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Original Research ARTICLE

Front. Genet., 18 February 2014 | http://dx.doi.org/10.3389/fgene.2014.00033

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

Jérôme Carayol1*, Gerard D. Schellenberg2, Beth Dombroski2, Claire Amiet1, Bérengère Génin1, Karine Fontaine1, Francis Rousseau1, Céline Vazart1, David Cohen3, Thomas W. Frazier4, Antonio Y. Hardan5, Geraldine Dawson6 and Thomas Rio Frio1
  • 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

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, genetic variance, polygenic model, common variants, genetic score, functional genomics

Citation: Carayol J, Schellenberg GD, Dombroski B, Amiet C, Génin B, Fontaine K, Rousseau F, Vazart C, Cohen D, Frazier TW, Hardan AY, Dawson G and Rio Frio T (2014) A scoring strategy combining statistics and functional genomics supports a possible role for common polygenic variation in autism. Front. Genet. 5:33. doi: 10.3389/fgene.2014.00033

Received: 16 July 2013; Accepted: 29 January 2014;
Published online: 18 February 2014.

Edited by:

Ravinesh A. Kumar, University of Chicago, USA

Reviewed by:

Judith A. Badner, University of Chicago, USA
Yong-Kyu Kim, Howard Hughes Medical Institute, USA
David Duffy, Queensland Institute of Medical Research, Australia
Benjamin Neale, Massachusetts General Hospital, USA

Copyright © 2014 Carayol, Schellenberg, Dombroski, Amiet, Génin, Fontaine, Rousseau, Vazart, Cohen, Frazier, Hardan, Dawson and Rio Frio. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jerôme Carayol, IntegraGen, 5 rue Henri Desbrueres, 91000 Evry, France e-mail: jerome.carayol@integragen.com