Clinical predictors of donor antibody titre and correlation with recipient antibody response in a COVID-19 convalescent plasma clinical trial.

BACKGROUND: Convalescent plasma therapy for COVID-19 relies on transfer of anti-viral antibody from donors to recipients via plasma transfusion. The relationship between clinical characteristics and antibody response to COVID-19 is not well defined. We investigated predictors of convalescent antibody production and quantified recipient antibody response in a convalescent plasma therapy clinical trial. METHODS: Multivariable analysis of clinical and serological parameters in 103 confirmed COVID-19 convalescent plasma donors 28 days or more following symptom resolution was performed. Mixed-effects regression models with piecewise linear trends were used to characterize serial antibody responses in 10 convalescent plasma recipients with severe COVID-19. RESULTS: Donor antibody titres ranged from 0 to 1 : 3892 (anti-receptor binding domain (RBD)) and 0 to 1 : 3289 (anti-spike). Higher anti-RBD and anti-spike titres were associated with increased age, hospitalization for COVID-19, fever and absence of myalgia (all P < 0.05). Fatigue was significantly associated with anti-RBD (P = 0.03). In pairwise comparison amongst ABO blood types, AB donors had higher anti-RBD and anti-spike than O donors (P < 0.05). No toxicity was associated with plasma transfusion. Non-ECMO recipient anti-RBD antibody titre increased on average 31% per day during the first three days post-transfusion (P = 0.01) and anti-spike antibody titre by 40.3% (P = 0.02). CONCLUSION: Advanced age, fever, absence of myalgia, fatigue, blood type and hospitalization were associated with higher convalescent antibody titre to COVID-19. Despite variability in donor titre, 80% of convalescent plasma recipients showed significant increase in antibody levels post-transfusion. A more complete understanding of the dose-response effect of plasma transfusion amongst COVID-19-infected patients is needed.

Tissue banking from patients withSARS-CoV-2 (COVID-19) infection

The clinical spectrum of SARS-CoV-2 (COVID-19) infection ranges from asymptomatic infection to fatal pneumonia, but the determinants of outcome are not well understood. To characterize the immune response to COVID-19, weestablished a protocol to collect biologic specimens from patients with confirmed or suspected COVID-19. BetweenApril 9th and June 8th, 2020, we enrolled 146 inpatients and 169 outpatients at the University of Chicago. Wehypothesized that the complex interplay of viral, environmental, and host genetic factors may influence diseaseseverity in patients with COVID-19. To probe for genetic predispositions that may influence outcomes, we collectedgermline DNA from 140 patients spanning the breadth of clinical severity, which will be sequenced for SNPs ingenes previously implicated in immune responsiveness and ARDS. To determine whether a pattern of commensalbacteria correlates with disease severity, we will analyze the composition of airway microbiota from 226nasopharyngeal swabs, using viral quantification and 16S sequencing. Longitudinal serum samples from 156patients were obtained to probe for the presence of antibodies using an ELISA against the spike protein of SARS-CoV-2. In tandem, 36-color flow cytometry on PBMCs, from the same patients, will characterize immune cellphenotypes influenced by infection. We also hypothesized that by characterizing mechanisms of immune-hyperresponsiveness, we may elucidate key biologic pathways that inform the development of novel therapeutics.To determine if severity of disease and response to therapy correlates with soluble factors, we are performing 44-plex cytokine Luminex assays on serum samples. We will probe the adaptive immune response using an ELISAagainst the SARS-CoV-2 RBD domain, and by performing IFN-g ELISPOT analysis against peptide pools fromSARS-CoV-2 proteins. We developed a bioinformatic pipeline to integrate clinical data with the results from thediverse data types and will adopt a machine learning approach to identify parameters contributing to diseaseseverity, response to therapies, and outcomes. In establishing this protocol, there were significant biosafetyconsiderations. To limit potential exposure and virus transmission, research coordinators contacted inpatients byphone for an informed consent discussion, and patients completed the consent form electronically using REDCap(n=61). Inpatients who were unable to navigate the electronic consent were visited with a paper consent (n= 85).Samples were processed in a BSL2 laboratory with enhanced biosafety precautions. Where feasible, samples werecollected into reagents such as Zymo DNA/RNA shield to immediately inactivate the virus. Other safety measuresincluded heat inactivation of some samples and use of a laminar flow washer to minimize aerosolization duringFACS staining. In summary, we have established a biorepository of specimens from patients with COVID-19, including a subset with active cancer or a history of the disease (n=22).