[HTML][HTML] Ultrasensitive high-resolution profiling of early seroconversion in patients with COVID-19

M Norman, T Gilboa, AF Ogata, AM Maley… - Nature biomedical …, 2020 - nature.com
M Norman, T Gilboa, AF Ogata, AM Maley, L Cohen, EL Busch, R Lazarovits, CP Mao, Y Cai
Nature biomedical engineering, 2020nature.com
Sensitive assays are essential for the accurate identification of individuals infected with
severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we report a
multiplexed assay for the fluorescence-based detection of seroconversion in infected
individuals from less than 1 µl of blood, and as early as the day of the first positive nucleic
acid test after symptom onset. The assay uses dye-encoded antigen-coated beads to
quantify the levels of immunoglobulin G (IgG), IgM and IgA antibodies against four SARS …
Abstract
Sensitive assays are essential for the accurate identification of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we report a multiplexed assay for the fluorescence-based detection of seroconversion in infected individuals from less than 1 µl of blood, and as early as the day of the first positive nucleic acid test after symptom onset. The assay uses dye-encoded antigen-coated beads to quantify the levels of immunoglobulin G (IgG), IgM and IgA antibodies against four SARS-CoV-2 antigens. A logistic regression model trained using samples collected during the pandemic and samples collected from healthy individuals and patients with respiratory infections before the first outbreak of coronavirus disease 2019 (COVID-19) was 99% accurate in the detection of seroconversion in a blinded validation cohort of samples collected before the pandemic and from patients with COVID-19 five or more days after a positive nasopharyngeal test by PCR with reverse transcription. The high-throughput serological profiling of patients with COVID-19 allows for the interrogation of interactions between antibody isotypes and viral proteins, and should help us to understand the heterogeneity of clinical presentations.
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