Regulation of gene expression change in autism by microRNA [miRNA-seq]
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE59286 | GEO | 2018/10/10
REPOSITORIES: GEO
Similar Datasets
Project description:Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by delayed/abnormal language development, deficits in social interaction, repetitive behaviors and restricted interests. The heterogeneity in clinical presentation of ASD, likely due to different etiologies, complicates genetic/biological analyses of these disorders. DNA microarray analyses were conducted on 116 lymphoblastoid cell lines (LCL) from individuals with idiopathic autism who are divided into 3 phenotypic subgroups according to severity scores from the commonly used Autism Diagnostic Interview-Revised questionnaire and age-matched, nonautistic controls. Statistical analyses of gene expression data from control LCL against that of LCL from ASD probands identify genes for which expression levels are either quantitatively or qualitatively associated with phenotypic severity. Comparison of the significant differentially expressed genes from each subgroup relative to the control group reveals differentially expressed genes unique to each subgroup as well as genes in common across subgroups. Among the findings unique to the most severely affected ASD group are genes that regulate circadian rhythm, which has been shown to have multiple effects on neurological as well as metabolic functions commonly dysregulated in autism. Among the genes common to all 3 subgroups of ASD are 5 novel genes which appear to associate with androgen sensitivity, which may underlie the strong 4:1 bias towards affected males. Gene expression profiling of 116 LCL from autistic (87) and nonautistic (29) individuals were obtained using a custom-printed DNA microarray containing 39,936 elements (TIGR 40K Human array, GPL3427) and a reference design in which each sample was compared to the Stratagene Universal Human RNA standard. The 87 autistic samples were divided into phenotypic subgroups (language, mild, savant) on the basis of cluster analyses of scores from an autism diagnostic questionnaire, the Autism Diagnostic Interview-Revised instrument. Differentially expressed genes were determined for all autistic vs. control groups, as well as for each of 3 phenotypic ASD groups and controls.
2010-05-17 | E-GEOD-15402 | biostudies-arrayexpress
Project description:Autism spectrum disorder (ASD) is a common, highly heritable neuro-developmental condition characterized by marked genetic heterogeneity. Thus, a fundamental question is whether autism represents an etiologically heterogeneous disorder in which the myriad genetic or environmental risk factors perturb common underlying molecular pathways in the brain. Here, we demonstrate consistent differences in transcriptome organization between autistic and normal brain by gene co-expression network analysis. Remarkably, regional patterns of gene expression that typically distinguish frontal and temporal cortex are significantly attenuated in the ASD brain, suggesting abnormalities in cortical patterning. We further identify discrete modules of co-expressed genes associated with autism: a neuronal module enriched for known autism susceptibility genes, including the neuronal specific splicing factor A2BP1/FOX1, and a module enriched for immune genes and glial markers. Using high-throughput RNA-sequencing we demonstrate dysregulated splicing of A2BP1-dependent alternative exons in ASD brain. Moreover, using a published autism GWAS dataset, we show that the neuronal module is enriched for genetically associated variants, providing independent support for the causal involvement of these genes in autism. In contrast, the immune-glial module showed no enrichment for autism GWAS signals, indicating a non-genetic etiology for this process. Collectively, our results provide strong evidence for convergent molecular abnormalities in ASD, and implicate transcriptional and splicing dysregulation as underlying mechanisms of neuronal dysfunction in this disorder. Total RNA was extracted from approximately 100mg of postmortem brain tissue representing Cerebellum (C), Frontal cortex (F), and Temporal cortex (T), from autistic and control individuals.
2011-05-01 | E-GEOD-28521 | biostudies-arrayexpress
Project description:gene expression profiles of lymphoblastoid cells from individuals with autism and full mutation of FMR1 Keywords: autism with FMR1-FM
2007-06-01 | GSE7316 | GEO
Project description:A number of genetic studies have identified rare protein-coding DNA variations associated with autism spectrum disorder (ASD), a neurodevelopmental disorder with significant genetic etiology and heterogeneity. In contrast, the contributions of functional, regulatory genetic variations that occur in the extensive non-protein-coding regions of the genome remain poorly understood. Here we developed a genome-wide analysis to identify rare single nucleotide variants (SNVs) that occur in non-coding regions and determined regulatory function and evolutionary conservation of these variants. Using publicly available datasets and computational predictions, we identified SNVs within putative regulatory regions in promoters, transcription factor binding sites, microRNA genes and their target sites. Overall, we found regulatory variants in the ASD cases were enriched in autism-risk genes and genes involved in fetal neurodevelopment. As with previously reported coding mutations, we found an enrichment of regulatory variants associated with dysregulation of neurodevelopmental and synaptic signaling pathways. Among these were rare inherited non-coding SNVs found in the mature sequence of a number of microRNAs predicted to affect the regulation of autism-risk genes. We show a paternally inherited miR-873-5p variant, with reduced NRXN2 binding affinity, overlays a maternally inherited NRXN1 putative loss-of-function coding variation to likely increase genetic liability in an idiopathic ASD case. Our analysis pipeline provides a new resource for identifying loss-of-function regulatory DNA variations that may contribute to the genetic etiology of complex disorders.
2017-04-25 | GSE98088 | GEO
Project description:Microdeletions of the MEF2C gene are linked to a syndromic form of autism termed MEF2C haploinsufficiency syndrome (MCHS). Here, we show that MCHS-associated missense mutations cluster in the conserved DNA binding domain and disrupt MEF2C DNA binding. DNA binding-deficient global Mef2c heterozygous mice (Mef2c-Het) display numerous MCHS-like behaviors, including autism-related behaviors, as well as deficits in cortical excitatory synaptic transmission. We find that hundreds of genes are dysregulated in Mef2c-Het cortex, including significant enrichments of autism risk and excitatory neuron genes. In addition, we observe an enrichment of upregulated microglial genes, but not due to neuroinflammation in the Mef2c-Het cortex. Importantly, conditional Mef2c heterozygosity in forebrain excitatory neurons reproduces a subset of the Mef2c-Het phenotypes, while conditional Mef2c heterozygosity in microglia reproduces social deficits and repetitive behavior. Together our findings suggest that MEF2C regulates typical brain development and function through multiple cell types, including excitatory neuronal and neuroimmune populations.
2020-10-24 | GSE139419 | GEO
Project description:A causal role of mutations in genes encoding for multiple general transcription factors in neurodevelopmental disorders including autism suggested that alterations at the global level of gene expression regulation might also relate to disease risk in sporadic cases of autism. This premise can be tested by evaluating for global changes in the overall distribution of gene expression levels. For instance, in mice, we recently showed that variability in hippocampal-dependent behaviors was associated with variability in the pattern of the overall distribution of gene expression levels, as assessed by variance in the distribution of gene expression levels in the hippocampus. We hypothesized that a similar change in the variance in gene expression levels might be found in children with autism. Gene expression microarrays covering greater than 47,000 unique RNA transcripts were done on purified RNA from peripheral blood lymphocytes of children with autism (n=82) and controls (n=64). The variance in the distribution of gene expression levels from each microarray was compared between groups of children. Also tested was whether a risk factor for autism, increased paternal age, was associated with variance in the overall distribution of gene expression levels. A decrease in the variance in the distribution of gene expression levels in peripheral blood lymphocytes (PBL) was associated with the diagnosis of autism and a risk factor for autism, increased paternal age. Traditional approaches to microarray analysis of gene expression suggested a possible mechanism for decreased variance in gene expression. Gene expression pathways involved in transcriptional regulation were down-regulated in the blood of children with autism and children of older fathers. Thus, results from global and gene specific approaches to studying microarray data were complimentary and supported the hypothesis that alterations at the global level of gene expression regulation are related to autism and increased paternal age. Regulation of transcription, thus, represents a possible point of convergence for multiple etiologies of autism and other neurodevelopmental disorders. The study was designed to compare gene expression profiles in peripheral blood lymphocytes of children with autism (n=82) and controls(n=64). Expression profiling: Expression profiling was performed at Translational Genomics (TGen), a member of the NIMH Neuroscience Microarray Consortium. Total RNA was extracted from peripheral blood lymphocytes (PBL) within 30 minutes of the blood draw using the Qiagen Qiaquick kit (Germantown, MD). Isolated total RNA was double round amplified, cleaned, and biotin-labeled using Affymetrix’s GeneChip Two-Cycle Target Labeling kit (Santa Clara, CA) with a T7 promoter and Ambion’s MEGAscript T7 High Yield Transcription kit (Austin, TX) as per manufacturer’s protocol. Amplified and labeled cRNA was quantified on a spectrophotometer and run on a 1% TAE gel to check for an evenly distributed range of transcript sizes. Twenty micrograms of cRNA was fragmented to approximately 35-200bp by alkaline treatment (200 mM Tris-acetate, pH 8.2, 500 mM KOAc, 150 mM MgOAc) and run on a 1% TAE gell to verify fragmentation. Separate hybridization cocktails were made using 15 micrograms of fragmented cRNA from each sample as per Affymetrix’s protocol. Two hundred microliters (containing 10 micrograms of fragmented cRNA) of each cocktail was separately hybridized to an Affymetrix Human Genome U133 Plus 2.0 Array for 16h at 45 degree Celsius in the Hybridization Oven 640. The Affymetrix Human Genome Arrays measure the expression of over 47,000 transcripts and variants, including 38,500 characterized human genes. Arrays were washed on Affymetrix’s GeneChip Fluidics Station 450 using a primary streptavidin phycoerythrin (SAPE) stain, subsequent biotinylated antibody stain, and secondary SAPE stain. Arrays were scanned on Affymetrix’s GeneChip Scanner 3000 7G with AutoLoader. Scanned images obtained by the Affymetrix GeneChip Operating Software (GCOS) v1.2 were used to extract raw signal intensity values per probe set on the array. A scaling factor of 150 was used to normalize array signal intensity in MAS 5.0. Arrays were scanned over 1 day on 2 different machines. Arrays scanned on the same machine and in the same day were considered to be from the same scan batch. Rescanning of a limited number of samples indicated that there were no significant differences between machines, nonetheless, for all comparisons groups were balanced for the scan batch. Gene expression levels were not adjusted for possible batch effects as algorithms that attempt to adjust for batch effects also alter the gene expression distribution. When samples could not be prepped simultaneously they were balanced for group membership (autism vs. control). To statistically control for possible confounds related to scan batches in our analysis of gene expression variance, batch number was entered into an analysis of covariance. For traditional analysis of gene expression, experimental groups were balanced with respect to batch membership. Microarray data analysis: Affymetrix .cel files were imported into Affymetrix Expression Console version 1.1. Data was pre-processed and summarized by Microarray Analysis Suite (MAS) 5.0 and Robust Multiarray Analysis (RMA). For the analysis of gene expression distributions, MAS 5.0 was used because the algorithm does not alter the gene expression distribution, whereas, RMA utilizes quantile normalization of probes prior to summarization and, therefore, has the potential to remove group level differences in gene expression distributions. Because of the numerous advantages in its handling of noise in gene expression and background subtraction, RMA was used for traditional gene expression analyses looking for specific gene expression differences between groups. Because, we found group level differences in the distribution of gene expression levels between groups, for traditional gene expression analyses summarized gene expression levels were also quantile normalized after the summarization step. Quantile normalization adjusts all data sets such that they have identical distribution patterns. Probesets were then filtered for those that were called present in at least 50 out of the 146 subjects (n = 25,146 probesets). A p-value of .05 was used as a threshold for significance. A fold-change of 1.1 was used as a cut off for magnitude of change. All microarrays met manufacturers recommended quality control criteria. Present calls ranged from 37.4% to 49%, mean 43.7%, SD 2.7%. Actin 3’to5’ ratios ranged from .726 to 5.15, mean1.37, SD 0.5. There were no significant group level differences in quality control measures.
2011-10-08 | E-GEOD-25507 | biostudies-arrayexpress
Project description:Autism is currently considered a multigene disorder with epigenetic influences. To investigate the contribution of DNA methylation to autism spectrum disorders, we have recently completed large-scale methylation profiling by CpG island microarray analysis of lymphoblastoid cell lines (LCL) derived from monozygotic twins discordant for diagnosis of autism and their nonautistic siblings. Methylation profiling revealed many candidate genes differentially methylated between discordant MZ twins as well as between both twins and nonautistic siblings. Bioinformatics analysis of the differentially methylated genes demonstrated enrichment for high level functions including gene transcription, nervous system development, cell death/survival, and other biological processes implicated in autism. The methylation status of two of these candidate genes, BCL-2 and retinoic acid receptor (RAR)-related orphan receptor alpha (RORA), was further confirmed by bisulfite sequencing and methylation-specific PCR, respectively. Immunohistochemical analyses of tissue arrays containing slices of the cerebellum and frontal cortex of autistic and age- and sex-matched control subjects revealed decreased expression of RORA and BCL-2 proteins in the autistic brain. Our data thus confirm the role of epigenetic regulation of gene expression via differential DNA methylation in idiopathic autism, and furthermore link molecular changes in a peripheral cell model with brain pathobiology in autism. Global methylation profiling was performed on lymphoblastoid cell lines (LCLs) derived from three pairs of male monozygotic twins discordant for diagnosis of autism as determined by the Autism Diagnostic Interview-Revised (ADI-R). As controls, cell lines derived from non-autistic siblings of two pairs of twins were also included in the analyses, in addition to cell lines derived from a set of monozygotic twins unaffected by autism. For all paired analyses, a direct comparison was performed in which the methylation-enriched fractions from two individuals were pooled and hybridized onto the same microarray. In addition, indirect comparisons were performed by co-hybridizing the methylation-enriched (MIRA) fraction with the respective unenriched DNA fraction obtained from the same individual. For each paired analysis (between autistic MZ twins and/or between autistic co-twin and unaffected sibling), a total number of 4 replicates were performed, including direct and indirect comparisons.
2010-04-27 | E-GEOD-21395 | biostudies-arrayexpress
Project description:gene expression profiles of lymphoblastoid cells from individuals with autism and duplication of 15q11-13 Keywords: autism with dup(15q)
2007-06-01 | GSE7315 | GEO
Project description:Significant differential expression genes from HUVECs induced by bg-CAT
2025-01-16 | E-GEOD-10479 | ExpressionAtlas
Project description:Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by delayed/abnormal language development, deficits in social interaction, repetitive behaviors and restricted interests. The heterogeneity in clinical presentation of ASD, likely due to different etiologies, complicates genetic/biological analyses of these disorders. DNA microarray analyses were conducted on 116 lymphoblastoid cell lines (LCL) from individuals with idiopathic autism who are divided into 3 phenotypic subgroups according to severity scores from the commonly used Autism Diagnostic Interview-Revised questionnaire and age-matched, nonautistic controls. Statistical analyses of gene expression data from control LCL against that of LCL from ASD probands identify genes for which expression levels are either quantitatively or qualitatively associated with phenotypic severity. Comparison of the significant differentially expressed genes from each subgroup relative to the control group reveals differentially expressed genes unique to each subgroup as well as genes in common across subgroups. Among the findings unique to the most severely affected ASD group are genes that regulate circadian rhythm, which has been shown to have multiple effects on neurological as well as metabolic functions commonly dysregulated in autism. Among the genes common to all 3 subgroups of ASD are 5 novel genes which appear to associate with androgen sensitivity, which may underlie the strong 4:1 bias towards affected males.
2009-12-22 | GSE15402 | GEO