COVID-19 serology at population scale: SARS-CoV-2-specific antibody responses in saliva

Author:

Randad Pranay R.,Pisanic Nora,Kruczynski Kate,Manabe Yukari C.,Thomas David,Pekosz Andrew,Klein Sabra L.,Betenbaugh Michael J.,Clarke William A.,Laeyendecker Oliver,Caturegli Patrizio P.,Larman H. Benjamin,Detrick Barbara,Fairley Jessica K.,Sherman Amy C.,Rouphael Nadine,Edupuganti Srilatha,Granger Douglas A.,Granger Steve W.,Collins Matthew,Heaney Christopher D.ORCID

Abstract

AbstractNon-invasive SARS-CoV-2 antibody testing is urgently needed to estimate the incidence and prevalence of SARS-CoV-2 infection at the general population level. Precise knowledge of population immunity could allow government bodies to make informed decisions about how and when to relax stay-at-home directives and to reopen the economy. We hypothesized that salivary antibodies to SARS-CoV-2 could serve as a non-invasive alternative to serological testing for widespread monitoring of SARS-CoV-2 infection throughout the population. We developed a multiplex SARS-CoV-2 antibody immunoassay based on Luminex technology and tested 167 saliva and 324 serum samples, including 134 and 118 negative saliva and serum samples, respectively, collected before the COVID-19 pandemic, and 33 saliva and 206 serum samples from participants with RT-PCR-confirmed SARS-CoV-2 infection. We evaluated the correlation of results obtained in saliva vs. serum and determined the sensitivity and specificity for each diagnostic media, stratified by antibody isotype, for detection of SARS-CoV-2 infection based on COVID-19 case designation for all specimens. Matched serum and saliva SARS-CoV-2 antigen-specific IgG responses were significantly correlated. Within the 10-plex SARS-CoV-2 panel, the salivary anti-nucleocapsid (N) protein IgG response resulted in the highest sensitivity for detecting prior SARS-CoV-2 infection (100% sensitivity at ≥10 days post-SARS-CoV-2 symptom onset). The salivary anti-receptor binding domain (RBD) IgG response resulted in 100% specificity. Among individuals with SARS-CoV-2 infection confirmed with RT-PCR, the temporal kinetics of IgG, IgA, and IgM in saliva were consistent with those observed in serum. SARS-CoV-2 appears to trigger a humoral immune response resulting in the almost simultaneous rise of IgG, IgM and IgA levels both in serum and in saliva, mirroring responses consistent with the stimulation of existing, cross-reactive B cells. SARS-CoV-2 antibody testing in saliva can play a critically important role in large-scale “sero”-surveillance to address key public health priorities and guide policy and decision-making for COVID-19.40-word summaryA multiplex immunoassay to detect SARS-CoV-2-specific antibodies in saliva performs with high diagnostic accuracy as early as ten days post-COVID-19 symptom onset. Highly sensitive and specific salivary COVID-19 antibody assays could advance broad immuno-surveillance goals in the USA and globally.

Publisher

Cold Spring Harbor Laboratory

Reference44 articles.

1. An interactive web-based dashboard to track COVID-19 in real time

2. Angulo, F.J. , Finelli, L . & Swerdlow, D.L . Reopening Society and the Need for Real-Time Assessment of COVID-19 at the Community Level. JAMA (2020).

3. Gronvall, G. , et al. Developing a National Strategy for Serology (Antibody Testing) in the United States. Johns Hopkins - Bloomberg School of Public Health (2020).

4. Bendavid, E. , et al. COVID-19 Antibody Seroprevalence in Santa Clara County, California. medRxiv, 2020.2004.2014.20062463-20062020.20062404.20062414.20062463 (2020).

5. Sood, N. , et al. Seroprevalence of SARS-CoV-2-Specific Antibodies Among Adults in Los Angeles County, California, on April 10-11, 2020. JAMA (2020).

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