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Distinct SARS-CoV-2 Antibody Reactivity Patterns in Coronavirus Convalescent Plasma Revealed by a Coronavirus Antigen Microarray

By Rafael Assis, Aarti Jain, Rie Nakajima, Algis Jasinskas, Saahir Khan, Larry J. Dumont, Kathleen Kelly, Graham Simmons, Mars Stone, Clara Di Germanio, Michael Busch, Philip L Felgner

Posted 17 Sep 2020
bioRxiv DOI: 10.1101/2020.09.16.300871

A coronavirus antigen microarray (COVAM) was constructed containing 11 SARS-CoV-2, 5 SARS-1, 5 MERS, and 12 seasonal coronavirus recombinant proteins. The array is designed to measure immunoglobulin isotype and subtype levels in serum or plasma samples against each of the individual antigens printed on the array. We probed the COVAM with COVID-19 convalescent plasma (CCP) collected from 99 donors who recovered from a PCR+ confirmed SARS-CoV-2 infection. The results were analyzed using two computational approaches, a generalized linear model (glm) and Random Forest (RF) prediction model, to classify individual specimens as either Reactive or Non-Reactive against the SARS-CoV-2 antigens. A training set of 88 pre-COVID-19 specimens (PreCoV) collected in August 2019 and102 positive specimens from SARS-CoV-2 PCR+ confirmed COVID-19 cases was used for these analyses. Results compared with an FDA emergency use authorized (EUA) SARS-CoV2 S1-based total Ig chemiluminescence immunoassay (Ortho Clinical Diagnostics VITROSĀ® Anti-SARS-CoV-2 Total, CoV2T) and with a SARS-CoV-2 S1-S2 spike-based pseudovirus micro neutralization assay (SARS-CoV-2 reporter viral particle neutralization titration (RVPNT) showed high concordance between the 3 assays. Three CCP specimens that were negative by the VITROS CoV2T immunoassay were also negative by both COVAM and the RVPNT assay. Concordance between VITROS CoV2T and COVAM was 96%, VITROS CoV2T and RVPNT 93%, and RVPNT and COVAM 95%. The discordances were all weakly reactive samples near the cutoff threshold of the VITROS CoV2T immunoassay. The multiplex COVAM allows CCP to be grouped according to antibody reactivity patterns against 11 SARS-CoV-2 antigens. Unsupervised K-means analysis, via the gap statistics, as well as hierarchical clustering analysis revealed 3 main clusters with distinct reactivity intensities and patterns. These patterns were not recapitulated by adjusting the VITROS CoV2T or RVPNT assay thresholds. Plasma classified according to these reactivity patterns may be better associated with CCP treatment efficacy than antibody levels alone. The use of a SARS-CoV-2 antigen array may be useful to qualify CCP for administration as a treatment for acute COVID-19 and to interrogate vaccine immunogenicity and performance in preclinical and clinical studies to understand and recapitulate antibody responses associated with protection from infection and disease. ### Competing Interest Statement The authors have declared no competing interest.

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