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Highly Sensitive and Specific Multiplex Antibody Assays To Quantify Immunoglobulins M, A, and G against SARS-CoV-2 Antigens.

ABSTRACT: Reliable serological tests are required to determine the prevalence of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to characterize immunity to the disease in order to address key knowledge gaps in the coronavirus disease 2019 (COVID-19) pandemic. Quantitative suspension array technology (qSAT) assays based on the xMAP Luminex platform overcome the limitations of rapid diagnostic tests and enzyme-linked immunosorbent assays (ELISAs) with their higher precision, dynamic range, throughput, miniaturization, cost-efficiency, and multiplexing capacity. We developed three qSAT assays for IgM, IgA, and IgG against a panel of eight SARS-CoV-2 antigens, including spike protein (S), nucleocapsid protein (N), and membrane protein (M) constructs. The assays were optimized to minimize the processing time and maximize the signal-to-noise ratio. We evaluated their performances using 128 prepandemic plasma samples (negative controls) and 104 plasma samples from individuals with SARS-CoV-2 diagnosis (positive controls), of whom 5 were asymptomatic, 51 had mild symptoms, and 48 were hospitalized. Preexisting IgG antibodies recognizing N, M, and S proteins were detected in negative controls, which is suggestive of cross-reactivity to common-cold coronaviruses. The best-performing antibody/antigen signatures had specificities of 100% and sensitivities of 95.78% at ≥14 days and 95.65% at ≥21 days since the onset of symptoms, with areas under the curve (AUCs) of 0.977 and 0.999, respectively. Combining multiple markers as assessed by qSAT assays has the highest efficiency, breadth, and versatility to accurately detect low-level antibody responses for obtaining reliable data on the prevalence of exposure to novel pathogens in a population. Our assays will allow gaining insights into antibody correlates of immunity and their kinetics, required for vaccine development to combat the COVID-19 pandemic.

SUBMITTER: Dobano C

PROVIDER: S-EPMC8111153 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundInfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces an antibody response targeting multiple antigens that changes over time. This study aims to take advantage of this complexity to develop more accurate serological diagnostics.MethodsA multiplex serological assay was developed to measure IgG and IgM antibody responses to seven SARS-CoV-2 spike or nucleoprotein antigens, two antigens for the nucleoproteins of the 229E and NL63 seasonal coronaviruses, and three non-coronavirus antigens. Antibodies were measured in serum samples collected up to 39 days after symptom onset from 215 adults in four French hospitals (53 patients and 162 health-care workers) with quantitative RT-PCR-confirmed SARS-CoV-2 infection, and negative control serum samples collected from healthy adult blood donors before the start of the SARS-CoV-2 epidemic (335 samples from France, Thailand, and Peru). Machine learning classifiers were trained with the multiplex data to classify individuals with previous SARS-CoV-2 infection, with the best classification performance displayed by a random forests algorithm. A Bayesian mathematical model of antibody kinetics informed by prior information from other coronaviruses was used to estimate time-varying antibody responses and assess the sensitivity and classification performance of serological diagnostics during the first year following symptom onset. A statistical estimator is presented that can provide estimates of seroprevalence in very low-transmission settings.FindingsIgG antibody responses to trimeric spike protein (Stri) identified individuals with previous SARS-CoV-2 infection with 91·6% (95% CI 87·5-94·5) sensitivity and 99·1% (97·4-99·7) specificity. Using a serological signature of IgG and IgM to multiple antigens, it was possible to identify infected individuals with 98·8% (96·5-99·6) sensitivity and 99·3% (97·6-99·8) specificity. Informed by existing data from other coronaviruses, we estimate that 1 year after infection, a monoplex assay with optimal anti-Stri IgG cutoff has 88·7% (95% credible interval 63·4-97·4) sensitivity and that a four-antigen multiplex assay can increase sensitivity to 96·4% (80·9-100·0). When applied to population-level serological surveys, statistical analysis of multiplex data allows estimation of seroprevalence levels less than 2%, below the false-positivity rate of many other assays.InterpretationSerological signatures based on antibody responses to multiple antigens can provide accurate and robust serological classification of individuals with previous SARS-CoV-2 infection. This provides potential solutions to two pressing challenges for SARS-CoV-2 serological surveillance: classifying individuals who were infected more than 6 months ago and measuring seroprevalence in serological surveys in very low-transmission settings.FundingEuropean Research Council. Fondation pour la Recherche Médicale. Institut Pasteur Task Force COVID-19.

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Highly Sensitive and Specific Multiplex Antibody Assays To Quantify Immunoglobulins M, A, and G against SARS-CoV-2 Antigens.

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