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A copy number variation morbidity map of developmental delay

A Corrigendum to this article was published on 01 September 2014

A Corrigendum to this article was published on 01 September 2014

This article has been updated

Abstract

To understand the genetic heterogeneity underlying developmental delay, we compared copy number variants (CNVs) in 15,767 children with intellectual disability and various congenital defects (cases) to CNVs in 8,329 unaffected adult controls. We estimate that 14.2% of disease in these children is caused by CNVs >400 kb. We observed a greater enrichment of CNVs in individuals with craniofacial anomalies and cardiovascular defects compared to those with epilepsy or autism. We identified 59 pathogenic CNVs, including 14 new or previously weakly supported candidates, refined the critical interval for several genomic disorders, such as the 17q21.31 microdeletion syndrome, and identified 940 candidate dosage-sensitive genes. We also developed methods to opportunistically discover small, disruptive CNVs within the large and growing diagnostic array datasets. This evolving CNV morbidity map, combined with exome and genome sequencing, will be critical for deciphering the genetic basis of developmental delay, intellectual disability and autism spectrum disorders.

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Figure 1: CNV size distributions in affected and unaffected individuals.
Figure 2: Maps of CNV locations for chromosomes 15 and 17.
Figure 3: Discovery of new microdeletions associated with genomic disorders.
Figure 4: Discovery of new, exon-altering CNVs using the Signature CGH data.

Change history

  • 27 August 2014

    In the version of this article initially published, in Table 1 and its associated text, there was a calculation error in which the relative sizes of the case and control populations were set to be equal; because the size of the case population (15,767) was nearly double that of the control population (8,329), this resulted in erroneously inflated penetrance estimates. A simple definition of penetrance is used that is often applied in medical genetics—namely, the proportion of observed mutation carriers that are affected—to provide a metric that would be useful to clinical geneticists in a setting in which disease is heavily enriched, for example, in diagnosing children with developmental delay. That formulation is biased upwards with respect to population-level penetrance. Thus, in this corrigendum, an estimate more appropriate for population-level inference is provided assuming a general disease prevalence of 5.3% (Am. J. Hum. Genet. 42, 677–693, 1988) along with the more familiar odds ratio (OR) estimate. Importantly, all of these measures of penetrance are intrinsically limited by sampling error and imprecision in defining disease prevalence. We note that the mutation carrier counts, P values and other results in the original version of Table 1 are correct, and the key results and conclusions of the paper are unaffected. The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

We thank N. Krumm, M. Malig, L. Vives and J. Luu for assistance in validation experiments. We also thank M. Dennis, C. Alkan, E. Karakoc and T. Brown for useful discussions and for editing the manuscript. B.P.C. is supported by a fellowship from the Canadian Institutes of Health Research. This study makes use of data generated by the Wellcome Trust Case Control Consortium. A full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk/. Funding for the project was provided by the Wellcome Trust under awards 076113 and 085475. We also thank A. Aragaki, C. Kooperberg and R. Jackson for access to SNP data (Fred Hutchinson Cancer Research Center (FHCRC) control dataset) generated as part of the ongoing genome-wide association study to identify genetic components of hip fracture in the Women's Health Initiative. This work was supported by US National Institutes of Health HD065285 to E.E.E. E.E.E. is an investigator of the Howard Hughes Medical Institute.

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Authors

Contributions

G.M.C., B.P.C., S.G., E.E.E., J.A.R., B.C.B. and L.G.S. designed the study. L.G.S. supervised array-CGH experiments at Signature Genomics. J.A.R. and B.C.B. coordinated clinical data collection. G.M.C. and B.P.C. performed data analysis and curated control CNV data. S.G. curated genomic disorders data. S.G., T.H.V. and C.B. performed array CGH and PCR validations. C.W., H.S., R.H., V.H., H.A.-H., P.B., E.M., D.N., K.L., H.T., M.H., N.A., J.G., J.K., V.S., K.J. and C.R. provided clinical information. G.M.C., B.P.C., S.G. and E.E.E. wrote the manuscript. All authors have read and approved the final version of the manuscript.

Corresponding author

Correspondence to Evan E Eichler.

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Competing interests

E.E.E. is a member of the Scientific Advisory Board of Pacific Biosciences. J.A.R., B.C.B. and L.G.S. are employees of PerkinElmer.

Supplementary information

Supplementary Text and Figures

Supplementary Tables 2–11, Supplementary Figures 1–13 and Supplementary Note. (PDF 3185 kb)

Supplementary Table 1

Phenotype by sample (XLSX 683 kb)

Supplementary Table 12

Gene level statistics (XLSX 5069 kb)

Supplementary Table 13

Control CNV burden by gene (XLSX 2814 kb)

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Cooper, G., Coe, B., Girirajan, S. et al. A copy number variation morbidity map of developmental delay. Nat Genet 43, 838–846 (2011). https://doi.org/10.1038/ng.909

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