contrast to the titer of antibodies, the binding strength went down with increasing disease severity. Within the critically ill patient group, a positive association with pulmonary embolism, d-dimer, and antibody titers was observed. Conclusion: In critically ill patients, antibody production is high, but affinity is low, and maturation is impaired. This may play a role in disease exacerbation and could be valuable as a prognostic marker for predicting severity.

Assessment of Comorbidity in Bariatric Patients through a Biomarker-Based Model-A Multicenter Validation of the Metabolic Health Index.

BACKGROUND: The metabolic health index (MHI) is a biomarker-based model that objectively assesses the cumulative impact of comorbidities type 2 diabetes mellitus, hypertension and dyslipidemia on the health state of bariatric patients. The MHI was developed on a single-center cohort using a fully laboratory data-driven approach, resulting in a MHI score on a range from 1 to 6. To show universal applicability in clinical care, the MHI was validated externally and potential laboratory-related shortcomings were evaluated. METHODS: Retrospective laboratory and national bariatric quality registry data were collected from five Dutch renowned bariatric centers (n = 11 501). MHI imprecision was derived from the cumulative effect of biological and analytical variance of the individual input variables of the MHI model. The performance of the MHI (model) was assessed in terms of discrimination and calibration. RESULTS: The cumulative imprecision in MHI was 0.25 MHI points. Calibration of the MHI model diverged over the different centers but was accounted for by misregistration of comorbidity after cross-checking the data. Discriminative performance of the MHI model was consistent across the different centers. CONCLUSIONS: The MHI model can be applied in clinical practice of bariatric centers, regardless of patient mix and analytical platform. Because the MHI is based on objective parameters, it is insensitive to diverging clinical definitions of comorbidities. Therefore, the MHI can be used to objectify severity of metabolic comorbidities in bariatric patients. The MHI can support the patient-selection process for surgery and objectively assessing the effect of surgery on the metabolic health state.