MARVELOUS: Maternal RSV Vaccination- Evaluating Optimal Immune Responses

About This Grant

PROJECT SUMMARY The recent approval of the Respiratory Syncytial Virus (RSV) vaccine for administration in pregnancy presents a novel opportunity to define immune responses of the maternal-fetal dyad, and how that response crosses the placenta and mammary tissue. Recent work indicates that timing of maternal RSV vaccination alters placental antibody transfer to the fetus. To maximize infant protection after maternal RSV vaccination, key gaps in knowledge include: 1. The extent to which maternal vaccination elicits direct fetal antigen-agnostic and antigen- specific cellular responses to augment infant protection from RSV and other infections. 2. How gestational age at vaccination alters maternal antibody response, subsequent placental and breastmilk antibody transfer, and persistence of immunity in the infant. The proposed studies will test the central hypothesis that timing of maternal vaccination, antibody Fc-receptor binding properties, glycosylation profiles, neutralizing antibody levels and non-neutralizing antibody functions are all key determinants of placental and breastmilk antibody transfer to the neonate. These antibody features will work in concert with fetal innate and adaptive immune responses to maternal vaccination, driving protection of the infant through 6 months of age. In a cohort of 400 pregnant women and their infants, this study will examine fetal cellular responses to maternal RSV vaccination, both RSV-agnostic and RSV-specific, by evaluating fetal immune cells isolated from placental villi and cord blood (Aim 1). It will comprehensively profile placentally- and breastmilk-transferred antibodies after RSV vaccination in pregnancy, evaluating IgG subclass, Fc-receptor binding, glycosylation profile, and neutralizing capacity of antibodies using in vivo and in vitro assays (Aim 2). It will then evaluate how antibody properties and timing of maternal vaccination impact the durability of antibody-mediated and cellular immunity in infant blood and breastmilk, through 6 months of age (Aim 3). Machine learning approaches will be used to estimate the magnitude and specific features of protective immune responses induced by maternal vaccination, not only for RSV, but also for influenza, Tdap, and COVID-19. These methods will generate a comprehensive model of durable infant protection from maternal vaccination spanning multiple pathogens. Defining these immune principles across the maternal-fetal dyad will generate key biological insights necessary to optimize neonatal and infant protection.