• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

Vaccine . Modeling of anti-spike IgG and neutralizing antibody waning after anti-SARS-CoV-2 mRNA vaccination

tetano

Editor, Senior Moderator
Vaccine


. 2024 Jul 19:126146.
doi: 10.1016/j.vaccine.2024.07.047. Online ahead of print. Modeling of anti-spike IgG and neutralizing antibody waning after anti-SARS-CoV-2 mRNA vaccination

Takahiro Sanada[SUP] 1 [/SUP], Tomoko Honda[SUP] 1 [/SUP], Michinori Kohara[SUP] 2 [/SUP]



Affiliations
Abstract

At present, mRNA-based vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are being administered on a global scale. While the efficacy of mRNA vaccines has been demonstrated, several unknowns remains. For example, as the number of booster vaccinations increases, there are uncertainties regarding how long effects of a vaccine will last and how much individual variability exists. In this study, to predict the duration of vaccine efficacy, we modeled the kinetics of antibody levels for each SARS-CoV-2 vaccination dose, incorporating predictive intervals to estimate the duration of vaccine efficacy and to account for variability among individuals. A total of 3,059 serum samples from 1,346 participants were assayed to quantify IgG antibodies specific for the S1 subunit of the S protein (anti-S1 IgG) and neutralizing antibody activities against SARS-CoV-2. A power law model was used to simulate the decay of antibody titers following vaccination, and models were constructed to assess antibody level kinetics after the second, third, fourth, and fifth vaccinations. The models assumed that booster vaccinations would significantly reduce the decline in anti-S antibody and neutralizing antibody levels, resulting in levels being maintained for a longer period. No significant differences in the decay rate of antibody levels were observed among age groups, yet the peak titers of antibody levels were significantly higher in the ≤ 39 age group than in the ≥ 60 age group following the second vaccination; these differences were not observed after the third and fourth vaccinations. The modeling of antibody level kinetics after vaccination is considered to be useful for understanding the immune status of mRNA vaccine recipients.

Keywords: Anti-spike antibody; Neutralizing antibody; Prediction model; SARS-CoV-2; Vaccine.

 
Back
Top Bottom