Assessment of Sources of Methylation Variation and Their Relationship to Autism Spectrum

Saturday, May 17, 2014
Atrium Ballroom (Marriott Marquis Atlanta)
M. D. Fallin1, S. V. Andrews2, B. K. Lee3, C. J. Newschaffer3, G. C. Windham4, L. A. Schieve5, L. A. Croen6, A. P. Feinberg7 and C. Ladd-Acosta2, (1)Johns Hopkins School of Public Health, Baltimore, MD, (2)Johns Hopkins University, Baltimore, MD, (3)Drexel University School of Public Health, Philadelphia, PA, (4)California Dept of Public Health, Richmond, CA, (5)National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, GA, (6)Division of Research, Kaiser Permanente Northern California, Oakland, CA, (7)Medicine, Johns Hopkins University, Baltimore, MD
Background:  Understanding DNA methylation variance in the context of autism spectrum disorders (ASD) may improve our understanding of the underlying molecular architecture involved in the etiology of ASD. The Study to Explore Early Development (SEED) is a multisite population-based case-control study of children aged 2-5 years with ASD and two control groups, one drawn from the general population and one with non-ASD developmental problems. We chose to examine DNA methylation among children in SEED because it is one of the only epidemiologic studies of ASD with comprehensive phenotypic evaluation, broad prenatal environmental exposure information, genome-wide genotyping data, and whole blood available for epigenomic measurements, all from the same individuals.

Objectives:  The goal of this study is to define sites of variable DNA methylation in our SEED methylation dataset, identify biological sources of methylation variation, and determine their relationship to ASD.

Methods:  Among 611 children enrolled in SEED, we generated unified genome-wide genotype data using the Illumina HumanOmni1-Quad BeadChip and genome-scale DNA methylation data using the 450K. Rigorous quality control measures were applied to the genotyping and methylation datasets resulting in a total of 593 children with more than 800,000 measured genotypes and over 485,000 methylation measurements. We identified genomic loci exhibiting variable methylation across the 593 SEED individuals. We then determined the relationship between the variably methylated sites and particular features of the genome sequence, and their association with ASD.

Results:  Among the 450K probes exhibiting variable methylation between subjects, we identified 83,265 probes with a particular variation in methylation signal, defined herein as “gap probes”, which cluster into 2 or 3 distinct groups separated by a “gap” in methylation values. We are in the process of characterizing the source of this gap probe behavior and determining whether the gap behavior is phenotypically driven, i.e. result from case or exposure status, and how genetic sequence contributes to this. We have already determined that a large fraction of these gap probes (25,427 or 30.1%) are at least in part attributed to the presence of a single nucleotide polymorphism (SNP) at the interrogated CpG site, at the single-base extension, or in the probe itself. It is possible that these methylation-associated SNPs and/or their associated haplotypes differ between ASD cases and controls. Therefore, we have begun to discern the role of SNPs (through identification of methylation quantitative trait loci, or meQTLs) and copy number variants in the genetic contribution to the gap probe methylation pattern. Because we have genome-wide genotype and genome-scale methylation data from the same SEED children, we can directly evaluate our SNP-methylation findings in relation to ASD status. The relationships we identify will be presented at the meeting.

Conclusions:  We have identified thousands of variably methylated positions that appear to be related to underlying features of the genomic sequence. Relating these to ASD status may provide valuable new insights into the etiology of disease.

See more of: Genetics
See more of: Genetics