Mapping internal exposome-metabolome dynamics with advanced data science to identify environmental determinants of autism.

ABSTRACT Neurodevelopmental disabilities among autistic people are an increasing public health concern in the U.S. Current prevalence estimates indicate that 1 in 31 school-aged children have autism, and the increase in recent decades strongly supports environmental factors as key contributors. However, there have been no systematic studies of complex environmental exposures contributing to the likelihood of developing autism. Leveraging a powerful untargeted high-resolution mass spectrometry (HRMS) approach and two large, multi-site autism studies from the U.S. that already include extensive genetic, omics, questionnaire, targeted exposure, and phenotype data, we will create the largest exposome database for autism and an Autism Exposome Atlas well-powered for foundational discovery analyses of non-genetic factors driving autism outcomes, including the role of critical developmental periods and familial studies supporting differentiation between shared environmental and genetic influences. The exposome represents cumulative life-long environmental exposures that produce biological response signatures influencing health; exposome characterization is widely recognized as the greatest unmet challenge in children’s environmental health. Our team is at the forefront in developing critical advances in HRMS methodologies and algorithms for chemical detection, high-dimensional approaches for biomarker selection, and advanced mixtures statistics that address the complexity of the real-life environment. We are thus poised to conduct cutting-edge exposomic research on environmental drivers of autism-associated health outcomes. In support of the Autism Data Science Initiative (ADSI) Tasks II and III, we will apply these approaches to establish dynamic exposome-metabolome signatures of autism outcomes. We will leverage children and parent biospecimens collected from participants enrolled in the Early Autism Risk Longitudinal Investigation (EARLI) and the Study to Explore Early Development (SEED) cohorts to 1) Develop a comprehensive database of environmental, dietary, and chemical biomarkers that influence autism development; 2) Assemble a unified Autism Exposome Atlas through comprehensive and high- throughput chemical exposome profiling of 7,812 blood samples (including autism cases and their parents) for profiling of environmental, dietary, pharmaceutical, and endogenous metabolite biomarkers; 3) Identify exposome biomarker profiles of autism development, and 4) Integrate exposure and biological response pathways to uncover mechanisms underlying autism across different windows of susceptibility. Our results will identify critical exposome biomarkers for autism and determine how exposure and biological response contribute to neurodevelopment and symptom heterogeneity. We will develop a transformative Autism Exposome Atlas providing a centralized and organized resource for evaluating familial and cross-sectional exposome signatures and corresponding functional relationships with underlying biological response signatures. Assembly of the Autism Exposome Atlas will accelerate identification of key environmental predictors of autism and provide the evidence needed to prioritize public health interventions to support child neurodevelopment and improve health and well-being among autistic people.