1. Quantitative mechanistic model reveals key determinants of placental IgG transfer and informs prenatal immunization strategies.
- Author
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Wessel, Remziye E. and Dolatshahi, Sepideh
- Subjects
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IMMUNOGLOBULINS , *IMMUNOGLOBULIN G , *PLACENTA , *IMMUNIZATION , *FC receptors , *FETUS , *IMMUNE system - Abstract
Transplacental antibody transfer is crucially important in shaping neonatal immunity. Recently, prenatal maternal immunization has been employed to boost pathogen-specific immunoglobulin G (IgG) transfer to the fetus. Multiple factors have been implicated in antibody transfer, but how these key dynamic regulators work together to elicit the observed selectivity is pertinent to engineering vaccines for mothers to optimally immunize their newborns. Here, we present the first quantitative mechanistic model to uncover the determinants of placental antibody transfer and inform personalized immunization approaches. We identified placental FcγRIIb expressed by endothelial cells as a limiting factor in receptor-mediated transfer, which plays a key role in promoting preferential transport of subclasses IgG1, IgG3, and IgG4, but not IgG2. Integrated computational modeling and in vitro experiments reveal that IgG subclass abundance, Fc receptor (FcR) binding affinity, and FcR abundance in syncytiotrophoblasts and endothelial cells contribute to inter-subclass competition and potentially inter- and intra-patient antibody transfer heterogeneity. We developed an in silico prenatal vaccine testbed by combining a computational model of maternal vaccination with this placental transfer model using the tetanus, diphtheria, and acellular pertussis (Tdap) vaccine as a case study. Model simulations unveiled precision prenatal immunization opportunities that account for a patient's anticipated gestational length, placental size, and FcR expression by modulating vaccine timing, dosage, and adjuvant. This computational approach provides new perspectives on the dynamics of maternal-fetal antibody transfer in humans and potential avenues to optimize prenatal vaccinations that promote neonatal immunity. Author summary: Newborns are vulnerable to infections due to their naïve immune system. Maternal antibodies transferred through the placenta protect the newborn while their own immune system acclimates to the environment outside of the womb. As the dampened immune response in early life presents a challenge to newborn vaccination, maternal vaccines are used to boost pathogen-specific antibody transfer. Despite the exciting therapeutic potential of this approach, few maternal vaccines are currently in use and experimental limitations pose a challenge to optimizing maternal vaccine strategies. To uncover mechanistic insights into this process and inform vaccine design, we developed the first computational model of placental antibody transfer. Model simulations revealed antibody abundance and placental Fc receptor expression determine transfer efficiency. We use this computational model to perform in silico immunization optimization experiments, revealing two key insights: (1) second trimester vaccination may be an effective population-level strategy for all neonates and (2) vaccination programs can be optimized in a vaccine- and patient-specific manner to maximize transfer of vaccine-induced antibodies. Ultimately, this model will expedite translation of novel immunization strategies from bench to bedside. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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