Autism Spectrum Disorder (ASD) is a major public health burden in the US, with current prevalence estimates of 1 in 68 children and economic costs exceed $60 billion per year. Identification of causes that can inform prevention and policy is the most efficient way to stem the tide of this rising prevalence. Most research to date has focused on identifying genetic causes of autism, however, recent twin and population-scale studies have shown that both genes and environmental exposures contribute equally to ASD risk and etiology. Evidence suggests the critical exposure window is most likely during in utero development, and thus focus on prenatal risk factors is extremely important. Environmental epidemiology has long recognized the neurotoxic effects of exposure to heavy metals, and some air pollution studies have specifically implicated exposure to metals during pregnancy as a risk factor for ASD. However, further assessment of risk due to prenatal metals exposure has been limited by (1) lack of prospective data from pregnancy; (2) lack of direct measures of biologically effective dose; (3) lack of consideration of maternal or child genetic susceptibility; (4) lack of fully characterized ASD phenotypes. Here we propose the first prospective, longitudinal study examining the contribution of prenatal exposure to lead (Pb), cadmium (Cd), mercury (Hg), selenium (Se), and manganese (Mn) on ASD risk, while accounting for potential genetic modification of metal exposure-ASD associations, using data from 456 mother-child dyads from the two largest enriched risk, prospective, longitudinal pregnancy autism cohorts in the US: Early Autism Risk Longitudinal Investigation (EARLI) and Markers of Autism Risk in Bablies Learning the Early Signs (MARBLES).
Our aims are to: (1) estimate prospective associations between direct measures of perinatal Pb, Cd, Hg, Se, and Mn levels, and ASD outcomes, including ASD-related quantitative neurodevelopmental phenotypes; (2) Incorporate maternal and child genetic susceptibility into analyses that estimate this risk; (3) Examine the role of DNA methylation (DNAm) in any detected metals associations, either as a birth biomarker of prenatal exposure, or as a mediator of risk effects. This study is likely to impact the field of autism and contribute to the advancement of human public health because it will: a) establish the relevance of prenatal metal exposures to ASD risk; b) determine whether prenatal metal exposure susceptibility differs based on underlying maternal or child genetic structure; c) potentially inform pathways and biological mechanisms, i.e. epigenetics, involved in disease and/or prenatal exposure processes; and d) generate unified GWAS, epigenetic, and metal measurement data across the 2 largest US longitudinal pregnancy autism cohorts that can be used in future investigations of health outcomes and/or additional exposure domains.

Public Health Relevance

The overall purpose of this proposal is to establish the relevance of prenatal exposure to heavy metals, including lead, cadmium, mercury, selenium, and manganese to risk for autism. Because an individual's susceptibility to metal exposure may also partly dependent on their genes, we plan to jointly test the effects of genes and prenatal metal levels in our analyses. The proposal provides an opportunity to identify a potentially modifiable, metal exposure, risk factor for autism that could substantially benefit public health in the US.

National Institute of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
Research Project (R01)
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Special Emphasis Panel (ZRG1-DKUS-C (50)R)
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Lawler, Cindy P
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Johns Hopkins University
Other Health Professions
Schools of Public Health
United States
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Dou, John; Schmidt, Rebecca J; Benke, Kelly S et al. (2018) Cord blood buffy coat DNA methylation is comparable to whole cord blood methylation. Epigenetics 13:108-116
Patel, Chirag J; Kerr, Jacqueline; Thomas, Duncan C et al. (2017) Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies. Cancer Epidemiol Biomarkers Prev 26:1370-1380