In a recent study published in Emerging Infectious Diseases, researchers found significant seroreversion of total anti-nucleocapsid immunoglobulin.
Background
It is difficult to estimate the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections (frequently asymptomatic) using passive surveillance. Antibodies could help identify past infection, and population-level serologic studies have often been used to measure antibody levels for different pathogens.
Such studies provide critical inputs about the spread and epidemiology of SARS-CoV-2. Nevertheless, false negatives might result due to antibody contraction and seroreversion, that is, the loss of antibodies.
About the study
In the current study, researchers quantified antibodies against SARS-CoV-2 nucleocapsid among healthcare workers (HCWs) in the United States (US). Nucleocapsid antibodies act as markers for prior SARS-CoV-2 infection even in the vaccinated population. Over 2300 Brigham and Women’s Hospital employees were included in a longitudinal cohort study between April 28 and September 30, 2020.
The team obtained sociodemographic characteristics by electronic questionaries and collected blood samples at baseline, monthly for three months, and subsequently once every three months until February 2022. Serum samples were tested for antibodies against nucleocapsid using a double-antigen sandwich electro-chemiluminescence immunoassay (Elecsys SARS-CoV-2 N immunoassay). Dates and results of SARS-CoV-2 polymerase chain reaction (PCR) tests were retrieved from the Brigham Health electronic medical record.
A generalized additive mixed-effects model (GAMM) was used to study antibody kinetics and a linear mixed-effects model (LMM) for estimating half-life. In the GAMM approach, the natural logarithm of antibody levels was modeled as a function of time since the index PCR-positive result; a constant exponential decline after the peak level was assumed in the LMM method.
Results
125 (5.3%) participants were positive for antibodies against SARS-CoV-2 nucleocapsid between April 2020 and January 2021, when the wild-type virus was predominantly circulating. Of these, 110 (88%) subjects, who had one or more samples after the first seropositive sample, were included in the study. Most participants were females (86%) and White (88%); the median age was 33, with a median body mass index of 24 kg/mm2.
Seventy-four participants were PCR-positive before the index seropositive sample. Most participants (96%) showed symptoms, and one individual was hospitalized. Among the PCR-positive individuals, the mean peak for nucleocapsid antibodies was 37, which occurred 72 days post-index PCR-positive result. The half-life of these antibodies was estimated as 128 days, with a mean time for seroreversion at 737 days, per the LMM method.
The GAMM model showed a more rapid antibody contraction up to one year after infection, followed by slower antibody contraction and seroreversion. Besides, the authors observed a non-significant step-wise trend of a slower relative decay in the concentration of antibodies among people of older age groups.
Conclusions
The two models, LMM and GAMM, suggested a significant seroreversion by 18 months post-SARS-CoV-2 infection; the LMM estimates suggested about 50% seroreversion two years post-infection. A 1.4% per month seroreversion during 4 – 12 months post-infection was estimated using the GAMM model.
The authors revealed that seroreversion would be 19% after two years and 35% after four years, assuming a relatively constant antibody contraction after a rapid initial decay, as supported by prior studies on human coronaviruses and SARS-CoV-2. They suggested that seroreversion would affect the serologic investigations conducted a year after the widespread transmission of SARS-CoV-2.
Notably, the adult-only enrolment and overrepresentation of White participants and females in the cohort might limit the generalizability of these findings. Above all, accounting for seroreversion and global vaccine rollout would be helpful for the planning and interpretation of SARS-CoV-2 seroepidemiologic analyses.