Dataset Information

Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder.

ABSTRACT: Integration of emerging epigenetic information with autism spectrum disorder (ASD) genetic results may elucidate functional insights not possible via either type of information in isolation. Here we use the genotype and DNA methylation (DNAm) data from cord blood and peripheral blood to identify SNPs associated with DNA methylation (meQTL lists). Additionally, we use publicly available fetal brain and lung meQTL lists to assess enrichment of ASD GWAS results for tissue-specific meQTLs. ASD-associated SNPs are enriched for fetal brain (OR?=?3.55; P?

SUBMITTER: Andrews SV

PROVIDER: S-EPMC5654961 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder.

Andrews Shan V SV Ellis Shannon E SE Bakulski Kelly M KM Sheppard Brooke B Croen Lisa A LA Hertz-Picciotto Irva I Newschaffer Craig J CJ Feinberg Andrew P AP Arking Dan E DE Ladd-Acosta Christine C Fallin M Daniele MD

Nature communications 20171024 1

Integration of emerging epigenetic information with autism spectrum disorder (ASD) genetic results may elucidate functional insights not possible via either type of information in isolation. Here we use the genotype and DNA methylation (DNAm) data from cord blood and peripheral blood to identify SNPs associated with DNA methylation (meQTL lists). Additionally, we use publicly available fetal brain and lung meQTL lists to assess enrichment of ASD GWAS results for tissue-specific meQTLs. ASD-assoc ...[more]

PMID: 29066808

Similar Datasets

Project description:DNA mutational events are increasingly being identified in autism spectrum disorder (ASD), but the potential additional role of dysregulation of the epigenome in the pathogenesis of the condition remains unclear. The epigenome is of interest as a possible mediator of environmental effects during development, encoding a cellular memory reflected by altered function of progeny cells. Advanced maternal age (AMA) is associated with an increased risk of having a child with ASD for reasons that are not understood. To explore whether AMA involves covert aneuploidy or epigenetic dysregulation leading to ASD in the offspring, we tested a homogeneous ectodermal cell type from 47 individuals with ASD compared with 48 typically developing (TD) controls born to mothers of ≥35 years, using a quantitative genome-wide DNA methylation assay. We show that DNA methylation patterns are dysregulated in ectodermal cells in these individuals, having accounted for confounding effects due to subject age, sex and ancestral haplotype. We did not find mosaic aneuploidy or copy number variability to occur at differentially-methylated regions in these subjects. Of note, the loci with distinctive DNA methylation were found at genes expressed in the brain and encoding protein products significantly enriched for interactions with those produced by known ASD-causing genes, representing a perturbation by epigenomic dysregulation of the same networks compromised by DNA mutational mechanisms. The results indicate the presence of a mosaic subpopulation of epigenetically-dysregulated, ectodermally-derived cells in subjects with ASD. The epigenetic dysregulation observed in these ASD subjects born to older mothers may be associated with aging parental gametes, environmental influences during embryogenesis or could be the consequence of mutations of the chromatin regulatory genes increasingly implicated in ASD. The results indicate that epigenetic dysregulatory mechanisms may complement and interact with DNA mutations in the pathogenesis of the disorder.

Dataset Information

Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder.

Publications

Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets