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1.
J Infect Dis ; 224(9): 1489-1499, 2021 11 16.
Article in English | MEDLINE | ID: covidwho-1522216

ABSTRACT

BACKGROUND: Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a complex antibody response that varies by orders of magnitude between individuals and over time. METHODS: We developed a multiplex serological test for measuring antibodies to 5 SARS-CoV-2 antigens and the spike proteins of seasonal coronaviruses. We measured antibody responses in cohorts of hospitalized patients and healthcare workers followed for up to 11 months after symptoms. A mathematical model of antibody kinetics was used to quantify the duration of antibody responses. Antibody response data were used to train algorithms for estimating time since infection. RESULTS: One year after symptoms, we estimate that 36% (95% range, 11%-94%) of anti-Spike immunoglobulin G (IgG) remains, 31% (95% range, 9%-89%) anti-RBD IgG remains, and 7% (1%-31%) of anti-nucleocapsid IgG remains. The multiplex assay classified previous infections into time intervals of 0-3 months, 3-6 months, and 6-12 months. This method was validated using data from a seroprevalence survey in France, demonstrating that historical SARS-CoV-2 transmission can be reconstructed using samples from a single survey. CONCLUSIONS: In addition to diagnosing previous SARS-CoV-2 infection, multiplex serological assays can estimate the time since infection, which can be used to reconstruct past epidemics.


Subject(s)
Antibodies, Viral/blood , COVID-19/blood , COVID-19/immunology , Serologic Tests/methods , Adolescent , Adult , Aged , Aged, 80 and over , Antibody Formation , Antibody Specificity , COVID-19/epidemiology , Female , France/epidemiology , Humans , Immunoglobulin G/blood , Kinetics , Male , Middle Aged , SARS-CoV-2/immunology , Sensitivity and Specificity , Seroepidemiologic Studies , Young Adult
2.
J Infect Dis ; 224(9): 1489-1499, 2021 11 16.
Article in English | MEDLINE | ID: covidwho-1317919

ABSTRACT

BACKGROUND: Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a complex antibody response that varies by orders of magnitude between individuals and over time. METHODS: We developed a multiplex serological test for measuring antibodies to 5 SARS-CoV-2 antigens and the spike proteins of seasonal coronaviruses. We measured antibody responses in cohorts of hospitalized patients and healthcare workers followed for up to 11 months after symptoms. A mathematical model of antibody kinetics was used to quantify the duration of antibody responses. Antibody response data were used to train algorithms for estimating time since infection. RESULTS: One year after symptoms, we estimate that 36% (95% range, 11%-94%) of anti-Spike immunoglobulin G (IgG) remains, 31% (95% range, 9%-89%) anti-RBD IgG remains, and 7% (1%-31%) of anti-nucleocapsid IgG remains. The multiplex assay classified previous infections into time intervals of 0-3 months, 3-6 months, and 6-12 months. This method was validated using data from a seroprevalence survey in France, demonstrating that historical SARS-CoV-2 transmission can be reconstructed using samples from a single survey. CONCLUSIONS: In addition to diagnosing previous SARS-CoV-2 infection, multiplex serological assays can estimate the time since infection, which can be used to reconstruct past epidemics.


Subject(s)
Antibodies, Viral/blood , COVID-19/blood , COVID-19/immunology , Serologic Tests/methods , Adolescent , Adult , Aged , Aged, 80 and over , Antibody Formation , Antibody Specificity , COVID-19/epidemiology , Female , France/epidemiology , Humans , Immunoglobulin G/blood , Kinetics , Male , Middle Aged , SARS-CoV-2/immunology , Sensitivity and Specificity , Seroepidemiologic Studies , Young Adult
3.
Lancet Microbe ; 2(2): e60-e69, 2021 02.
Article in English | MEDLINE | ID: covidwho-1065710

ABSTRACT

BACKGROUND: Infection 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. METHODS: A 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. FINDINGS: IgG 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. INTERPRETATION: Serological 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. FUNDING: European Research Council. Fondation pour la Recherche Médicale. Institut Pasteur Task Force COVID-19.


Subject(s)
COVID-19 , Adult , Antibodies, Viral , Bayes Theorem , COVID-19/diagnosis , Humans , Immunoglobulin G , Immunoglobulin M , Machine Learning , SARS-CoV-2 , Sensitivity and Specificity , Seroepidemiologic Studies
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