Discovery of regulatory variants underlying pediatric neurological disease

  • Awarded: 2015
  • Award Type: Targeted: Whole-Genome Analysis for Autism Risk Variants
  • Award #: 385330

Autism, intellectual disability, developmental delay and related phenotypes affect more than 1 percent of children worldwide. These conditions can reduce the length and quality of life of affected individuals, and contribute to emotional distress, financial challenges and lifestyle restrictions for affected families. Because these conditions are diverse and sometimes severe, many affected children undergo years of interactions with clinicians and costly testing procedures without ever receiving a precise medical diagnosis.

Recent advances in genetic and genomic technologies have demonstrated that genetic changes underlie much of the risk for autism and intellectual disabilities. Although genetic testing can provide more precise, predictive and informative diagnoses to affected children and their families, and considerable improvements have been made in genetic screening, a large fraction of affected individuals remain undiagnosed even after substantial genetic testing.

Greg Cooper and his colleagues at the HudsonAlpha Institute for Biotechnology aim to identify new genetic risk factors for autism and related conditions by taking advantage of the whole-genome sequencing (WGS) data from 500 affected children and their unaffected parents and siblings, as part of the Simons Simplex Collection (SSC). Cooper and his team will focus their efforts on identifying risk factors located outside of protein-coding regions of the genome. Using both automated and manual variant assessment, they will search for patterns of noncoding variant clustering near genes and gene groups defined by ontology, pathway and other resources. They plan to combine systematic analyses of the SSC WGS data with their own clinical sequencing data from children with similar, overlapping conditions. They will also exploit unique data resources and innovative methods that they have developed to analyze the WGS data.

Results from this research project are expected to lead to better insights into the genetic and molecular mechanisms that contribute to autism and related conditions, improve diagnostic success rates and help to guide further research to improve health and educational outcomes for the millions of affected children and their families.

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