Autism spectrum disorder (ASD) is a neurodevelopmental disorder with unknown etiology in 90% of cases. Over the past decade, the prevalence of ASD has increased at an alarming rate in the U.S. while in the UK the prevalence has been relatively stable in the past decade after a five-fold increase in the 1990s. Younger age at diagnosis only accounts for 12% of increases in prevalence and inclusive diagnosis alone - a 56% increase - cannot explain the increasing rate in the past decade. Moreover, recent twin studies on heritability have acknowledged that shared environmental factors may explain a larger proportion of the variance in liability (41-52%) relative to heritability (38%-49%. Therefore, the variance explained by genetic factors may be equal, or less than, that by environmental risk factors. We have characterized blood gene expression changes in ASD, and discovered biomarkers of ASD and genomically homogeneous subgroups. Unlike microarrays and genome sequencing, a unified technological platform to measure personal exposures has not been established due to the inherent variability in individual exposure history. We have developed a novel gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-high resolution mass spectrometry (LC-HRMS) and metabolic profiling approach to measure exogenous and endogenous low molecular weight analytes in human serum to maximize chemical space coverage. To analyze exposome-wide associations in ASD, we developed an Environment-Wide Association Study (EWAS) framework to conduct a data-driven search for exposures in the patients with ASD associate multiple environmental exposures (e.g., N = 250 to 1000) iteratively with disease status. We will leverage a unique and pre-existing cohort consisting of consenting children recruited at Boston Children's Hospital to conduct EWAS (Aim 1), examine the relationship between exposures between mother and inherited by their children (Aim 2) and investigate interactions between the exposome and genome (Aim 3). The outcome of the proposed study will address three critical questions of environmental risk factors contributing ASD and exposome-based research. First, we shall address what can be measured. A catalog of candidate environmental chemicals that can be stably measured in maternal and proband's blood will be created and disseminated to the scientific community. Second, we will discover what environmental risk factors are associated with ASD. Finally, our findings will provide preliminary data to support follow-up studies much needed in this area of research after completion of the proposed project: 1) to execute a longitudinal birth cohort studies to examine the risk explained by environmental risk factors found in EWAS in this proposal, and 2) to investigate how EWAS-identified factors modify genetic predisposition for ASD.

Public Health Relevance

Over the past decade, the prevalence of autism has increased at an alarming rate in the U.S. Younger age at diagnosis only accounts for 12% of increases in prevalence and inclusive diagnosis alone - a 56% increase - cannot explain the increasing rate in the past decade. This project investigates what contributed a significant increase in the autism prevalence of the U.S. and focuses on internal and external environmental exposures that are detectable in the blood from the patients with autism and their mothers, and the genetic susceptibility to environmental risk factors in autism.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Dutka, Tara
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Boston Children's Hospital
United States
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Chandler, Joshua D; Horati, Hamed; Walker, Douglas I et al. (2018) Determination of thiocyanate in exhaled breath condensate. Free Radic Biol Med 126:334-340
Lee, Samuel C; Quinn, Thomas P; Lai, Jerry et al. (2018) Solving for X: Evidence for sex-specific autism biomarkers across multiple transcriptomic studies. Am J Med Genet B Neuropsychiatr Genet :
Kong, Sek Won; Lee, In-Hee; Liu, Xuanshi et al. (2018) Measuring coverage and accuracy of whole-exome sequencing in clinical context. Genet Med :
Hajjar, Ihab; Hayek, Salim S; Goldstein, Felicia C et al. (2018) Oxidative stress predicts cognitive decline with aging in healthy adults: an observational study. J Neuroinflammation 15:17
Tylee, Daniel S; Hess, Jonathan L; Quinn, Thomas P et al. (2017) Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined-samples mega-analysis. Am J Med Genet B Neuropsychiatr Genet 174:181-201
Feiglin, Ariel; Allen, Bryce K; Kohane, Isaac S et al. (2017) Comprehensive Analysis of Tissue-wide Gene Expression and Phenotype Data Reveals Tissues Affected in Rare Genetic Disorders. Cell Syst 5:140-148.e2
Somekh, Judith; Peleg, Mor; Eran, Alal et al. (2016) A model-driven methodology for exploring complex disease comorbidities applied to autism spectrum disorder and inflammatory bowel disease. J Biomed Inform 63:366-378
Brown, Adam S; Kong, Sek Won; Kohane, Isaac S et al. (2016) ksRepo: a generalized platform for computational drug repositioning. BMC Bioinformatics 17:78
Green, Robert C; Goddard, Katrina A B; Jarvik, Gail P et al. (2016) Clinical Sequencing Exploratory Research Consortium: Accelerating Evidence-Based Practice of Genomic Medicine. Am J Hum Genet 98:1051-1066
Castro, V M; Kong, S W; Clements, C C et al. (2016) Absence of evidence for increase in risk for autism or attention-deficit hyperactivity disorder following antidepressant exposure during pregnancy: a replication study. Transl Psychiatry 6:e708

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