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Environment, the Perinatal Epigenome, and Risk for Autism and Related Disorders

Thursday, 2 May 2013: 09:00-13:00
Banquet Hall (Kursaal Centre)
J. I. Feinberg1, M. A. Taub2, S. C. Brown3, R. Irizarry4, K. D. Hansen5, L. A. A. Croen6, I. Hertz-Picciotto7, C. J. Newschaffer8, A. P. Feinberg9 and M. D. Fallin10, (1)Medicine, Johns Hopkins University, Baltimore, MD, (2)Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, (3)Epidemiology, Bloomberg School of Public Health, Baltimore, MD, (4)Johns Hopkins University, Baltimore, MD, (5)Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, (6)Kaiser Permanente Division of Research, Oakland, CA, (7)University of California at Davis, Davis, CA, (8)Drexel University School of Public Health, Philadelphia, PA, (9)Center for Epigenetics, Johns Hopkins University, Baltimore, MD, (10)Johns Hopkins School of Public Health, Baltimore, MD
Background: The study of epigenetic variation is an essential complement to conventional genetic disease studies; unlike sequence variation, epigenetic marks are affected by the environment. We report here on preliminary results of a large Epigenome Roadmap project (Fallin, Feinberg PIs) which takes a comprehensive genome-wide approach to understand the interplay between genetics, epigenetics, and in utero environment in birth and early development phenotypes that are important predictors of adverse outcomes generally, and are related to ASD specifically.

Objectives:  As a continuation of our pilot study looking at the role of Epigenetics in ASD, we have measured DNAm across the genome in multiple sample types and time points during and after pregnancy from samples contributed by families enrolled in the EARLI study.  Our goal is to assess changes in DNAm in mothers over the pregnancy interval, in addition to fathers and children, and correlations between DNAm and parental or child characteristics that may be related to ASD risk.

Methods: Using prospectively collected biosamples and environmental data, we performed genome-wide DNAm analyses on blood, semen, and placenta samples using both the Illumina 450k platform and CHARM 2.1, another array-based genome-wide approach containing over 4 million probes.  In the CHARMed group we analyzed 266 blood samples contributed by 90 pregnant women during all 3 trimesters of pregnancy and 6 months post-delivery.  These samples were analyzed against control samples (run on CHARM 2.0) from non-pregnant women matched for age and race.  A total of 840 samples contributed by EARLI mothers, fathers and children from an additional 170 families were analyzed on the Illumina platform (and  53 samples from the CHARMed group were also run on the Illumina arrays).  We first searched for regions of the genome where DNAm changes over time in mothers, and then looked for regions that are differentially methylated (DMRs) between individuals with and without particular exposures and/or potential ASD risk factors. 

Results: We do not see large changes in DNAm in blood within mothers during pregnancy itself; however, we do observe multiple intra-individual changes in DNAm in blood between the pregnancy and post-partum intervals, with the methylation pattern in post-partum samples showing a striking resemblance to the methylation of the matched non-pregnant control group.  Additional cross-sectional analyses of pregnancy-interval blood samples revealed DMRs associated with maternal alcohol use during pregnancy.  Results of comparisons with a larger array of factors will also be presented.

Conclusions: Our work has allowed us to develop the laboratory pipeline to analyze DNAm in epidemiologic samples across multiple platforms.  It appears that DNAm marks in blood are stable throughout pregnancy, which has implications for interpretation of results relating DNAm with potential ASD risk factors and outcomes. We have developed a strategy for identifying differentially methylated regions related to risk factors and outcomes.  This strategy is being applied across a spectrum of variables with the goal of identifying epigenetic marks in families affected with ASDs that may relate to environmental risk factors and thus elucidate mechanisms by which these risk factors influence ASD risk.

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