Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.

A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder.

BACCHELLI, ELENA;MAESTRINI, ELENA;MINOPOLI, FIORELLA;
2012

Abstract

Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.
Casey JP; Magalhaes T; Conroy JM; Regan R; Shah N; Anney R; Shields DC; Abrahams BS; Almeida J; Bacchelli E; Bailey AJ; Baird G; Battaglia A; Berney T; Bolshakova N; Bolton PF; Bourgeron T; Brennan S; Cali P; Correia C; Corsello C; Coutanche M; Dawson G; de Jonge M; Delorme R; Duketis E; Duque F; Estes A; Farrar P; Fernandez BA; Folstein SE; Foley S; Fombonne E; Freitag CM; Gilbert J; Gillberg C; Glessner JT; Green J; Guter SJ; Hakonarson H; Holt R; Hughes G; Hus V; Igliozzi R; Kim C; Klauck SM; Kolevzon A; Lamb JA; Leboyer M; Le Couteur A; Leventhal BL; Lord C; Lund SC; Maestrini E; Mantoulan C; Marshall CR; McConachie H; McDougle CJ; McGrath J; McMahon WM; Merikangas A; Miller J; Minopoli F; Mirza GK; Munson J; Nelson SF; Nygren G; Oliveira G; Pagnamenta AT; Papanikolaou K; Parr JR; Parrini B; Pickles A; Pinto D; Piven J; Posey DJ; Poustka A; Poustka F; Ragoussis J; Roge B; Rutter ML; Sequeira AF; Soorya L; Sousa I; Sykes N; Stoppioni V; Tancredi R; Tauber M; Thompson AP; Thomson S; Tsiantis J; Van Engeland H; Vincent JB; Volkmar F; Vorstman JA; Wallace S; Wang K; Wassink TH; White K; Wing K; Wittemeyer K; Yaspan BL; Zwaigenbaum L; Betancur C; Buxbaum JD; Cantor RM; Cook EH; Coon H; Cuccaro ML; Geschwind DH; Haines JL; Hallmayer J; Monaco AP; Nurnberger JI Jr; Pericak-Vance MA; Schellenberg GD; Scherer SW; Sutcliffe JS; Szatmari P; Vieland VJ; Wijsman EM; Green A; Gill M; Gallagher L; Vicente A; Ennis S.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/107208
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