Maternal Vaccination to Prevent Adverse Pregnancy Outcomes: An Underutilized Molecular Immunological Intervention?

Abstract

Adverse pregnancy outcomes including maternal mortality, stillbirth, preterm birth, intrauterine growth restriction cause millions of deaths each year. More effective interventions are urgently needed. Maternal immunization could be one such intervention protecting the mother and newborn from infection through its pathogen-specific effects. However, many adverse pregnancy outcomes are not directly linked to the infectious pathogens targeted by existing maternal vaccines but rather are linked to pathological inflammation unfolding during pregnancy. The underlying pathogenesis driving such unfavourable outcomes have only partially been elucidated but appear to relate to altered immune regulation by innate as well as adaptive immune responses, ultimately leading to aberrant maternal immune activation. Maternal immunization, like all immunization, impacts the immune system beyond pathogen-specific immunity. This raises the possibility that maternal vaccination could potentially be utilised as a pathogen-agnostic immune modulatory intervention to redirect abnormal immune trajectories towards a more favourable phenotype providing pregnancy protection. In this review we describe the epidemiological evidence surrounding this hypothesis, along with the mechanistic plausibility and present a possible path forward to accelerate addressing the urgent need of adverse pregnancy outcomes.

Keywords: adverse pregnancy outcomes; artificial intelligence; machine learning; maternal vaccination; systems biology.

Figure 1.. Overview of feasible approach to reducing adverse pregnancy outcomes.

Inclusion of pregnant people in vaccine studies, with particular emphasis on LMIC (first and second layer), along with sample- and data collection in prospective, globally coordinated cohort studies (third layer) followed by application of the modern tools of machine learning and artificial intelligence (fourth layer) to this data is bound to deliver the insight (fifth layer) necessary to tackling the longest, deadliest pandemic of human history, adverse pregnancy outcomes. (Figure courtesy of Wenna Lee; made in BioRender (# QI2528V08M).