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Author Notes:

Correspondence: Dr D Moreno-De-Luca, Department of Human Genetics, Emory University School of Medicine, 615 Michael Street, Suite 315, Atlanta, GA 30322, USAE-mail: daniel.morenodeluca@yale.edu; Dr DH Ledbetter, Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA. E-mail: dhledbetter@geisinger.edu

We would like to thank the families and the investigators for their participation in the clinical, ASD, and control collections we used for this study.

We also thank DJ Cutler for expert statistical advice, CT Strauss for editorial assistance and EB Kaminsky and A Moreno-De-Luca for critical review of the manuscript.

We acknowledge support from AGRE and autism speaks.

We also acknowledge the resources provided by the AGRE Consortium (D Geschwind, M Bucan, W Brown, R Cantor, J Constantino, T Gilliam, M Herbert, C Lajonchere, D Ledbetter, C Martin, J Miller, S Nelson, G Schellenberg, C Samango-Sprouse, S Spence, M State, R Tanzi).

Approved researchers can obtain the AGRE population data set described in this study by applying online at http://research.agre.org/.

We are also grateful to the principal investigators of the SSC (A Beaudet, R Bernier, J Constantino, E Cook, E Fombonne, D Geschwind, R Goin-Kochel, E Hanson, D Grice, A Klin, D Ledbetter, C Lord, C Martin, D Martin, R Maxim, J Miles, O Ousley, K Pelphrey, B Peterson, J Piggot, C Saulnier, M State, W Stone, J Sutcliffe, C Walsh, Z Warren, E Wijsman).

We appreciate obtaining access to phenotypic data on SFARI Base. Approved researchers can obtain the SSC population data set described in this study by applying online at https://base.sfari.org.

The authors declare no conflict of interest.

Subjects:

Research Funding:

This work was funded in part by National Institutes of Health grants MH081754 (DHG, CLM) and MH074090 (DHL, CLM) and by a grant from the Simons Foundation (SFARI 124827 to CLM, MS).

The AGRE is a program of autism speaks and is supported, in part, by grant 1U24MH081810 from the National Institute of Mental Health to Clara M Lajonchere (PI).

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Biochemistry & Molecular Biology
  • Neurosciences
  • Psychiatry
  • Neurosciences & Neurology
  • BIOCHEMISTRY & MOLECULAR BIOLOGY
  • NEUROSCIENCES
  • PSYCHIATRY, SCI
  • autism
  • chromosomal microarray
  • copy number variant
  • deletion
  • duplication
  • pathogenic
  • HIDDEN-MARKOV MODEL
  • SNP GENOTYPING DATA
  • SPECTRUM DISORDERS
  • CHROMOSOME 16P11.2
  • GENETICS
  • GENOME
  • SCHIZOPHRENIA
  • ABNORMALITIES
  • DUPLICATIONS
  • DELETIONS

Using large clinical data sets to infer pathogenicity for rare copy number variants in autism cohorts

Tools:

Journal Title:

Molecular Psychiatry

Volume:

Volume 18, Number 10

Publisher:

, Pages 1090-1095

Type of Work:

Article | Final Publisher PDF

Abstract:

Copy number variants (CNVs) have a major role in the etiology of autism spectrum disorders (ASD), and several of these have reached statistical significance in case-control analyses. Nevertheless, current ASD cohorts are not large enough to detect very rare CNVs that may be causative or contributory (that is, risk alleles). Here, we use a tiered approach, in which clinically significant CNVs are first identified in large clinical cohorts of neurodevelopmental disorders (including but not specific to ASD), after which these CNVs are then systematically identified within well-characterized ASD cohorts. We focused our initial analysis on 48 recurrent CNVs (segmental duplication-mediated 'hotspots') from 24 loci in 31 516 published clinical cases with neurodevelopmental disorders and 13 696 published controls, which yielded a total of 19 deletion CNVs and 11 duplication CNVs that reached statistical significance. We then investigated the overlap of these 30 CNVs in a combined sample of 3955 well-characterized ASD cases from three published studies. We identified 73 deleterious recurrent CNVs, including 36 deletions from 11 loci and 37 duplications from seven loci, for a frequency of 1 in 54; had we considered the ASD cohorts alone, only 58 CNVs from eight loci (24 deletions from three loci and 34 duplications from five loci) would have rea ched statistical significance. In conclusion, until there are sufficiently large ASD research cohorts with enough power to detect very rare causative or contributory CNVs, data from larger clinical cohorts can be used to infer the likely clinical significance of CNVs in ASD.

Copyright information:

© 2013 Macmillan Publishers Limited All rights reserved.

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommerical-NoDerivs 3.0 Unported License (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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