Child Health Impacts of Injury in Pregnancy (CHIIP) - SUMMARY In the United States, 8% of pregnant women experience a severe injury prepartum, with profound consequences on the pregnancy and the fetus, including physiological stress responses, placental trauma, as well as birth and pregnancy complications. Our results, published in Nature Medicine, show that such injuries are associated with up to a 2-fold increase in achild’s autism risk. However, the broader neurodevelopmental implications of maternal injury and the underlying mechanisms remain largely unexplored. This status quo precludes the identification of potentially modifiable risk factors for neurodevelopmental disorders, the early identification of at-risk children, and the development of effective interventions in pregnancies affected by maternal injury. Our proposal seeks to address these knowledge gaps by leveraging large-scale EHR and genetic resources. We will use advanced epidemiological and causal inference approaches to (i) establish the spectrumof neurodevelopmental outcomes associated with maternal injury; (ii) isolate the etiological mechanisms underlying these associations – including a thorough assessment of potential familial confounders; and (iii) identify the potential mediators and mitigators of risk, including trauma management strategies. Additionally, we will generate and share genomic sequence data for an established Child Health and Environment Study (CHES), contributing a novel resource for applications in other perinatal epidemiology studies. Aim 1: Isolate the effects of maternal injury on child neurodevelopmental and neurological outcomes using Epic Cosmos data (>11M mother-child dyads), including in relation to maternal injury timing, its site, and severity. Leveraging a causal mediation framework and moderation approaches, we will identify critical obstetric mediators and potential intervention pathways. Aim 2: Determine if the associations between maternal injury and offspring outcomes are due to maternal and familial confounders, by implementing a suite of causal inference designs in Epic Cosmos and CHES data, including sibling and analyses and the use of negative control of pre-pregnancy injury. Aim 3: Elucidate the gene-environment (G-E) effects in the associations between maternal injury and offspring outcomes, including both G-E correlation and additive effects. The innovation of this project is three-fold: (i) it uses large-scale US EHR Epic data for family-based analyses, leveraging the novel family linkage to implement causal designs that up to now were predominantly conducted outside of the US; (ii) it generates a novel mother-child genomic resource, building upon the established CHES cohort; this resource will be made open access, enabling applications across perinatal epidemiology projects;(iii) it examines the impacts of injury management strategies, thus not only identifying a new risk factor, but also isolating the critical pathways towards its modifiability. The translational significance of this work will be novel insights into the effects of injury in pregnancy on brain development, rigorously disentangling causal mechanisms and gene-environment interactions, and ascertaining the critical obstetric and ER-based factors influencing the impacts of maternal injury.
