Determinants of health as predictors for differential antibody responses following SARS-CoV-2 primary and booster vaccination in an at-risk, longitudinal cohort (preprint)

Post vaccine immunity following COVID-19 mRNA vaccination may be driven by extrinsic, or controllable and intrinsic, or inherent health factors. Thus, we investigated the effects of extrinsic and intrinsic on the peak antibody response following COVID-19 primary vaccination and on the trajectory of peak antibody magnitude and durability over time. Participants in a longitudinal cohort attended visits every 3 months for up to 2 years following enrollment. At baseline, participants provided information on their demographics, recreational behaviors, and comorbid health conditions which guided our model selection process. Blood samples were collected for serum processing and spike antibody testing at each visit. Cross-sectional and longitudinal models (linear-mixed effects models) were generated to assess the relationship between selected intrinsic and extrinsic health factors on peak antibody following vaccination and to determine the influence of these predictors on antibody over time. Following cross-sectional analysis, we observed higher peak antibody titers after primary vaccination in females, those who reported recreational drug use, younger age, and prior COVID-19 history. Following booster vaccination, females and Hispanics had higher peak titers after the 3rd and 4th doses, respectively. Longitudinal models demonstrated that Moderna mRNA-1273 recipients, females, and those previously vaccinated had increased peak titers over time. Moreover, drug users and half-dose Moderna mRNA-1273 recipients had higher peak antibody titers over time following the first booster, while no predictive factors significantly affected post-second booster antibody responses. Overall, both intrinsic and extrinsic health factors play a significant role in shaping humoral immunogenicity after initial vaccination and the first booster. The absence of predictive factors for second booster immunogenicity suggests a more robust and consistent immune response after the second booster vaccine administration.

Permissive Omicron breakthrough infections in individuals with binding or neutralizing antibodies to ancestral SARS-CoV-2 (preprint)

Background Breakthrough infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant (B.1.1.529) has occurred in populations with high vaccination rates. These infections are due to sequence variation in the spike protein leading to a reduction in protection afforded by the current vaccines, which are based on the original Wuhan-Hu-1 strain, or by natural infection with pre-Omicron strains. Methods In a longitudinal cohort study, pre-breakthrough infection sera for Omicron breakthroughs (n=12) were analyzed. Assays utilized include a laboratory-developed solid phase binding assay to recombinant spike protein, a commercial assay to the S1 domain of the spike protein calibrated to the World Health Organization (WHO) standard, and a commercial solid-phase surrogate neutralizing activity (SNA) assay. All assays employed spike protein preparations based on sequences from the Wuhan-Hu-1 strain. Participant demographics and clinical characteristics were captured. Results Pre-breakthrough binding antibody (bAB) titers ranged from 1:800-1:51,200 for the laboratory-developed binding assay, which correlated well and agreed quantitatively with the commercial spike S1 domain WHO calibrated assay. SNA was detected in 10/12 (83%) samples. Conclusions Neither high bAB nor SNA were markers of protection from Omicron infection/re-infection. Laboratory tests with antigen targets based on Wuhan-Hu-1 may not accurately reflect the degree of immune protection from variants with significant spike protein differences. Omicron breakthrough infections are likely due to high sequence variation of the spike protein and reflect incomplete immune protection from previous infection with strains that preceded Omicron or with vaccinations based on the original Wuhan-Hu-1 strain.

Predictors for Reactogenicity and Humoral Immunity to SARS-CoV-2 Following Infection and mRNA Vaccination: A Regularized Mixed-Effects Modelling Approach (preprint)

BackgroundThe influence of pre-existing humoral immunity, inter-individual demographic factors, and vaccine-associated reactogenicity on immunogenicity following COVID vaccination remains poorly understood. MethodsTen-fold cross-validated least absolute shrinkage and selection operator (LASSO) and linear mixed effects models were used to evaluate symptoms experienced during natural infection and following SARS-CoV-2 mRNA vaccination along with demographics as predictors for antibody (AB) responses in COVID+ participants in a longitudinal cohort study. ResultsIn previously infected individuals, AB were more durable and robust following vaccination when compared to natural infection alone. Higher AB were associated with experiencing dyspnea during natural infection, as was the total number of symptoms reported during the COVID-19 disease course. Both local and systemic symptoms following 1st and 2nd dose of SARS-CoV-2 mRNA vaccines were predictive of higher AB after vaccination, as were the demographic factors of age and Hispanic ethnicity. Lastly, there was a significant temporal relationship between AB and days since infection or vaccination. ConclusionVaccination in COVID+ individuals ensures a more robust immune response. Experiencing systemic and local symptoms post-vaccine is suggestive of higher AB, which may confer greater protection. Age and Hispanic ethnicity are predictive of higher AB.