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Pre-vaccine sentinel antibodies predict blunted vaccine responses
Lusheng Song1, Jin G Park1, Ji Qiu1
1Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Abstract:
Predicting which individuals will mount poor antibody responses before vaccination could improve personalized vaccination strategies. Here, we conducted a national longitudinal study of humoral immune responses to 185 antigens, including SARS-CoV-2 (n = 3), common microbial pathogens (n = 157), and autoantigens (n = 25), in 1,644 immunosuppressed patients and 2,445 healthy individuals before and after COVID-19 vaccination. Although blunted COVID-19 vaccine responses were more frequent in solid organ transplant recipients and individuals with multiple myeloma, autoimmune disease, inflammatory bowel disease, and human immunodeficiency virus, responses were highly heterogeneous within every cohort, and approximately 5-6% of healthy individuals also mounted weak responses. Pre-existing antibodies to common microbes, including Staphylococcus aureus, respiratory syncytial virus, and human respirovirus 3, consistently predicted post-vaccination antibody responses in both healthy and immunosuppressed populations. These broadly prevalent antimicrobial antibodies represent sentinel antibodies that may serve as biomarkers of system-level humoral immune competence. Using global antimicrobial antibody profiles, we developed a deep-learning predictive model that stratified individuals according to their likelihood of mounting blunted vaccine responses. Together, these findings identify pre-existing antimicrobial antibody profiles as scalable biomarkers of humoral immune responsiveness and provide a framework for predicting vaccine responses before immunization.
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