Expanding the Value of the EARLI study: Small Cohort with Big Data

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Neurodevelopmental disorders (NDDs), including ASD, affect over 15 percent of US children – Autism Spectrum Disorder (ASD) alone affects approximately 1.5% of US children. Identification of underlying causes can lead to primary and secondary prevention efforts. Substantial evidence supports contribution of both genes and environment, particularly prenatal exposures. Prospective studies, with exposure information collected during pregnancy, prior to symptom onset, are sorely needed although prospective studies in the general population are not feasible, cost effective, or efficient for ASD. The enriched-familial-risk design, which capitalizes on the substantial recurrence risk of both ASD and NDD among siblings of children with ASD, has been employed to achieve prospective data collection with reasonable outcome events. The Early Autism Risk Longitudinal Investigation (EARLI) study has helped to trailblaze this enriched risk cohort approach. EARLI recruited and followed over 260 pregnant women who already had a child with ASD with multiple study visits, child assessments, biosampling, and home environment surveys over pregnancy and the first 3 years of life. While the total sample size was constrained; the value of EARLI is the depth of longitudinal data and molecular measurements across multiple tissue types and early developmental windows. To date, over 9.4 billion data points have been generated across multiple phenotypes, tissues, exposures, and -omic measures. The current proposal seeks to maintain and enrich this valuable study to fully realize its impact on environmental health. The goals are to: 1. Maintain and extend the EARLI Biosample Repository through support of the storage and retrieval efforts and addition and storage of shed baby teeth that will enable longitudinal prenatal exposure measures across a growing array of toxicant exposures. 2. Measure frequency and patterns of emerging co-occurring conditions at school age to better characterize phenotypes across co-occurring NDDs and quantitative traits. 3. Characterize variability of heavy metals measurement across timing, family members, and matrices including maternal blood and urine and shed baby teeth. 4. Develop and apply methods for phenotype and for exposure harmonization using latent constructs, enabling within and cross- cohort investigations; 5. Migrate, enhance, and increase the reproducibility of EARLI research data to enable data sharing. The EARLI study is a valuable asset to early life environmental epidemiology of neurodevelopmental outcomes. Conducting these aims will allow us to maximize the contribution of this novel study to the understanding of ASD and NDD etiology.