Boston Birth Cohort - Autism Data Science Initiative (BBC-ADSI) - Project title: Boston Birth Cohort - Autism Data Science Initiative (BBC-ADSI). Abstract The overarching goal of this proposed project is to address two strategic tasks outlined by the NIH OTA- 25-006 - Autism Data Science Initiative (ADSI): • Task II – Targeted data generation to complement existing datasets to fill critical data gaps. • Task III – Advanced data analysis using state-of-the-art statistical methods, artificial intelligence (AI), and machine learning (ML) for both hypothesis testing and hypothesis generating. Aim 1 will leverage the Boston Birth Cohort (BBC)—a large, long-term, prospective, and deeply phenotyped U.S. birth cohort—to advance the ADSI mission. We propose to expand the BBC’s multi- omics resources by generating new data from archived biospecimens using cutting-edge, unbiased biotechnologies across the following informative groups: Children diagnosed with autism; Children with elevated autistic quantitative traits without a diagnosis; children with other developmental disabilities; and Neurotypical children. The omics data will include the genome, epigenome, metabolome, proteome, and IgG antibody reactome, all derived from blood samples collected at birth and at 1–2 years of age—critical developmental windows for gaining insight into the biological mechanisms underlying autism onset and trajectory. Aim 2 will conduct innovative analyses by integrating multi-omics data with exposome measures and detailed autism phenotypes to address a fundamental question: What causes autism? Informed by literature and our own work, we will test hypotheses focused on understudied, yet potentially high-impact environmental exposures and promising biological pathways. Our team is uniquely positioned to contribute scientific and methodological advances to the ADSI, including but not limited to: 1. Defining autism’s complex phenotypes by leveraging rich data resources—quantitative measures of core autistic traits (e.g., SCQ and SRS), clinical evaluations and diagnoses, longitudinal electronic medical records, and special educational services. 2. Delineating the individual and combined effects of early-life factors on autism. The BBC has amassed extensive early-life exposure data—many rarely studied in an integrated fashion— including maternal nutrition, dietary patterns, psychosocial stress, toxic metals, per- and polyfluoroalkyl substances (PFAS), prenatal and perinatal clinical interventions, medications, adverse birth outcomes, neighborhood characteristics, and in utero and early-life infections, inflammation, antibiotics use, and immune responses. 3. Integrating multi-omics and early life exposome to gain crucial insights into gene–environment (G×E) interactions and the biological pathways underlying autism development and progression. This proposal builds on our longstanding effort to generate a multi-dimensional, prospective birth cohort for autism research. It will be carried out by a transdisciplinary team with expertise in pediatrics, autism, environmental and genetic epidemiology, biotechnology, immunology, multi-omics, statistical genetics, computational genomics, AI, and ML. Successful execution of this project will produce an unprecedented multi-omics × exposome dataset, support novel analytic approaches, and catalyze future research, including replication studies and meta-analyses within the ADSI network. The project’s impact will be further amplified through a robust community engagement and dissemination strategy throughout the study period.
