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Identification of risk genes for autism spectrum disorder through copy number variation analysis in Austrian families

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Abstract

Autism or autism spectrum disorder (ASD) is a range of neurodevelopmental disorders starting in early childhood and is characterized by impairments in communication and reciprocal social interaction and presence of restricted and repetitive patterns of behavior. The contribution of genetic factors to autism is clear in twin and family studies. It is apparent that, overall, ASD is a complex non-Mendelian disorder. Recent studies suggest that copy number variations (CNVs) play a significant role in the etiology of ASD. For the current work, we recruited 245 family members from 73 ASD families from Styria, Austria. The DNA from probands was genotyped with Affymetrix single nucleotide polymorphism (SNP) 6.0 microarrays to screen for CNVs in their genomes. Analysis of the microarray data was performed using three different algorithms, and a list of stringent calls was compared to existing CNV data from over 2,357 controls of European ancestry. For stringent calls not present in controls, quantitative real-time PCR (qRT-PCR) was used to validate the CNVs in the probands and in their family members. Twenty-two CNVs were validated from this set (five of which are apparently de novo), many of which appear likely to disrupt genes that may be considered as good candidates for neuropsychiatric disorders, including DLG2, S100B, ARX, DIP2A, HPCAL1, and GPHN. Several others disrupt genes that have previously been implicated in autism, such as BDNF, AUTS2, DPP6, and C18orf22, and our data add to the growing evidence of their involvement in ASD.

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Acknowledgments

We thank the patients and their families for participating in this study. This work was supported by grants from Genome Canada and the Ontario Genomics Institute, and ÖNB Jubiläumsfonds (Project Number 13226). A.C.L. holds a NeuroDevNet doctoral fellowship. S.W.S. holds the GlaxoSmithKline-CIHR Chair in Genome Sciences at the University of Toronto and The Hospital for Sick Children. This study makes use of data generated by the DECIPHER and ISCA (www.iscaconsortium.org) consortia. A full list of centers contributing to the generation of the DECIPHER data is available from http://decipher.sanger.ac.uk and via email from decipher@sanger.ac.uk. Funding for the DECIPHER project was provided by the Wellcome Trust.

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Correspondence to John B. Vincent.

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Gerald Egger and Katharina M. Roetzer contributed equally to this work.

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Egger, G., Roetzer, K.M., Noor, A. et al. Identification of risk genes for autism spectrum disorder through copy number variation analysis in Austrian families. Neurogenetics 15, 117–127 (2014). https://doi.org/10.1007/s10048-014-0394-0

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