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Detecting large copy number variants using exome genotyping arrays in a large Swedish schizophrenia sample

Abstract

Although copy number variants (CNVs) are important in genomic medicine, CNVs have not been systematically assessed for many complex traits. Several large rare CNVs increase risk for schizophrenia (SCZ) and autism and often demonstrate pleiotropic effects; however, their frequencies in the general population and other complex traits are unknown. Genotyping large numbers of samples is essential for progress. Large cohorts from many different diseases are being genotyped using exome-focused arrays designed to detect uncommon or rare protein-altering sequence variation. Although these arrays were not designed for CNV detection, the hybridization intensity data generated in each experiment could, in principle, be used for gene-focused CNV analysis. Our goal was to evaluate the extent to which CNVs can be detected using data from one particular exome array (the Illumina Human Exome Bead Chip). We genotyped 9100 Swedish subjects (3962 cases with SCZ and 5138 controls) using both standard genome-wide association study (GWAS) and exome arrays. In comparison with CNVs detected using GWAS arrays, we observed high sensitivity and specificity for detecting genic CNVs 400 kb including known pathogenic CNVs along with replicating the literature finding that cases with SCZ had greater enrichment for genic CNVs. Our data confirm the association of SCZ with 16p11.2 duplications and 22q11.2 deletions, and suggest a novel association with deletions at 11q12.2. Our results suggest the utility of exome-focused arrays in surveying large genic CNVs in very large samples; and thereby open the door for new opportunities such as conducting well-powered CNV assessment and comparisons between different diseases. The use of a single platform also minimizes potential confounding factors that could impact accurate detection.

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Acknowledgements

Funding was from K01 MH093517 (JPS), R01 MH077139 (PFS), the Stanley Center for Psychiatric Research, the Karolinska Institutet, Karolinska University Hospital, the Swedish Research Council, an ALF grant from Swedish County Council, the Söderström Königska Foundation and the Sylvan Herman Foundation. This study makes use of data generated by the DECIPHER Consortium. A full list of centers who contributed to the generation of the data is available from http://decipher.sanger.ac.uk or from decipher@sanger.ac.uk. Funding for the project was provided by the Wellcome Trust. We thank two anonymous reviewers for their helpful comments. All authors reviewed and approved the final version of the manuscript. The corresponding authors had access to the full data set.

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Correspondence to P F Sullivan.

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Dr Sullivan was on the SAB of Expression Analysis (Durham, NC, USA).

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Szatkiewicz, J., Neale, B., O'Dushlaine, C. et al. Detecting large copy number variants using exome genotyping arrays in a large Swedish schizophrenia sample. Mol Psychiatry 18, 1178–1184 (2013). https://doi.org/10.1038/mp.2013.98

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