SARS-CoV-2 antibody magnitude and detectability are driven by disease severity, timing, and assay - PubMed (original) (raw)

. 2021 Jul 30;7(31):eabh3409.

doi: 10.1126/sciadv.abh3409. Print 2021 Jul.

Saki Takahashi 2, Jill Hakim 2, J Daniel Kelly 3, Leonel Torres 2 4, Nikita S Iyer 4, Keirstinne Turcios 2, Owen Janson 2, Sadie E Munter 4, Cassandra Thanh 4, Joanna Donatelli 4, Christopher C Nixon 4, Rebecca Hoh 2, Viva Tai 2, Emily A Fehrman 2, Yanel Hernandez 2, Matthew A Spinelli 2, Monica Gandhi 2, Mary-Ann Palafox 5, Ana Vallari 5, Mary A Rodgers 5, John Prostko 5, John Hackett Jr 5, Lan Trinh 6, Terri Wrin 6, Christos J Petropoulos 6, Charles Y Chiu 7 8 9, Philip J Norris 10, Clara DiGermanio 10, Mars Stone 10, Michael P Busch 7 10, Susanna K Elledge 11, Xin X Zhou 11, James A Wells 11 12, Albert Shu 7, Theodore W Kurtz 7, John E Pak 13, Wesley Wu 13, Peter D Burbelo 14, Jeffrey I Cohen 15, Rachel L Rutishauser 4, Jeffrey N Martin 3, Steven G Deeks 2, Timothy J Henrich 4, Isabel Rodriguez-Barraquer 2, Bryan Greenhouse 2

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SARS-CoV-2 antibody magnitude and detectability are driven by disease severity, timing, and assay

Michael J Peluso et al. Sci Adv. 2021.

Abstract

Interpretation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurveillance studies is limited by poorly defined performance of antibody assays over time in individuals with different clinical presentations. We measured antibody responses in plasma samples from 128 individuals over 160 days using 14 assays. We found a consistent and strong effect of disease severity on antibody magnitude, driven by fever, cough, hospitalization, and oxygen requirement. Responses to spike protein versus nucleocapsid had consistently higher correlation with neutralization. Assays varied substantially in sensitivity during early convalescence and time to seroreversion. Variability was dramatic for individuals with mild infection, who had consistently lower antibody titers, with sensitivities at 6 months ranging from 33 to 98% for commercial assays. Thus, the ability to detect previous infection by SARS-CoV-2 is highly dependent on infection severity, timing, and the assay used. These findings have important implications for the design and interpretation of SARS-CoV-2 serosurveillance studies.

Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

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Figures

Fig. 1

Fig. 1. Longitudinal antibody kinetics.

Time since symptom onset is shown on the x axis versus the measured antibody response for each assay. For asymptomatic individuals, the time since the first positive polymerase chain reaction (PCR) test was used. Black points indicate individual time points, and longitudinal samples are connected with gray lines. y axes are transformed as indicated in Table 2. Assay units are as follows: S-Lum (conc, relative concentration), RBD-Lum (conc, relative concentration), RBD-LIPS (LU, light unit), RBD-Split Luc (RLU, relative light unit), S-Ortho IgG (S/C, sample result to calibrator result index), S-Ortho Ig (S/C, sample result to calibrator result index), S-DiaSorin (AU/ml, arbitrary unit per milliliter), N(full)-Lum (conc, relative concentration), N(frag)-Lum (conc, relative concentration), N-LIPS (LU, light unit), N-Split Luc (RLU, relative light unit), N-Abbott (S/C, sample result to calibrator result index), N-Roche (COI, cutoff index), and Neut-Monogram (ID50, 50% inhibitory dilution). Red dotted lines indicate cutoff values for positivity, as indicated in Table 2.

Fig. 2

Fig. 2. Correlation of responses between assays.

(A) Spearman correlation of random intercepts derived from a mixed-effects model, representing responses at 21 days after symptom onset for each individual from the longitudinal data. Assays are sorted by hierarchical clustering using average distance clustering. Darker blue indicates higher correlation; colored label box indicates antigen for each binding assay and the neutralizing assay. (B) Pairwise scatterplots showing the random intercepts for the neutralizing assay (x axis) versus the random intercepts for each of the other assays (y axis). Assay units are indicated in Table 2.

Fig. 3

Fig. 3. Severity-stratified antibody response at baseline.

Swarm plot of antibody response at the baseline visit for each study participant by assay, stratified into individuals who experienced no symptoms, individuals who experienced symptoms but were not hospitalized, and those who experienced symptoms and were hospitalized. y axes are transformed as indicated in Table 2.

Fig. 4

Fig. 4. Clinical predictors of antibody responses.

Rank of variable importance (1 = highest rank; 50 = lowest rank) in a random forest classifier of top half versus bottom half of responders for each assay, based on random intercepts, including (A) all individuals (n = 128) and (B) only individuals who were not hospitalized (n = 97), as hospitalization is a strong predictor of antibody response. Variable importance was determined as the reduction in classification error averaged across 10 runs of the algorithm. Variables only relevant to hospitalized individuals (i.e., whether the individual was hospitalized, whether oxygen was required, whether the individual was in the ICU, and whether the individual required a ventilator) were omitted from the classifier in (B) and shown in gray. In addition, HIV status is excluded as a predictor for the Neut-Monogram assay for reasons described in the main text. The dependent variable (individual-level random intercepts derived from a mixed-effects model) is dichotomized into “high” and “low,” determined by the random intercept being in the upper or lower half of all random intercepts for that assay, respectively. Full labels of the predictor variables are provided in table S10.

Fig. 5

Fig. 5. Estimated time to seroreversion and assay sensitivity by time and hospitalization status.

(A) Mean time to seroreversion for individuals tested on each assay, stratified by hospitalization status, with 95% confidence intervals derived from bootstrapping. The symbol “‡” indicates increasing antibody responses over time (95% confidence interval for time to seroreversion was negative and did not cross 0), and the symbol “*” indicates antibody responses for which 95% confidence interval of time to seroreversion crossed 0. (B) Estimated sensitivity of each assay (showing posterior median estimates and 95% credible intervals), stratified by hospitalization status at 2-month intervals, from 0 to 6 months after seroconversion. Seroconversion was assumed to occur (if at all) 21 days after symptom onset (if symptomatic) or 21 days after positive PCR test (if asymptomatic).

Fig. 6

Fig. 6. Negative predictive values of the commercial assays.

Negative predictive values shown are based on the estimated assay sensitivities for nonhospitalized individuals in Fig. 5B, for a range of prevalence between 5 and 50% (x axis). Bottom panels show the same data with a smaller range in the y axis to visualize small differences.

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