scholarly journals Placental DNA methylation levels at CYP2E1 and IRS2 are associated with child outcome in a prospective autism study

2018 ◽  
Author(s):  
Yihui Zhu ◽  
Charles E. Mordaunt ◽  
Dag H. Yasui ◽  
Ria Marathe ◽  
Rochelle L. Coulson ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Dna Methylation ◽  
Neuronal Development ◽  
Autism Spectrum ◽  
Child Outcome ◽  
Genome Wide ◽  
Genetic And Environmental Factors ◽  
A Prospective Study ◽  
Methylation Patterns ◽  
Genome Wide Significance

AbstractDNA methylation acts at the interface of genetic and environmental factors relevant for autism spectrum disorder (ASD). Placenta, normally discarded at birth, is a potentially rich source of DNA methylation patterns predictive of ASD in the child. Here, we performed whole methylome analyses of placentas from a prospective study of high-risk pregnancies. 400 differentially methylated regions (DMRs) discriminated placentas stored from children later diagnosed with ASD compared to typical controls. These ASD DMRs were significantly enriched at promoters, mapped to 596 genes functionally enriched in neuronal development, and overlapped genetic ASD risk. ASD DMRs at CYP2E1 and IRS2 reached genome-wide significance, replicated by pyrosequencing, and correlated with expression. Methylation at CYP2E1 associated with both ASD diagnosis and cis genotype, while methylation at IRS2 was unaffected by cis genotype but modified by preconceptional maternal prenatal vitamin use. This study therefore identified two potentially useful early epigenetic markers for ASD in placenta.

scholarly journals Placental DNA methylation levels at CYP2E1 and IRS2 are associated with child outcome in a prospective autism study

2019 ◽  
Vol 28 (16) ◽  
pp. 2659-2674 ◽  
Author(s):  
Yihui Zhu ◽  
Charles E Mordaunt ◽  
Dag H Yasui ◽  
Ria Marathe ◽  
Rochelle L Coulson ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Neuronal Development ◽  
Autism Spectrum ◽  
Typically Developing ◽  
Child Outcome ◽  
Genome Wide ◽  
Genetic And Environmental Factors ◽  
A Prospective Study ◽  
Methylation Patterns ◽  
Genome Wide Significance

Abstract DNA methylation acts at the interface of genetic and environmental factors relevant for autism spectrum disorder (ASD). Placenta, normally discarded at birth, is a potentially rich source of DNA methylation patterns predictive of ASD in the child. Here, we performed whole methylome analyses of placentas from a prospective study MARBLES (Markers of Autism Risk in Babies—Learning Early Signs) of high-risk pregnancies. A total of 400 differentially methylated regions (DMRs) discriminated placentas stored from children later diagnosed with ASD compared to typically developing controls. These ASD DMRs were significantly enriched at promoters, mapped to 596 genes functionally enriched in neuronal development, and overlapped genetic ASD risk. ASD DMRs at CYP2E1 and IRS2 reached genome-wide significance, replicated by pyrosequencing and correlated with expression differences in brain. Methylation at CYP2E1 associated with both ASD diagnosis and genotype within the DMR. In contrast, methylation at IRS2 was unaffected by within DMR genotype but modified by preconceptional maternal prenatal vitamin use. This study therefore identified two potentially useful early epigenetic markers for ASD in placenta.

scholarly journals MOSAIC EPIGENETIC DYSREGULATION OF ECTODERMAL CELLS IN AUTISM SPECTRUM DISORDER

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.

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

2018 ◽  
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.

scholarly journals DNA Methylation and Susceptibility to Autism Spectrum Disorder

2019 ◽  
Vol 70 (1) ◽  
pp. 151-166 ◽  
Author(s):  
Martine W. Tremblay ◽  
Yong-hui Jiang
Keyword(s):  
Autism Spectrum Disorder ◽  
Dna Methylation ◽  
Causative Factor ◽  
Autism Spectrum ◽  
Postnatal Period ◽  
Spectrum Disorder ◽  
Regulation Of Transcription ◽  
Peak Time ◽  
Genome Wide ◽  
Technical Advances

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.

scholarly journals Genome-wide molecular effects of the neuropsychiatric 16p11 CNVs in an iPSC-to-iN neuronal model

2020 ◽  
Author(s):  
Thomas R. Ward ◽  
Xianglong Zhang ◽  
Louis C. Leung ◽  
Bo Zhou ◽  
Kristin Muench ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cell Model ◽  
Copy Number Variants ◽  
Induced Pluripotent Stem Cell ◽  
Neuronal Model ◽  
Autism Spectrum ◽  
Genome Wide ◽  
Induced Pluripotent ◽  
Methylation Patterns

AbstractCopy number variants (CNVs), either deletions or duplications, at the 16p11.2 locus in the human genome are known to increase the risk for autism spectrum disorders (ASD), schizophrenia, and for several other developmental conditions. Here, we investigate the global effects on gene expression and DNA methylation using a 16p11.2 CNV patient-derived induced pluripotent stem cell (iPSC) to induced neuron (iN) cell model system. This approach revealed genome-wide and cell-type specific alterations to both gene expression and DNA methylation patterns and also yielded specific leads on genes potentially contributing to some of the known 16p11.2 patient phenotypes. PCSK9 is identified as a possible contributing factor to the symptoms seen in carriers of the 16p11.2 CNVs. The protocadherin (PCDH) gene family is found to have altered DNA methylation patterns in the CNV patient samples. The iPSC lines used for this study are available through a repository as a resource for research into the molecular etiology of the clinical phenotypes of 16p11.2 CNVs and into that of neuropsychiatric and neurodevelopmental disorders in general.

scholarly journals Analysis of Global and Local DNA Methylation Patterns in Blood Samples of Patients With Autism Spectrum Disorder

2021 ◽  
Vol 9 ◽  
Author(s):  
María Victoria García-Ortiz ◽  
María José de la Torre-Aguilar ◽  
Teresa Morales-Ruiz ◽  
Antonio Gómez-Fernández ◽  
Katherine Flores-Rojas ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Dna Methylation ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Control Group ◽  
Healthy Children ◽  
Blood Samples ◽  
Epigenetic Biomarkers ◽  
Increased Risk ◽  
Methylation Patterns

The goal of this investigation was to determine whether there are alterations in DNA methylation patterns in children with autism spectrum disorder (ASD).Material and Methods: Controlled prospective observational case-control study. Within the ASD group, children were sub-classified based on the presence (AMR subgroup) or absence (ANMR subgroup) of neurodevelopmental regression during the first 2 years of life. We analyzed the global levels of DNA methylation, reflected in LINE-1, and the local DNA methylation pattern in two candidate genes, Neural Cell Adhesion Molecule (NCAM1) and Nerve Growth Factor (NGF) that, according to our previous studies, might be associated to an increased risk for ASD. For this purpose, we utilized blood samples from pediatric patients with ASD (n = 53) and their corresponding controls (n = 45).Results: We observed a slight decrease in methylation levels of LINE-1 in the ASD group, compared to the control group. One of the CpG in LINE-1 (GenBank accession no.X58075, nucleotide position 329) was the main responsible for such reduction, highly significant in the ASD subgroup of children with AMR (p < 0.05). Furthermore, we detected higher NCAM1 methylation levels in ASD children, compared to healthy children (p < 0.001). The data, moreover, showed higher NGF methylation levels in the AMR subgroup, compared to the control group and the ANMR subgroup. These results are consistent with our prior study, in which lower plasma levels of NCAM1 and higher levels of NGF were found in the ANMR subgroup, compared to the subgroup that comprised neurotypically developing children.Conclusions: We have provided new clues about the epigenetic changes that occur in ASD, and suggest two potential epigenetic biomarkers that would facilitate the diagnosis of the disorder. We similarly present with evidence of a clear differentiation in DNA methylation between the ASD subgroups, with or without mental regression.

scholarly journals A novel automated autism spectrum disorder detection system

2021 ◽  
Author(s):  
Shu Lih Oh ◽  
V. Jahmunah ◽  
N. Arunkumar ◽  
Enas W. Abdulhay ◽  
Raj Gururajan ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Developmental Disorder ◽  
Detection System ◽  
Brain Activity ◽  
Limited Range ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Nonlinear Features ◽  
Genetic And Environmental Factors ◽  
Future Work

AbstractAutism spectrum disorder (ASD) is a neurological and developmental disorder that begins early in childhood and lasts throughout a person’s life. Autism is influenced by both genetic and environmental factors. Lack of social interaction, communication problems, and a limited range of behaviors and interests are possible characteristics of autism in children, alongside other symptoms. Electroencephalograms provide useful information about changes in brain activity and hence are efficaciously used for diagnosis of neurological disease. Eighteen nonlinear features were extracted from EEG signals of 40 children with a diagnosis of autism spectrum disorder and 37 children with no diagnosis of neuro developmental disorder children. Feature selection was performed using Student’s t test, and Marginal Fisher Analysis was employed for data reduction. The features were ranked according to Student’s t test. The three most significant features were used to develop the autism index, while the ranked feature set was input to SVM polynomials 1, 2, and 3 for classification. The SVM polynomial 2 yielded the highest classification accuracy of 98.70% with 20 features. The developed classification system is likely to aid healthcare professionals as a diagnostic tool to detect autism. With more data, in our future work, we intend to employ deep learning models and to explore a cloud-based detection system for the detection of autism. Our study is novel, as we have analyzed all nonlinear features, and we are one of the first groups to have uniquely developed an autism (ASD) index using the extracted features.

scholarly journals Multi-species and multi-tissue methylation clocks for age estimation in toothed whales and dolphins

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Todd R. Robeck ◽  
Zhe Fei ◽  
Ake T. Lu ◽  
Amin Haghani ◽  
Eve Jourdain ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Age Estimation ◽  
Species Conservation ◽  
Genome Wide ◽  
Epigenetic Aging ◽  
Highly Correlated ◽  
Methylation Patterns ◽  
Cg Dinucleotides ◽  
Free Ranging ◽  
Unique Species

AbstractThe development of a precise blood or skin tissue DNA Epigenetic Aging Clock for Odontocete (OEAC) would solve current age estimation inaccuracies for wild odontocetes. Therefore, we determined genome-wide DNA methylation profiles using a custom array (HorvathMammalMethyl40) across skin and blood samples (n = 446) from known age animals representing nine odontocete species within 4 phylogenetic families to identify age associated CG dinucleotides (CpGs). The top CpGs were used to create a cross-validated OEAC clock which was highly correlated for individuals (r = 0.94) and for unique species (median r = 0.93). Finally, we applied the OEAC for estimating the age and sex of 22 wild Norwegian killer whales. DNA methylation patterns of age associated CpGs are highly conserved across odontocetes. These similarities allowed us to develop an odontocete epigenetic aging clock (OEAC) which can be used for species conservation efforts by provide a mechanism for estimating the age of free ranging odontocetes from either blood or skin samples.

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