scholarly journals Peripheral blood DNA methylation and autism spectrum disorder

2018 ◽  
Author(s):  
Shan V. Andrews ◽  
Brooke Sheppard ◽  
Gayle C. Windham ◽  
Laura A. Schieve ◽  
Diana E. Schendel ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Dna Methylation ◽  
Sample Size ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Case Control ◽  
Small Sample ◽  
Spectrum Disorder ◽  
Blood Samples ◽  
Cpg Sites

AbstractBackgroundSeveral reports have suggested a role for epigenetic mechanisms in ASD etiology. Epigenome-wide association studies (EWAS) in autism spectrum disorder (ASD) may shed light on particular biological mechanisms. However, studies of ASD cases versus controls have been limited by post-mortem timing and severely small sample sizes. Reports from in-life sampling of blood or saliva have also been very limited in sample size, and/or genomic coverage. We present the largest case-control EWAS for ASD to date, combining data from population-based case-control and case-sibling pair studies.MethodsDNA from 968 blood samples from children in the Study to Explore Early Development (SEED 1) was used to generate epigenome-wide array DNA methylation (DNAm) data at 485,512 CpG sites for 453 cases and 515 controls, using the Illumina 450K Beadchip. The Simons Simplex Collection (SSC) provided 450K array DNAm data on an additional 343 cases and their unaffected siblings. We performed EWAS meta-analysis across results from the two data sets, with adjustment for sex and surrogate variables that reflect major sources of biological variation and technical confounding such as cell type, batch, and ancestry. We compared top EWAS results to those from a previous brain-based analysis. We also tested for enrichment of ASD EWAS CpGs for being targets of meQTL associations using available SNP genotype data in the SEED sample.FindingsIn this meta-analysis of blood-based DNA from 796 cases and 858 controls, no single CpG met a Bonferroni discovery threshold of p < 1.12×10−7. Seven CpGs showed differences at p < 1×10−5 and 48 at 1×10−4. Of the top 7, 5 showed brain-based ASD associations as well, often with larger effect sizes, and the top 48 overall showed modest concordance (r = 0.31) in direction of effect with cerebellum samples. Finally, we observed suggestive evidence for enrichment of CpG sites controlled by SNPs (meQTL targets) among the EWAS CpGs hits, which was consistent across EWAS and meQTL discovery p-value thresholds.ConclusionsWe report the largest case-control EWAS study of ASD to date. No single CpG site showed a large enough DNAm difference between cases and controls to achieve epigenome-wide significance in this sample size. However, our results suggest the potential to observe disease associations from blood-based samples. Among the 7 sites achieving suggestive statistical significance, we observed consistent, and stronger, effects at the same sites among brain samples. Discovery-oriented EWAS for ASD using blood samples will likely need even larger samples and unified genetic data to further understand DNAm differences in ASD.

scholarly journals Case-control meta-analysis of blood DNA methylation and autism spectrum disorder

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Shan V. Andrews ◽  
Brooke Sheppard ◽  
Gayle C. Windham ◽  
Laura A. Schieve ◽  
Diana E. Schendel ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Dna Methylation ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Case Control ◽  
Spectrum Disorder

scholarly journals LINE-1 and Alu methylation Signatures in Autism Spectrum Disorder and Their Function in The Regulation of Autism-Related Genes

2021 ◽  
Author(s):  
Thanit Saeliw ◽  
Tiravut Permpoon ◽  
Nutta Iadsee ◽  
Tewin Tencomnao ◽  
Tewarit Sarachana ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Dna Methylation ◽  
Autism Spectrum ◽  
Small Sample ◽  
Spectrum Disorder ◽  
Post Mortem ◽  
Global Methylation ◽  
Post Mortem Brain ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

Abstract BackgroundLong interspersed nucleotide element-1 (LINE-1) and Alu elements are retrotransposons whose abilities cause abnormal gene expression and genomic instability. Several studies have focused on DNA methylation profiling of gene regions, but the locus-specific methylation of LINE-1 and Alu elements has not been identified in autism spectrum disorder (ASD).MethodsHere, DNA methylation age was predicted using Horvath’s method. We interrogated locus- and family-specific methylation profiles of LINE-1 and Alu elements (22,352 loci) in ASD blood using publicly-available Illumina Infinium 450K methylation datasets from heterogeneous ASD (n = 52), ASD with 16p11.2 del (n = 7), and ASD with Chromodomain Helicase DNA-binding 8 (CHD8) variants (n = 15). The differentially methylated positions of LINE-1 and Alu elements corresponding to genes were combined with transcriptome data from multiple ASD studies. ROC curve was conducted to examine the specificity of target loci.ResultsEpigenetic age acceleration was significantly decelerated in ASD children over the age of 11 years. DNA methylation profiling revealed LINE-1 and Alu methylation signatures in each ASD risk loci by which global methylation were notably hypomethylated exclusively in ASD with CHD8 variants. When LINE-1 and Alu elements were clustered into subfamilies, we found methylation changes in a family-specific manner in L1P, L1H, HAL, AluJ, and AluS families in the heterogeneous ASD and ASD with CHD8 variants. Our results showed that LINE-1 and Alu methylation within target genes is inversely related to the expression level in each ASD variant. Moreover, LINE-1 and Alu methylation signatures can be used to predict ASD individuals from non-ASD.LimitationsIntegration of methylome and transcriptome datasets was performed from different ASD cohorts. The small sample size of the validation cohort used post-mortem brain tissues and necessitates future validation in a larger cohort.ConclusionsThe DNA methylation signatures of the LINE-1 and Alu elements in ASD, as well as their functional impact on ASD-related genes, have been studied. These findings are considered for further research into DNA methylation profiles and the expression of the LINE-1 and Alu elements in post-mortem brain tissue, which has been linked to ASD pathogenesis.

scholarly journals DNA methylation of PGC-1α is associated with elevated mtDNA copy number and altered urinary metabolites in Autism Spectrum Disorder

2021 ◽  
Author(s):  
Sophia Bam ◽  
Erin Buchanan ◽  
Caitlyn Mahony ◽  
Colleen O’Ryan
Keyword(s):  
Autism Spectrum Disorder ◽  
Dna Methylation ◽  
Mitochondrial Dysfunction ◽  
Copy Number ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Peroxisome Proliferator ◽  
Mtdna Copy Number ◽  
Cpg Sites ◽  
Mtdna Deletions

AbstractBackgroundAutism Spectrum Disorder (ASD) is a complex disorder that is underpinned by numerous dysregulated biological pathways, including canonical mitochondrial pathways. Epigenetic mechanisms contribute to this dysregulation and DNA methylation is an important factor in the aetiology of ASD. We examined the relationship between DNA methylation of peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1α), an essential transcriptional regulator of mitochondrial homeostasis, and mitochondrial dysfunction in an ASD cohort of South African children.ResultsUsing targeted Next Generation bisulfite sequencing, we found 12 highly variable CpG sites in PGC-1α that were significantly differentially methylated (p<0.05) between ASD (n = 55) and controls (n = 44). In ASD, eight CpG sites were hypermethylated in the PGC-1α promotor with a putative binding site for CAMP response binding element 1 (CREB1) spanning one of these CpG sites (p = 1 × 10−6). Mitochondrial DNA (mtDNA) copy number, a marker of mitochondrial function, was elevated (p = 0.002) in ASD compared to controls and correlated significantly with DNA methylation at the PGC-1α promoter. There was a positive correlation between methylation at PGC-1α at CpG#1 and mtDNA copy number (Spearman’s r = 0.2, n = 49, p = 0.04) in ASD, but a negative correlation between methylation at PGC-1α at CpG#4 promoter and mtDNA copy number in controls (Spearman’s r = −0.4, n = 42, p = 0.045). While there was no relationship between mtDNA deletions and PGC-1α methylation in ASD, mtDNA deletions correlated negatively with methylation at PGC-1α at CpG#4 (Spearman’s r = −0.4, n = 42, p = 0.032) in controls. Furthermore, levels of urinary organic acids associated with mitochondrial dysfunction correlated significantly (p<0.05) with DNA methylation at PGC-1α CpG#1 and mtDNA copy number in ASD (n= 20) and controls (n= 13) with many of these metabolites involved in altered redox homeostasis and neuroendocrinology.ConclusionsThese data show an association between PGC-1α promoter methylation, elevated mtDNA copy number and metabolomic evidence of mitochondrial dysfunction in ASD. This highlights an unexplored link between DNA methylation and mitochondrial dysfunction in ASD.

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 &lt; 0.05). Furthermore, we detected higher NCAM1 methylation levels in ASD children, compared to healthy children (p &lt; 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 Cord blood DNA methylome in newborns later diagnosed with autism spectrum disorder reflects early dysregulation of neurodevelopmental and X-linked genes

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Charles E. Mordaunt ◽  
Julia M. Jianu ◽  
Benjamin I. Laufer ◽  
Yihui Zhu ◽  
Hyeyeon Hwang ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Dna Methylation ◽  
Cord Blood ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Chromosome Location ◽  
Blood Samples ◽  
Chromatin States ◽  
Males And Females

Abstract Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder with complex heritability and higher prevalence in males. The neonatal epigenome has the potential to reflect past interactions between genetic and environmental factors during early development and influence future health outcomes. Methods We performed whole-genome bisulfite sequencing of 152 umbilical cord blood samples from the MARBLES and EARLI high-familial risk prospective cohorts to identify an epigenomic signature of ASD at birth. Samples were split into discovery and replication sets and stratified by sex, and their DNA methylation profiles were tested for differentially methylated regions (DMRs) between ASD and typically developing control cord blood samples. DMRs were mapped to genes and assessed for enrichment in gene function, tissue expression, chromosome location, and overlap with prior ASD studies. DMR coordinates were tested for enrichment in chromatin states and transcription factor binding motifs. Results were compared between discovery and replication sets and between males and females. Results We identified DMRs stratified by sex that discriminated ASD from control cord blood samples in discovery and replication sets. At a region level, 7 DMRs in males and 31 DMRs in females replicated across two independent groups of subjects, while 537 DMR genes in males and 1762 DMR genes in females replicated by gene association. These DMR genes were significantly enriched for brain and embryonic expression, X chromosome location, and identification in prior epigenetic studies of ASD in post-mortem brain. In males and females, autosomal ASD DMRs were significantly enriched for promoter and bivalent chromatin states across most cell types, while sex differences were observed for X-linked ASD DMRs. Lastly, these DMRs identified in cord blood were significantly enriched for binding sites of methyl-sensitive transcription factors relevant to fetal brain development. Conclusions At birth, prior to the diagnosis of ASD, a distinct DNA methylation signature was detected in cord blood over regulatory regions and genes relevant to early fetal neurodevelopment. Differential cord methylation in ASD supports the developmental and sex-biased etiology of ASD and provides novel insights for early diagnosis and therapy.

scholarly journals The Association between Vitamin D Status and Autism Spectrum Disorder (ASD): A Systematic Review and Meta-Analysis

Nutrients ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 86
Author(s):  
Zuqun Wang ◽  
Rui Ding ◽  
Juan Wang
Keyword(s):  
Autism Spectrum Disorder ◽  
Vitamin D ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Case Control ◽  
Spectrum Disorder ◽  
Cochrane Library ◽  
Vitamin D Status ◽  
Case Control Studies ◽  
Lower Vitamin

The association between vitamin D status and autism spectrum disorder (ASD) is well-investigated but remains to be elucidated. We quantitatively combined relevant studies to estimate whether vitamin D status was related to ASD in this work. PubMed, EMBASE, Web of Science, and the Cochrane Library were searched to include eligible studies. A random-effects model was applied to pool overall estimates of vitamin D concentration or odds ratio (OR) for ASD. In total, 34 publications involving 20,580 participants were identified in this present study. Meta-analysis of 24 case–control studies demonstrated that children and adolescents with ASD had significantly lower vitamin D concentration than that of the control group (mean difference (MD): −7.46 ng/mL, 95% confidence interval (CI): −10.26; −4.66 ng/mL, p < 0.0001, I2 = 98%). Quantitative integration of 10 case–control studies reporting OR revealed that lower vitamin D was associated with higher risk of ASD (OR: 5.23, 95% CI: 3.13; 8.73, p < 0.0001, I2 = 78.2%). Analysis of 15 case–control studies barring data from previous meta-analysis reached a similar result with that of the meta-analysis of 24 case–control studies (MD: −6.2, 95% CI: −9.62; −2.78, p = 0.0004, I2 = 96.8%), which confirmed the association. Furthermore, meta-analysis of maternal and neonatal vitamin D showed a trend of decreased early-life vitamin D concentration in the ASD group (MD: −3.15, 95% CI: −6.57; 0.26, p = 0.07, I2 = 99%). Meta-analysis of prospective studies suggested that children with reduced maternal or neonatal vitamin D had 54% higher likelihood of developing ASD (OR: 1.54, 95% CI: 1.12; 2.10, p = 0.0071, I2 = 81.2%). These analyses indicated that vitamin D status was related to the risk of ASD. The detection and appropriate intervention of vitamin D deficiency in ASD patients and pregnant and lactating women have clinical and public significance.

Diagnostic test accuracy for use of machine learning in diagnosis of autism spectrum disorder: A Systematic Review and Meta-Analysis (Preprint)

2019 ◽  
Author(s):  
Sun Jae Moon ◽  
Jin Seub Hwang ◽  
Rajesh Kana ◽  
John Torous ◽  
Jung Won Kim
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Meta Analysis ◽  
Learning Algorithms ◽  
Structural Mri ◽  
Autism Spectrum ◽  
Machine Learning Algorithms ◽  
Spectrum Disorder ◽  
Test Accuracy

BACKGROUND Over the recent years, machine learning algorithms have been more widely and increasingly applied in biomedical fields. In particular, its application has been drawing more attention in the field of psychiatry, for instance, as diagnostic tests/tools for autism spectrum disorder. However, given its complexity and potential clinical implications, there is ongoing need for further research on its accuracy. OBJECTIVE The current study aims to summarize the evidence for the accuracy of use of machine learning algorithms in diagnosing autism spectrum disorder (ASD) through systematic review and meta-analysis. METHODS MEDLINE, Embase, CINAHL Complete (with OpenDissertations), PsyINFO and IEEE Xplore Digital Library databases were searched on November 28th, 2018. Studies, which used a machine learning algorithm partially or fully in classifying ASD from controls and provided accuracy measures, were included in our analysis. Bivariate random effects model was applied to the pooled data in meta-analysis. Subgroup analysis was used to investigate and resolve the source of heterogeneity between studies. True-positive, false-positive, false negative and true-negative values from individual studies were used to calculate the pooled sensitivity and specificity values, draw SROC curves, and obtain area under the curve (AUC) and partial AUC. RESULTS A total of 43 studies were included for the final analysis, of which meta-analysis was performed on 40 studies (53 samples with 12,128 participants). A structural MRI subgroup meta-analysis (12 samples with 1,776 participants) showed the sensitivity at 0.83 (95% CI-0.76 to 0.89), specificity at 0.84 (95% CI -0.74 to 0.91), and AUC/pAUC at 0.90/0.83. An fMRI/deep neural network (DNN) subgroup meta-analysis (five samples with 1,345 participants) showed the sensitivity at 0.69 (95% CI- 0.62 to 0.75), the specificity at 0.66 (95% CI -0.61 to 0.70), and AUC/pAUC at 0.71/0.67. CONCLUSIONS Machine learning algorithms that used structural MRI features in diagnosis of ASD were shown to have accuracy that is similar to currently used diagnostic tools.

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