Genome-Wide DNA Methylation Analysis Reveals Epigenetic Pattern of SH2B1 in Chinese Monozygotic Twins Discordant for Autism Spectrum Disorder

The prevalence of autism spectrum disorder (ASD) has been increasing steadily over the last 20 years; however, the molecular basis for the majority of ASD cases remains unknown. Recent advances in next-generation sequencing and detection of DNA modifications have made methylation-dependent regulation of transcription an attractive hypothesis for being a causative factor in ASD etiology. Evidence for abnormal DNA methylation in ASD can be seen on multiple levels, from genetic mutations in epigenetic machinery to loci-specific and genome-wide changes in DNA methylation. Epimutations in DNA methylation can be acquired throughout life, as global DNA methylation reprogramming is dynamic during embryonic development and the early postnatal period that corresponds to the peak time of synaptogenesis. However, technical advances and causative evidence still need to be established before abnormal DNA methylation and ASD can be confidently associated.

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Epigenetic outlier profiles in depression: A genome-wide DNA methylation analysis of monozygotic twins

PLoS ONE ◽

10.1371/journal.pone.0207754 ◽

2018 ◽

Vol 13 (11) ◽

pp. e0207754 ◽

Cited By ~ 5

Author(s):

Aldo Córdova-Palomera ◽

Helena Palma-Gudiel ◽

Jaume Forés-Martos ◽

Rafael Tabarés-Seisdedos ◽

Lourdes Fañanás

Keyword(s):

Dna Methylation ◽

Monozygotic Twins ◽

Methylation Analysis ◽

Genome Wide ◽

A Genome ◽

Dna Methylation Analysis

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MOSAIC EPIGENETIC DYSREGULATION OF ECTODERMAL CELLS IN AUTISM SPECTRUM DISORDER

10.1101/004853 ◽

2014 ◽

Author(s):

Esther R. Berko ◽

Masako Suzuki ◽

Faygel Beren ◽

Christophe Lemetre ◽

Christine M. Alaimo ◽

...

Keyword(s):

Autism Spectrum Disorder ◽

Dna Methylation ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Dna Mutations ◽

Genome Wide ◽

Methylation Assay ◽

Increased Risk ◽

Methylation Patterns ◽

Encoding Protein

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 an 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.

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Genome-wide DNA methylation patterns in Autism Spectrum Disorder and mitochondrial function

10.1101/310748 ◽

2018 ◽

Cited By ~ 1

Author(s):

Sofia Stathopoulos ◽

Renaud Gaujoux ◽

Colleen O’Ryan

Keyword(s):

Autism Spectrum Disorder ◽

Dna Methylation ◽

Brain Tissue ◽

Mitochondrial Function ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Protein Ubiquitination ◽

Genome Wide ◽

Differentially Methylated Genes ◽

Methylation Patterns

AbstractAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterised by phenotypic heterogeneity and overlapping co-morbidities. The genetic architecture of ASD is complex, with 100’s of risk genes cumulatively contributing to the aetiology of ASD. Epigenetic mechanisms, particularly DNA methylation, have been associated with ASD. The vast majority of ASD molecular research has focused on Northern European populations, with a paucity of data from Africa. This study examines genome-wide DNA methylation patterns in a novel cohort of South African children with ASD and matched, unrelated controls. We performed a whole-genome DNA methylation screen using the Illumina 450K Human Methylation Array. We identify differentially methylated loci associated with ASD across 898 genes (p-value ≤ 0.05). Using a pathway analysis framework, we find nine enriched canonical pathways implicating 32 of the significant genes in our ASD cohort. These pathways converge on two crucial biological processes: mitochondrial metabolism and protein ubiquitination, both hallmarks of mitochondrial function. The involvement of mitochondrial function in ASD aetiology is in line with the recently reported transcriptomic dysregulation associated with the disorder. The differentially methylated genes in our cohort overlap with the gene co-expression modules identified in brain tissue from five major neurological disorders, including ASD. We find significant enrichment of three gene modules, two of which are classified as Mitochondrial and were significantly downregulated in ASD brains. Furthermore, we find significant overlap between differentially methylated and differentially expressed genes from our dataset with a RNA seq dataset from ASD brain tissue. This overlap is particularly significant across the Occipital brain region (padj= 0.0002) which has known association to ASD. Our differential methylation data recapitulate the expression differences of genes and co-expression module functions observed in ASD brain tissue which is consistent with a central role for DNA-methylation leading to mitochondrial dysfunction in the aetiology of ASD.

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