scholarly journals Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder

2016 ◽  
Vol 19 (11) ◽  
pp. 1454-1462 ◽  
Author(s):  
Arjun Krishnan ◽  
Ran Zhang ◽  
Victoria Yao ◽  
Chandra L Theesfeld ◽  
Aaron K Wong ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Genetic Basis ◽  
Functional Characterization ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Genome Wide

scholarly journals Functional characterization of FABP3, 5 and 7 gene variants identified in schizophrenia and autism spectrum disorder and mouse behavioral studies

2014 ◽  
Vol 23 (24) ◽  
pp. 6495-6511 ◽  
Author(s):  
Chie Shimamoto ◽  
Tetsuo Ohnishi ◽  
Motoko Maekawa ◽  
Akiko Watanabe ◽  
Hisako Ohba ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Characterization ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Gene Variants ◽  
Behavioral Studies

scholarly journals Genome-wide characterization of genetic and functional dysregulation in autism spectrum disorder

2016 ◽  
Author(s):  
Arjun Krishnan ◽  
Ran Zhang ◽  
Victoria Yao ◽  
Chandra L. Theesfeld ◽  
Aaron K. Wong ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Human Brain ◽  
Genetic Basis ◽  
Interaction Network ◽  
Autism Spectrum ◽  
Genetic Evidence ◽  
Spectrum Disorder ◽  
Large Set ◽  
Genome Wide ◽  
The Brain

AbstractAutism spectrum disorder (ASD) is a range of major neurodevelopmental disabilities with a strong genetic basis. Yet, owing to extensive genetic heterogeneity, multiple modes of inheritance and limited study sizes, sequencing and quantitative genetics approaches have had limited success in characterizing the complex genetics of ASD. Currently, only a small fraction of potentially causal genes—about 65 genes out of an estimated severalhundred—are known based on strong genetic evidence. Hence, there isa critical need for complementary approaches to further characterize the genetic basis of ASD, enabling development of better screening and therapeutics. Here, we use a machine-learning approach based on a human brain-specific functional gene interaction network to present a genome-wide prediction of autism-associated genes, including hundreds of candidate genes for which there is minimal or no prior genetic evidence. Our approach is validated in an independent case-control sequencing study of approximately 2,500families. Leveraging these genome-wide predictions and the brain-specificnetwork, we demonstrate that the large set of ASD genes converges on a smaller number of key cellular pathways and specific developmental stages of the brain. Specifically, integration with spatiotemporal transcriptome expression data implicates early fetal and midfetal stages of the developing human brain in ASD etiology. Likewise, analysis of the connectivity of topautism genes in the brain-specific interaction network reveals the breadthof autism-associated functional modules, processes, and pathways in the brain. Finally, we identify likely pathogenic genes within the most frequent autism-associated copy-number-variants (CNVs) and propose genes and pathways that are likely mediators of autism across multiple CNVs. All the predictions, interactions, and functional insights from this work are available to biomedical researchers at asd.princeton.edu.

scholarly journals High Resolution Magnetic Resonance Imaging for Characterization of the Neuroligin-3 Knock-in Mouse Model Associated with Autism Spectrum Disorder

PLoS ONE ◽  
2014 ◽  
Vol 9 (10) ◽  
pp. e109872 ◽  
Author(s):  
Manoj Kumar ◽  
Jeffery T. Duda ◽  
Wei-Ting Hwang ◽  
Charles Kenworthy ◽  
Ranjit Ittyerah ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Autism Spectrum Disorder ◽  
Magnetic Resonance ◽  
High Resolution ◽  
Mouse Model ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Resonance Imaging

The Genetic Basis of Autism Spectrum Disorder

2015 ◽  
pp. 39-63
Author(s):  
Jaqueline Bohrer Schuch ◽  
Luiza Monteavaro Mariath ◽  
Tatiana Roman ◽  
Lavinia Schuler-Faccini
Keyword(s):  
Autism Spectrum Disorder ◽  
Genetic Basis ◽  
Autism Spectrum ◽  
Spectrum Disorder

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.

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