ABSTRACT
Neutralizing antibody (nAb) responses are attenuated in solid organ transplant recipients (SOTRs) despite severe acute respiratory syndrome-coronavirus-2 vaccination. Preexposure prophylaxis (PrEP) with the antibody combination tixagevimab and cilgavimab (T+C) might augment immunoprotection, yet in vitro activity and durability against Omicron sublineages BA.4/5 in fully vaccinated SOTRs have not been delineated. Vaccinated SOTRs, who received 300 + 300 mg T+C (ie, full dose), within a prospective observational cohort submitted pre and postinjection samples between January 31, 2022, and July 6, 2022. The peak live virus nAb was measured against Omicron sublineages (BA.1, BA.2, BA.2.12.1, and BA.4), and surrogate neutralization (percent inhibition of angiotensin-converting enzyme 2 receptor binding to full length spike, validated vs live virus) was measured out to 3 months against sublineages, including BA.4/5. With live virus testing, the proportion of SOTRs with any nAb increased against BA.2 (47%-100%; P < .01), BA.2.12.1 (27%-80%; P < .01), and BA.4 (27%-93%; P < .01), but not against BA.1 (40%-33%; P = .6). The proportion of SOTRs with surrogate neutralizing inhibition against BA.5, however, fell to 15% by 3 months. Two participants developed mild severe acute respiratory syndrome-coronavirus-2 infection during follow-up. The majority of fully vaccinated SOTRs receiving T+C PrEP achieved BA.4/5 neutralization, yet nAb activity commonly waned by 3 months postinjection. It is critical to assess the optimal dose and interval of T+C PrEP to maximize protection in a changing variant climate.
Subject(s)
COVID-19 , Transplant Recipients , Humans , Antibodies, Monoclonal , Antibodies, Neutralizing , Antibodies, ViralABSTRACT
BACKGROUND: Solid organ transplant recipients (SOTRs) are less likely to mount an antibody response to SARS-CoV-2 mRNA vaccines. Understanding risk factors for impaired vaccine response can guide strategies for antibody testing and additional vaccine dose recommendations. METHODS: Using a nationwide observational cohort of 1031 SOTRs, we created a machine learning model to explore, identify, rank, and quantify the association of 19 clinical factors with antibody responses to 2 doses of SARS-CoV-2 mRNA vaccines. External validation of the model was performed using a cohort of 512 SOTRs at Houston Methodist Hospital. RESULTS: Mycophenolate mofetil use, a shorter time since transplant, and older age were the strongest predictors of a negative antibody response, collectively contributing to 76% of the model's prediction performance. Other clinical factors, including transplanted organ, vaccine type (mRNA-1273 versus BNT162b2), sex, race, and other immunosuppressants, showed comparatively weaker associations with an antibody response. This model showed moderate prediction performance, with an area under the receiver operating characteristic curve of 0.79 in our cohort and 0.67 in the external validation cohort. An online calculator based on our prediction model is available at http://transplantmodels.com/covidvaccine/ . CONCLUSIONS: Our machine learning model helps understand which transplant patients need closer follow-up and additional doses of vaccine to achieve protective immunity. The online calculator based on this model can be incorporated into transplant providers' practice to facilitate patient-centric, precision risk stratification and inform vaccination strategies among SOTRs.