40 research outputs found

    Expanded Insights Into Mechanisms of Gene Expression and Disease Related Disruptions

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    Definitive molecular diagnoses in disorders apparently due to genetic or genomic defects are still lacking in a significant number of investigated cases, despite use of studies designed to discover defects in the protein coding regions of the genome. Increasingly studies are being designed to search for defects in the non-protein coding genome, and for alterations in gene expression. Here we review new insights into genomic elements involved in control of gene expression, including methods to analyze chromatin that is accessible for transcription factor binding, enhancers, chromatin looping, transcription, RNA binding proteins, and alternative splicing. We review new studies on levels of genome organization, including the occurrence of transcriptional domains and their boundary elements. Information is presented on specific malformation syndromes that arise due to structural genomic changes that impact the non-protein coding genome and sometimes impact specific transcriptional domains. We also review convergence of genome-wide association with studies of gene expression, discoveries related to expression quantitative trait loci and splicing quantitative trait loci and the relevance of these to specific complex common diseases. Aspects of epigenetic mechanisms and clinical applications of analyses of methylation signatures are also discussed

    A case of autism with an interstitial deletion on 4q leading to hemizygosity for genes encoding for glutamine and glycine neurotransmitter receptor sub-units (AMPA 2, GLRA3, GLRB) and neuropeptide receptors NPY1R, NPY5R

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    BACKGROUND: Autism is a pervasive developmental disorder characterized by a triad of deficits: qualitative impairments in social interactions, communication deficits, and repetitive and stereotyped patterns of behavior. Although autism is etiologically heterogeneous, family and twin studies have established a definite genetic basis. The inheritance of idiopathic autism is presumed to be complex, with many genes involved; environmental factors are also possibly contributory. The analysis of chromosome abnormalities associated with autism contributes greatly to the identification of autism candidate genes. CASE PRESENTATION: We describe a child with autistic disorder and an interstitial deletion on chromosome 4q. This child first presented at 12 months of age with developmental delay and minor dysmorphic features. At 4 years of age a diagnosis of Pervasive Developmental Disorder was made. At 11 years of age he met diagnostic criteria for autism. Cytogenetic studies revealed a chromosome 4q deletion. The karyotype was 46, XY del 4 (q31.3-q33). Here we report the clinical phenotype of the child and the molecular characterization of the deletion using molecular cytogenetic techniques and analysis of polymorphic markers. These studies revealed a 19 megabase deletion spanning 4q32 to 4q34. Analysis of existing polymorphic markers and new markers developed in this study revealed that the deletion arose on a paternally derived chromosome. To date 33 genes of known or inferred function are deleted as a consequence of the deletion. Among these are the AMPA 2 gene that encodes the glutamate receptor GluR2 sub-unit, GLRA3 and GLRB genes that encode glycine receptor subunits and neuropeptide Y receptor genes NPY1R and NPY5R. CONCLUSIONS: The deletion in this autistic subject serves to highlight specific autism candidate genes. He is hemizygous for AMPA 2, GLRA3, GLRB, NPY1R and NPY5R. GluR2 is the major determinant of AMPA receptor structure. Glutamate receptors maintain structural and functional plasticity of synapses. Neuropeptide Y and its receptors NPY1R and NPY5R play a role in hippocampal learning and memory. Glycine receptors are expressed in very early cortical development. Molecular cytogenetic studies and DNA sequence analysis in other patients with autism will be necessary to confirm that these genes are involved in autism

    Rightward hemispheric asymmetries in auditory language cortex in children with autistic disorder: an MRI investigation

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    Purpose: determine if language disorder in children with autistic disorder (AD) corresponds to abnormalities in hemispheric asymmetries in auditory language cortex. Methods: MRI morphometric study in children with AD (n = 50) to assess hemispheric asymmetries in auditory language cortex. A key region of interest was the planum temporale (PT), which is larger in the left hemisphere in most healthy individuals. Results: (i) Heschl’s gyrus and planum polare showed typical hemisphere asymmetry patterns; (ii) posterior Superior Temporal Gyrus (pSTG) showed significant rightward asymmetry; and (iii) PT showed a trend for rightward asymmetry that was significant when constrained to right-handed boys (n = 30). For right-handed boys, symmetry indices for pSTG were significantly positively correlated with those for PT. PT asymmetry was age dependent, with greater rightward asymmetry with age. Conclusions: results provide evidence for rightward asymmetry in auditory association areas (pSTG and PT) known to subserve language processing. Cumulatively, our data provide evidence for a differing maturational path for PT for lower functioning children with AD, with both pre- and post-natal experience likely playing a role in PT asymmetry

    Determining Complex Genetic Risks by Computer

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    Mixture model based group inference in fused genotype and phenotype data

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    The analysis of genetic diseases has classically been directed towards establishing direct links between cause, a genetic variation, and effect, the observable deviation of phenotype. For complex diseases which are caused by multiple factors and which show a wide spread of variations in the phenotypes this is unlikely to succeed. One example is the Attention Deficit Hyperactivity Disorder (ADHD), where it is expected that phenotypic variations will be caused by the overlapping effects of several distinct genetic mechanisms. The classical statistical models to cope with overlapping subgroups are mixture models, essentially convex combinations of density functions, which allow inference of descriptive models from data as well as the deduction of groups. An extension of conventional mixtures with attractive properties for clustering is the context-specific independence (CSI) framework. CSI allows for an automatic adaption of model complexity to avoid overfitting and yields a highly descriptive model
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