Project description:The aim of this study was to identify ASD vulnerability components, explore possible vulnerability subgroups, and evaluate environmental contribution to phenotypic variability. We performed PCA and cluster analysis using ASD risk factor data. We found that PC1 had a higher correlation with psychosocial stress (maternal stress, maternal education, and social class), and PC2 a higher correlation with biological factors (Psychiatric Family History and Gestational Complications). Clustering analysis of PCA scores using bootstrap approach showed two clusters. Comparing the methylome between clusters we found 11.879 DMPs (p<0.05), and their CpG sites were enriched in VMRs, most showing environmental and genetic influences. Hypermethylated probes presented higher rates in different regulatory regions associated with functional SNPs, indicating that the subgroups may have different affected regulatory regions and their liability to disease explained by common variations. Vulnerability score moderated by epigenetic clock was associated with Vineland Total score (p=0.0036, adjR2=0.31), suggesting risk factors with stress burden can influence phenotype.

2021-10-01 | GSE164563 | GEO

RNA-seq of 36 individuals with autism spectrum disorder

Project description:To assess the clinical impact of splice-altering noncoding mutations in autism spectrum disorder (ASD), we used a deep learning framework (SpliceAI) to predict the splice-altering potential of de novo mutations in 3,953 individuals with ASD from the Simons Simplex Collection. To validate these predictions, we selected 36 individuals that harbored predicted de-novo cryptic splice mutations; each individual represented the only case of autism within their immediate family. We obtained peripheral blood-derived lymphoblastoid cell lines (LCLs) and performed high-depth mRNA sequencing (approximately 350 million 150 bp single-end reads per sample). We used OLego to align the reads against a reference created from hg19 by substituting de novo variants of each individual with the corresponding alternate allele.

2018-11-25 | E-MTAB-7351 | biostudies-arrayexpress

Structural Variation of Chromosomes in Autism Spectrum Disorder.

Project description:Chromosomal abnormalities have been identified in some individuals with Autism Spectrum Disorder (ASD), but their full etiologic role is unknown. Submicroscopic copy number variation (CNV) represents a considerable source of genetic variation in the human genome that contributes to phenotypic differences and disease susceptibility. To explore the contribution CNV imbalances in ASD, we genotyped unrelated ASD index cases using the Affymetrix GeneChip® 500K single nucleotide polymorphism (SNP) mapping array. Keywords: Whole Genome Mapping SNP Genotyping Array

2007-12-20 | GSE9222 | GEO

MicroRNA biomarkers in blood for Autism spectrum disorder

Project description:Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social communication deficits and repetitive behaviors. MicroRNAs (miRNAs) have been recently recognized as potential biomarkers of ASD as they are dysregulated in various tissues of individuals with ASD. However, it remains unclear whether miRNA expression is altered in individuals with high-functioning ASD. Here, we investigated the miRNA expression profile in peripheral blood from adults with high-functioning ASD, and age and gender-matched healthy controls. Our findings may provide insights regarding the molecular clues for recognizing high-functioning ASD.

2020-05-03 | GSE89596 | GEO

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