Identification of Gene-Environment Interactions Associated with Autism Spectrum Disorders
Objectives: The main purpose of this study is to identify genetic and environmental factors that influence risk for ASD. Specifically, we sought to identify single nucleotide polymorphisms (SNPs) whose effects on ASD risk vary across levels of selected prenatal environmental exposures including SSRI use, B2AR use, smoking, alcohol use, and infection.
Methods: For our GxE analysis, we examined prenatal exposures across four domains including maternal use of tobacco, alcohol, and medication (B2ARs and SSRIs) as well as maternal infection. Prenatal environmental exposure information was obtained from maternal self-reported data using a structured interview. Genotypes for 1,321 SEED children (590 cases and 731 controls) were measured using Illumina Omni1 and Affymetrix Axiom arrays. After applying data quality control measures, and performing imputation to obtain about 4 million genotypes per person, initial analysis was performed using a new joint likelihood ratio test for marginal genetic main effects and gene-environment interaction. To maximize our power and appropriately account for gene and environment independence assumptions we also plan to implement a case-only GxE likelihood ratio test of association that uses an Empirical Bayes-type shrinkage estimator to address gene-environment independence.
Results: Our GxE analysis using data from 873 SEED children revealed a genome-wide significant (P < 5x10-7) interaction between genotype and smoking for several neighboring SNPs on chromosome 2. We are in the process of completing final GxE analyses for the complete set of 1,321 SEED samples and will present our latest findings, in the largest set of samples, at the conference.
Conclusions: We have identified interactions between genomic regions and specific in utero environmental exposures that are associated with ASD. Our results suggest that coupling genetic and environmental exposure information to determine ASD risk may be more fruitful than looking for genetic marginal effects alone. SEED has proven to be a particularly useful resource for these types of integrative of studies.