Predicting humoral responses to primary and booster SARS-CoV-2 mRNA vaccination in people living with HIV: a machine learning approach.

BACKGROUND: SARS-CoV-2 mRNA vaccines are highly immunogenic in people living with HIV (PLWH) on effective antiretroviral therapy (ART). However, whether viro-immunologic parameters or other factors affect immune responses to vaccination is debated. This study aimed to develop a machine learning-based model able to predict the humoral response to mRNA vaccines in PLWH and to assess the impact of demographic and clinical variables on antibody production over time. METHODS: Different machine learning algorithms have been compared in the setting of a longitudinal observational study involving 497 PLWH, after primary and booster SARS-CoV-2 mRNA vaccination. Both Generalized Linear Models and non-linear Models (Tree Regression and Random Forest) were trained and tested. RESULTS: Non-linear algorithms showed better ability to predict vaccine-elicited humoral responses. The best-performing Random Forest model identified a few variables as more influential, within 39 clinical, demographic, and immunological factors. In particular, previous SARS-CoV-2 infection, BMI, CD4 T-cell count and CD4/CD8 ratio were positively associated with the primary cycle immunogenicity, yet their predictive value diminished with the administration of booster doses. CONCLUSIONS: In the present work we have built a non-linear Random Forest model capable of accurately predicting humoral responses to SARS-CoV-2 mRNA vaccination, and identifying relevant factors that influence the vaccine response in PLWH. In clinical contexts, the application of this model provides promising opportunities for predicting individual vaccine responses, thus facilitating the development of vaccination strategies tailored for PLWH.

Homologous or heterologous administration of mRNA or adenovirus-vectored vaccines show comparable immunogenicity and effectiveness against the SARS-CoV-2 Omicron variant.

BACKGROUND: Heterologous prime-boost schedules have been employed in SARS-CoV-2 vaccination, yet additional data on immunogenicity and effectiveness are still needed. RESEARCH DESIGN AND METHODS: Here, we measured the immunogenicity and effectiveness in the real-world setting of the mRNA booster dose in 181 subjects who had completed primary vaccination with ChAdOx1, BNT162b2, or mRNA1273 vaccines (IMMUNO_COV study; protocol code 18,869). The spike-specific antibody and B cell responses were analyzed up to 6 months after boosting. RESULTS: After an initial slower antibody response, the heterologous ChAdOx1/mRNA prime-boost formulation elicited spike-specific IgG titers comparable to homologous approaches, while spike-specific B cells showed a higher percentage of CD21-CD27- atypical cells compared to homologous mRNA vaccination. Mixed combinations of BNT162b2 and mRNA-1273 elicited an immune response comparable with homologous strategies. Non-significant differences in the Relative Risk of infection, calculated over a period of 18 months after boosting, were reported among homologous or heterologous vaccination groups, indicating a comparable relative vaccine effectiveness. CONCLUSIONS: Our data endorse the heterologous booster vaccination with mRNA as a valuable alternative to homologous schedules. This approach can serve as a solution in instances of formulation shortages and contribute to enhancing vaccine strategies for potential epidemics or pandemics.

Trajectory of Spike-Specific B Cells Elicited by Two Doses of BNT162b2 mRNA Vaccine.

The mRNA vaccines for SARS-CoV-2 have demonstrated efficacy and immunogenicity in the real-world setting. However, most of the research on vaccine immunogenicity has been centered on characterizing the antibody response, with limited exploration into the persistence of spike-specific memory B cells. Here we monitored the durability of the memory B cell response up to 9 months post-vaccination, and characterized the trajectory of spike-specific B cell phenotypes in healthy individuals who received two doses of the BNT162b2 vaccine. To profile the spike-specific B cell response, we applied the tSNE and Cytotree automated approaches. Spike-specific IgA+ and IgG+ plasmablasts and IgA+ activated cells were observed 7 days after the second dose and disappeared 3 months later, while subsets of spike-specific IgG+ resting memory B cells became predominant 9 months after vaccination, and they were capable of differentiating into spike-specific IgG secreting cells when restimulated in vitro. Other subsets of spike-specific B cells, such as IgM+ or unswitched IgM+IgD+ or IgG+ double negative/atypical cells, were also elicited by the BNT162b2 vaccine and persisted up to month 9. The analysis of circulating spike-specific IgG, IgA, and IgM was in line with the plasmablasts observed. The longitudinal analysis of the antigen-specific B cell response elicited by mRNA-based vaccines provides valuable insights into our understanding of the immunogenicity of this novel vaccine platform destined for future widespread use, and it can help in guiding future decisions and vaccination schedules.