Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Genetics and genomics of autism spectrum disorder: embracing complexity.

ABSTRACT: Autism spectrum disorder (ASD) is a neurodevelopmental disorder (NDD) characterized by impairments in social communication and social interaction and the presence of repetitive behaviors and/or restricted interests. ASD has profound etiological and clinical heterogeneity, which has impeded the identification of risk factors and pathophysiological processes underlying the disorder. A constellation of (i) types of genetic variation, (ii) modes of inheritance and (iii) specific genomic loci and genes have all recently been implicated in ASD risk, and these findings are currently being extended with functional analyses in model organisms and genotype-phenotype correlation studies. The overlap of risk loci between ASD and other NDDs raises intriguing questions around the mechanisms of risk. In this review, we will touch upon these aspects of ASD and how they might be addressed.

SUBMITTER: De Rubeis S

PROVIDER: S-EPMC4675826 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Genetics and genomics of autism spectrum disorder: embracing complexity.

De Rubeis Silvia S Buxbaum Joseph D JD

Human molecular genetics 20150717 R1

Autism spectrum disorder (ASD) is a neurodevelopmental disorder (NDD) characterized by impairments in social communication and social interaction and the presence of repetitive behaviors and/or restricted interests. ASD has profound etiological and clinical heterogeneity, which has impeded the identification of risk factors and pathophysiological processes underlying the disorder. A constellation of (i) types of genetic variation, (ii) modes of inheritance and (iii) specific genomic loci and gen ...[more]

PMID: 26188008

Similar Datasets

KDM5A mutations identified in autism spectrum disorder using forward genetics.

Project description:Autism spectrum disorder (ASD) is a constellation of neurodevelopmental disorders with high phenotypic and genetic heterogeneity, complicating the discovery of causative genes. Through a forward genetics approach selecting for defective vocalization in mice, we identified Kdm5a as a candidate ASD gene. To validate our discovery, we generated a Kdm5a knockout mouse model (Kdm5a-/-) and confirmed that inactivating Kdm5a disrupts vocalization. In addition, Kdm5a-/- mice displayed repetitive behaviors, sociability deficits, cognitive dysfunction, and abnormal dendritic morphogenesis. Loss of KDM5A also resulted in dysregulation of the hippocampal transcriptome. To determine if KDM5A mutations cause ASD in humans, we screened whole exome sequencing and microarray data from a clinical cohort. We identified pathogenic KDM5A variants in nine patients with ASD and lack of speech. Our findings illustrate the power and efficacy of forward genetics in identifying ASD genes and highlight the importance of KDM5A in normal brain development and function.

| S-EPMC7755391 | biostudies-literature

Genetics of glutamate and its receptors in autism spectrum disorder.

Project description:Autism spectrum disorder (ASD) is a neurodevelopmental impairment characterized by deficits in social interaction skills, impaired communication, and repetitive and restricted behaviors that are thought to be due to altered neurotransmission processes. The amino acid glutamate is an essential excitatory neurotransmitter in the human brain that regulates cognitive functions such as learning and memory, which are usually impaired in ASD. Over the last several years, increasing evidence from genetics, neuroimaging, protein expression, and animal model studies supporting the notion of altered glutamate metabolism has heightened the interest in evaluating glutamatergic dysfunction in ASD. Numerous pharmacological, behavioral, and imaging studies have demonstrated the imbalance in excitatory and inhibitory neurotransmitters, thus revealing the involvement of the glutamatergic system in ASD pathology. Here, we review the effects of genetic alterations on glutamate and its receptors in ASD and the role of non-invasive imaging modalities in detecting these changes. We also highlight the potential therapeutic targets associated with impaired glutamatergic pathways.

| S-EPMC9135628 | biostudies-literature

Genetics of Autism Spectrum Disorder: Current Status and Possible Clinical Applications.

Project description:Autism spectrum disorder (ASD) is one of the most complex behavioral disorders with a strong genetic influence. The objectives of this article are to review the current status of genetic research in ASD, and to provide information regarding the potential candidate genes, mutations, and genetic loci possibly related to pathogenesis in ASD. Investigations on monogenic causes of ASD, candidate genes among common variants, rare de novo mutations, and copy number variations are reviewed. The current possible clinical applications of the genetic knowledge and their future possibilities are highlighted.

| S-EPMC4688327 | biostudies-literature

Genetics of structural and functional brain changes in autism spectrum disorder.

Project description:Autism spectrum disorder (ASD) is a neurological and developmental disorder characterized by social impairment and restricted interactive and communicative behaviors. It may occur as an isolated disorder or in the context of other neurological, psychiatric, developmental, and genetic disorders. Due to rapid developments in genomics and imaging technologies, imaging genetics studies of ASD have evolved in the last few years. Increased risk for ASD diagnosis is found to be related to many specific single-nucleotide polymorphisms, and the study of genetic mechanisms and noninvasive imaging has opened various approaches that can help diagnose ASD at the nascent level. Identifying risk genes related to structural and functional changes in the brain of ASD patients provide a better understanding of the disease's neuropsychiatry and can help identify targets for therapeutic intervention that could be useful for the clinical management of ASD patients.

| S-EPMC7359361 | biostudies-literature

Dynamical Electrical Complexity Is Reduced during Neuronal Differentiation in Autism Spectrum Disorder.

Project description:Neuronal activity can be modeled as a nonlinear dynamical system to yield measures of neuronal state and dysfunction. The electrical recordings of stem cell-derived neurons from individuals with autism spectrum disorder (ASD) and controls were analyzed using minimum embedding dimension (MED) analysis to characterize their dynamical complexity. MED analysis revealed a significant reduction in dynamical complexity in ASD neurons during differentiation, which was correlated to bursting and spike interval measures. MED was associated with clinical endpoints, such as nonverbal intelligence, and was correlated with 53 differentially expressed genes, which were overrepresented with ASD risk genes related to neurodevelopment, cell morphology, and cell migration. Spatiotemporal analysis also showed a prenatal temporal enrichment in cortical and deep brain structures. Together, we present dynamical analysis as a paradigm that can be used to distinguish disease-associated cellular electrophysiological and transcriptional signatures, while taking into account patient variability in neuropsychiatric disorders.

| S-EPMC6739708 | biostudies-literature

Minimum embedding dimension analysis uncovers reduced network complexity during neuronal differentiation in autism spectrum disorder

Project description:Background: Neuronal activity can be modeled as a nonlinear dynamical system to yield novel measures of neuronal state and dysfunction. We hypothesized that electrical activity during neuronal differentiation would be marked by a reduction in dynamical complexity in autism spectrum disorder (ASD). Methods: Electrical activity of induced pluripotent stem cell (iPSC)-derived neurons from ASD patients and controls were recorded using a multielectrode array (MEA). Minimum embedding dimension (MED) analysis was performed to characterize the complexity present in the electrical recordings of the neuronal cultures during differentiation. Gene expression changes with respect to the MED were analyzed, and gene ontology analysis and the BrainSpan Atlas were used to identify gene enrichments in specific biological pathways, brain regions, and developmental stages. Results: We found that the MED showed a statistically significant deficit in the ASD samples, suggesting that, compared to controls, network complexity is reduced in ASD during neuronal differentiation. MED was correlated to clinical endpoints such as nonverbal intelligence and was associated with 53 differentially expressed genes. These differentially expressed genes were overrepresented in ASD gene lists and pathways related to neurodevelopment, cell morphology, and cell migration. Spatiotemporal analysis also showed a prenatal temporal enrichment in cortical and deep brain structures. Conclusion: Reduced network complexity in ASD was observed by MED analysis during neuronal differentiation, indicating deficits in integrated and synchronized firing. The results present nonlinear dynamical analysis of iPSC-derived neuronal electrical recordings as a new paradigm for the investigation of aberrant brain activity in neurodevelopmental disorders.

2020-05-18 | GSE125020 | GEO

Transcriptional organization of autism spectrum disorder

Project description:This SuperSeries is composed of the SubSeries listed below.

2018-02-27 | GSE111176 | GEO

Imaging-genetics in autism spectrum disorder: advances, translational impact, and future directions.

Project description:Autism Spectrum Disorder (ASD) refers to a group of heterogeneous neurodevelopmental disorders that are unified by impairments in reciprocal social communication and a pattern of inflexible behaviors. Recent genetic advances have resolved some of the complexity of the genetic architecture underlying ASD by identifying several genetic variants that contribute to the disorder. Different etiological pathways associated with ASD may converge through effects on common molecular mechanisms, such as synaptogenesis, neuronal motility, and axonal guidance. Recently, with more sophisticated techniques, neuroimaging, and neuropathological studies have provided some consistency of evidence that altered structure, activity, and connectivity within complex neural networks is present in ASD, compared to typically developing children. The imaging-genetics approach promises to help bridge the gap between genetic variation, resultant biological effects on the brain, and production of complex neuropsychiatric symptoms. Here, we review recent findings from the developing field of imaging-genetics applied to ASD. Studies to date have indicated that relevant risk genes are associated with alterations in circuits that mediate socio-emotional, visuo-spatial, and language processing. Longitudinal studies ideally focused on early development, in conjunction with investigation for gene-gene, and gene-environment interactions may move the promise of imaging-genetics in ASD closer to the clinical domain.

| S-EPMC3351673 | biostudies-literature

Autism spectrum disorder.

Project description:Autism spectrum disorder is a construct used to describe individuals with a specific combination of impairments in social communication and repetitive behaviours, highly restricted interests and/or sensory behaviours beginning early in life. The worldwide prevalence of autism is just under 1%, but estimates are higher in high-income countries. Although gross brain pathology is not characteristic of autism, subtle anatomical and functional differences have been observed in post-mortem, neuroimaging and electrophysiological studies. Initially, it was hoped that accurate measurement of behavioural phenotypes would lead to specific genetic subtypes, but genetic findings have mainly applied to heterogeneous groups that are not specific to autism. Psychosocial interventions in children can improve specific behaviours, such as joint attention, language and social engagement, that may affect further development and could reduce symptom severity. However, further research is necessary to identify the long-term needs of people with autism, and treatments and the mechanisms behind them that could result in improved independence and quality of life over time. Families are often the major source of support for people with autism throughout much of life and need to be considered, along with the perspectives of autistic individuals, in both research and practice.

| S-EPMC8900942 | biostudies-literature

Epigenome analysis of autism spectrum disorder samples

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

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data