13 research outputs found

    A Brain Region-Specific Predictive Gene Map for Autism Derived by Profiling a Reference Gene Set

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    Molecular underpinnings of complex psychiatric disorders such as autism spectrum disorders (ASD) remain largely unresolved. Increasingly, structural variations in discrete chromosomal loci are implicated in ASD, expanding the search space for its disease etiology. We exploited the high genetic heterogeneity of ASD to derive a predictive map of candidate genes by an integrated bioinformatics approach. Using a reference set of 84 Rare and Syndromic candidate ASD genes (AutRef84), we built a composite reference profile based on both functional and expression analyses. First, we created a functional profile of AutRef84 by performing Gene Ontology (GO) enrichment analysis which encompassed three main areas: 1) neurogenesis/projection, 2) cell adhesion, and 3) ion channel activity. Second, we constructed an expression profile of AutRef84 by conducting DAVID analysis which found enrichment in brain regions critical for sensory information processing (olfactory bulb, occipital lobe), executive function (prefrontal cortex), and hormone secretion (pituitary). Disease specificity of this dual AutRef84 profile was demonstrated by comparative analysis with control, diabetes, and non-specific gene sets. We then screened the human genome with the dual AutRef84 profile to derive a set of 460 potential ASD candidate genes. Importantly, the power of our predictive gene map was demonstrated by capturing 18 existing ASD-associated genes which were not part of the AutRef84 input dataset. The remaining 442 genes are entirely novel putative ASD risk genes. Together, we used a composite ASD reference profile to generate a predictive map of novel ASD candidate genes which should be prioritized for future research

    Clinical Implications of Human Population Differences in Genome-wide Rates of Functional Genotypes

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    There have been a number of recent successes in the use of whole genome sequencing and sophisticated bioinformatics techniques to identify pathogenic DNA sequence variants responsible for individual idiopathic congenital conditions. However, the success of this identification process is heavily influenced by the ancestry or genetic background of a patient with an idiopathic condition. This is so because potential pathogenic variants in a patient’s genome must be contrasted with variants in a reference set of genomes made up of other individuals’ genomes of the same ancestry as the patient. We explored the effect of ignoring the ancestries of both an individual patient and the individuals used to construct reference genomes. We pursued this exploration in two major steps. We first considered variation in the per-genome number and rates likely functional derived (i.e., non-ancestral, based on the chimp genome) single nucleotide variants and small indels in 52 individual whole human genomes sampled from 10 different global populations. We took advantage of a suite of computational and bioinformatics techniques to predict the functional effect of over 24 million genomic variants, both coding and non-coding, across these genomes. We found that the typical human genome harbors ~5.5-6.1 million total derived variants, of which ~12,000 are likely to have a functional effect (~5000 coding and ~7000 non-coding). We also found that the rates of functional genotypes per the total number of genotypes in individual whole genomes differ dramatically between human populations. We then created tables showing how the use of comparator or reference genome panels comprised of genomes from individuals that do not have the same ancestral background as a patient can negatively impact pathogenic variant identification. Our results have important implications for clinical sequencing initiatives

    UCLA neuroscience undergraduate students teaching local school children about the brain.

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    <p>(A) Explaining how the water in a jar protects an egg from breaking in much the same way that the cerebrospinal fluid protects the brain from damage. (B) School children look at healthy and diseased human brains wrapped in plastic. (C) Undergraduate neuroscience student introduces the brain to a classroom of seventh grade students. (D) Classroom of fifth grade students learn the gross anatomy of the brain from an undergraduate student holding a model human brain. All participants in this study (legal guardians of school children, undergraduate and graduate students) provided signed consent to publication of their likeness as part of this project.</p

    A genome sequencing program for novel undiagnosed diseases.

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    PurposeThe Scripps Idiopathic Diseases of Man (IDIOM) study aims to discover novel gene-disease relationships and provide molecular genetic diagnosis and treatment guidance for individuals with novel diseases using genome sequencing integrated with clinical assessment and multidisciplinary case review. Here we describe the operational protocol and initial results of the IDIOM study.MethodsA total of 121 cases underwent first-tier review by the principal investigators to determine whether the primary inclusion criteria were satisfied, 59 (48.8%) underwent second-tier review by our clinician-scientist review panel, and 17 patients (14.0%) and their family members were enrolled.Results60% of cases resulted in a plausible molecular diagnosis, and 18% of cases resulted in a confirmed molecular diagnosis. Two of three confirmed cases led to the identification of novel gene-disease relationships. In the third confirmed case a previously described but unrecognized disease was revealed. In all three confirmed cases a new clinical management strategy was initiated based on the genetic findings.ConclusionGenome sequencing provides tangible clinical benefit for individuals with idiopathic genetic disease, not only in the context of molecular genetic diagnosis of known rare conditions but also in cases where prior clinical information regarding a new genetic disorder is lacking
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