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Front Genet. 2014 Feb 18;5:33. doi: 10.3389/fgene.2014.00033. eCollection 2014.

A scoring strategy combining statistics and functional genomics supports a possible role for common polygenic variation in autism.

Author information

  • 1IntegraGen Evry, France.
  • 2Department of Pathology and Laboratory Medicine, University of Pennsylvania Philadelphia, PA, USA.
  • 3Groupe Hospitalier Pitié-Salpêtrière, Department of Child and Adolescent Psychiatry, AP-HP, Université Pierre et Marie Curie Paris, France.
  • 4Center for Pediatric Behavioral Health and Center for Autism, Cleveland Clinic Cleveland, OH, USA.
  • 5Department of Psychiatry and Behavioral Sciences, Stanford University Stanford, CA, USA.
  • 6Department of Psychiatry and Behavioral Sciences, Duke University Medical Center Durham, NC, USA.

Abstract

Autism spectrum disorders (ASD) are highly heritable complex neurodevelopmental disorders with a 4:1 male: female ratio. Common genetic variation could explain 40-60% of the variance in liability to autism. Because of their small effect, genome-wide association studies (GWASs) have only identified a small number of individual single-nucleotide polymorphisms (SNPs). To increase the power of GWASs in complex disorders, methods like convergent functional genomics (CFG) have emerged to extract true association signals from noise and to identify and prioritize genes from SNPs using a scoring strategy combining statistics and functional genomics. We adapted and applied this approach to analyze data from a GWAS performed on families with multiple children affected with autism from Autism Speaks Autism Genetic Resource Exchange (AGRE). We identified a set of 133 candidate markers that were localized in or close to genes with functional relevance in ASD from a discovery population (545 multiplex families); a gender specific genetic score (GS) based on these common variants explained 1% (P = 0.01 in males) and 5% (P = 8.7 × 10(-7) in females) of genetic variance in an independent sample of multiplex families. Overall, our work demonstrates that prioritization of GWAS data based on functional genomics identified common variants associated with autism and provided additional support for a common polygenic background in autism.

KEYWORDS:

autism; common variants; functional genomics; genetic score; genetic variance; polygenic model

PMID:
24600472
[PubMed]
PMCID:
PMC3927086
Free PMC Article
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