Investigating SARS-CoV-2 infection and the health and psychosocial impact of the COVID-19 pandemic in the Canadian CHILD Cohort study: methodology and cohort profile

BackgroundThe COVID-19 pandemic is affecting all Canadian families, with some impacted differently than others. Our study aims to: 1) determine the prevalence and transmission of SARS-CoV-2 infection among Canadian families, 2) identify predictors of infection susceptibility and severity of SARS-CoV-2 and 3) identify health and psychosocial impacts of the COVID-19 pandemic. MethodsThis study builds upon the CHILD Cohort Study, an ongoing multi-ethnic general population prospective cohort consisting of 3454 Canadian families with children born in Vancouver, Edmonton, Manitoba, and Toronto between 2009-12. During the pandemic, 1462 CHILD households (5378 individuals) consented to participate in the CHILD COVID-19 Add-On Study involving: (1) brief biweekly surveys about COVID-19 symptoms and testing; (2) quarterly questionnaires assessing COVID-19 exposure, testing and vaccination status, physical and mental health, and pandemic-driven life changes; (3) in-home biological sampling kits to collect blood and stool. Mean ages were 9 years (range 0-17) for children and 43 years (range 18-85) for adults. Prevalence of SARS-CoV-2 infection will be estimated from survey data and confirmed through serology testing. We will combine these new data with a wealth of pre-pandemic CHILD data and use multivariate modelling and machine learning methods to identify risk and resilience factors for susceptibility and severity to the direct and indirect effects of the pandemic. InterpretationOur short-term findings will inform key stakeholders and knowledge users to shape current and future pandemic responses. Additionally, this study provides a unique resource to study the long-term impacts of the pandemic as the CHILD Cohort Study continues.

Longitudinal profiles of plasma gelsolin, cytokines and antibody expression predict COVID-19 severity and hospitalization outcomes

BackgroundPrognostic markers for COVID-19 disease outcome are currently lacking. Plasma gelsolin (pGSN) is an actin-binding protein and an innate immune marker involved in disease pathogenesis and viral infections. Here, we demonstrate the utility of pGSN as a prognostic marker for COVID-19 disease outcome; a test performance that is significantly improved when combined with cytokines and antibodies compared to other conventional markers such as CRP and ferritin. MethodsBlood samples were longitudinally collected from hospitalized COVID-19 patients as well as COVID-19 negative controls and the levels of pGSN in g/mL, cytokines and anti-SARS-CoV-2 spike protein antibodies assayed. Mean{+/-}SEM values were correlated with clinical parameters to develop a prognostic platform. ResultspGSN levels were significantly reduced in COVID-19 patients compared to healthy individuals. Additionally, pGSN levels combined with plasma IL-6, IP-10 and M-CSF significantly distinguished COVID-19 patients from healthy individuals. While pGSN and anti-spike IgG titers together strongly predict COVID-19 severity and death, the combination of pGSN and IL-6 was a significant predictor of milder disease and favorable outcomes. ConclusionTaken together, these findings suggest that multi-parameter analysis of pGSN, cytokines and antibodies could predict COVID-19 hospitalization outcomes with greater certainty compared with conventional clinical laboratory markers such as CRP and ferritin. This research will inform and improve clinical management and health system interventions in response to SARS-CoV-2 infection. Trial RegistrationN/A FundingThe Ottawa Hospital Department of Medicine - Special Pandemic Agile Research Competition

Plant-based production of SARS-CoV-2 antigens for use in a subunit vaccine

The COVID-19 pandemic has brought to the forefront an urgent need for the rapid development of highly efficacious vaccines, particularly in light of the ongoing emergence of multiple variants of concern. Plant-based recombinant protein platforms are emerging as cost-effective and highly scalable alternatives to conventional protein production. Viral glycoproteins, however, are historically challenging to produce in plants. Herein, we report the production of plant-expressed wild-type glycosylated SARS-CoV-2 Spike RBD (receptor-binding domain) protein that is recognized by anti-RBD antibodies and exhibits high-affinity binding to the SARS-CoV-2 receptor ACE2 (angiotensin-converting enzyme 2). Moreover, our plant-expressed RBD was readily detected by IgM, IgA, and IgG antibodies from naturally infected convalescent, vaccinated, or convalescent and vaccinated individuals. We further demonstrate that RBD binding to the ACE2 receptor was efficiently neutralized by antibodies from sera of SARS-CoV-2 convalescent and partially and fully vaccinated individuals. Collectively, these findings demonstrate that recombinant RBD produced in planta exhibits suitable biochemical and antigenic features for use in a subunit vaccine platform.

A "Made-in-Canada" serology solution for profiling humoral immune responses to SARS-CoV-2 infection and vaccination

OBJECTIVESAntibody testing against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been instrumental in detecting previous exposures and analyzing vaccine-elicited immune responses. Here, we describe a scalable solution to detect and quantify SARS-CoV-2 antibodies, discriminate between natural infection- and vaccination-induced responses, and assess antibody-mediated inhibition of the spike-angiotensin converting enzyme 2 (ACE2) interaction. METHODSWe developed methods and reagents to detect SARS-CoV-2 antibodies by enzyme-linked immunosorbent assay (ELISA). The main assays focus on the parallel detection of immunoglobulin (Ig)Gs against the spike trimer, its receptor binding domain (RBD), and nucleocapsid (N). We automated a surrogate neutralization (sn)ELISA that measures inhibition of ACE2-spike or -RBD interactions by antibodies. The assays were calibrated to a World Health Organization reference standard. RESULTSOur single-point IgG-based ELISAs accurately distinguished non-infected and infected individuals. For seroprevalence assessment (in a non-vaccinated cohort), classifying a sample as positive if antibodies were detected for [≥] 2 of the 3 antigens provided the highest specificity. In vaccinated cohorts, increases in anti-spike and -RBD (but not -N) antibodies are observed. We present detailed protocols for serum/plasma or dried blood spots analysis performed manually and on automated platforms. The snELISA can be performed automatically at single points, increasing its scalability. CONCLUSIONSMeasuring antibodies to three viral antigens and identify neutralizing antibodies capable of disrupting spike-ACE2 interactions in high-throughput enables large-scale analyses of humoral immune responses to SARS-CoV-2 infection and vaccination. The reagents are available to enable scaling up of standardized serological assays, permitting inter-laboratory data comparison and aggregation.

Relative Ratios of Human Seasonal Coronavirus Antibodies Predict the Efficiency of Cross-Neutralization of SARS-CoV-2 Spike Binding to ACE2

BackgroundAntibodies raised against human seasonal coronaviruses (sCoVs), which are responsible for the common cold, are known to cross-react with SARS-CoV-2 antigens. This prompts questions about their protective role against SARS-CoV-2 infections and COVID-19 severity. However, the relationship between sCoV exposure and SARS-CoV-2 correlates of protection are not clearly identified. MethodsWe performed a cross-sectional analysis of cross-reactivity and cross-neutralization to SARS-CoV-2 antigens (S-RBD, S-trimer, N) using pre-pandemic serum from four different groups: pediatrics and adolescents, persons 21 to 70 years of age, older than 70 years of age, and persons living with HCV or HIV. FindingsAntibody cross-reactivity to SARS-CoV-2 antigens varied between 1.6% and 15.3% depending on the cohort and the isotype-antigen pair analyzed. We also show a range of neutralizing activity (0-45%) in serum that interferes with SARS-CoV-2 spike attachment to ACE2. While the abundance of sCoV antibodies did not directly correlate with neutralization, we show that neutralizing activity is rather dependent on relative ratios of IgGs in sera directed to all four sCoV spike proteins. More specifically, we identified antibodies to NL63 and OC43 as being the most important predictors of neutralization. InterpretationOur data support that exposure to sCoVs triggers antibody responses that influence the efficiency of SARS-CoV-2 spike binding to ACE2, and may also impact COVID-19 disease severity through other latent variables. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSThere is a growing body of evidence showing that within the population there are varying levels of pre-existing immunity to SARS-CoV-2 infection and possibly COVID-19 disease severity. This immunity is believed to be attributable to prior infection by four prevalent seasonal coronaviruses (sCoVs) responsible for the common cold. Pre-existing immunity can be assessed in part by antibodies directed to sCoVs that also cross-react to SARS-CoV-2 antigens. The SARS-CoV-2 spike and, more specifically, the receptor binding domain are the primary targets for neutralizing antibodies. It is unclear if cross-reactive antibodies to SARS-CoV-2 are neutralizing and are also responsible for the broad spectrum of COVID-19 disease severity, from asymptomatic to critical, observed in the infected population. Added-value of this studyHere we carried out a detailed analysis of sCoV prevalence in samples acquired before the pandemic from individuals of various age groups and in people living with HIV and HCV. We then analyzed the frequency of all the different types of antibodies that cross-react to three SARS-CoV-2 antigens. We found a high level of people with cross-reactive antibodies, surprisingly we also detected that some people have antibodies that block the SARS-CoV-2 spike from binding to its human receptor, ACE2. By using machine learning, we were able to accurate predict which individuals can neutralize SARS-CoV-2 spike-ACE2 interactions based on their relative ratios of antibodies against the four sCoVs. Implications of all the available evidenceWe demonstrate that it not absolute levels of sCoVs antibodies that are predictive of neutralization but the relative ratios to all four sCoVs, with NL63 being the most weighted for this prediction. Machine learning also highlighted the existence of latent variables that contribute to the neutralization and that may be related to the type of cellular immune response triggered by the infection to certain sCoVs. This study is one of the first to identify a functional relationship between prior-exposure to sCoV and the establishment of a certain degree of immunity to SARS-CoV-2 by way of a cross-reactive antibody response. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=179 SRC="FIGDIR/small/21260079v3_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@e74392org.highwire.dtl.DTLVardef@1052bd5org.highwire.dtl.DTLVardef@80d88eorg.highwire.dtl.DTLVardef@10976cb_HPS_FORMAT_FIGEXP M_FIG C_FIG