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Open Access Research article

Copy number variants (CNVs) analysis in a deeply phenotyped cohort of individuals with intellectual disability (ID)

Ying Qiao12, Eloi Mercier3, Jila Dastan2, Jane Hurlburt2, Barbara McGillivray2, Albert E Chudley4, Sandra Farrell5, Francois P Bernier6, ME Suzanne Lewis7*, Paul Pavlidis3* and Evica Rajcan-Separovic1*

Author Affiliations

1 Department of Pathology (Cytogenetics), BC Child and Family Research Institute, University of British Columbia (UBC), 950 West 28th, Room 3060, Vancouver, BC V5Z 4H4, Canada

2 Department of Medical Genetics, BC Child and Family Research Institute, UBC, Vancouver, BC V6H 3N1, Canada

3 Centre for High-throughout Biology, 177 Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada

4 Department of Human Genetics, University of Manitoba Children’s Hospital, Winnipeg, Manitoba R3A 1R9, Canada

5 The Trillium Health Partners, 2200 Eglinton Avenue West, Mississauga, ON L5M 2N1, Canada

6 Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada

7 Department of Medical Genetics, BC Child and Family Research Institute and BC Children’s and Women’s Health Center, University of British Columbia, C234, 4500 Oak Street, Vancouver, BC V6H 3N1, Canada

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BMC Medical Genetics 2014, 15:82  doi:10.1186/1471-2350-15-82

Published: 16 July 2014

Abstract

Background

DNA copy number variants (CNVs) are found in 15% of subjects with ID but their association with phenotypic abnormalities has been predominantly studied in smaller cohorts of subjects with detailed yet non-systematically categorized phenotypes, or larger cohorts (thousands of cases) with smaller number of generalized phenotypes.

Methods

We evaluated the association of de novo, familial and common CNVs detected in 78 ID subjects with phenotypic abnormalities classified using the Winter-Baraitser Dysmorphology Database (WBDD) (formerly the London Dysmorphology Database). Terminology for 34 primary (coarse) and 169 secondary (fine) phenotype features were used to categorize the abnormal phenotypes and determine the prevalence of each phenotype in patients grouped by the type of CNV they had.

Results

In our cohort more than 50% of cases had abnormalities in primary categories related to head (cranium, forehead, ears, eye globes, eye associated structures, nose) as well as hands and feet. The median number of primary and secondary abnormalities was 12 and 18 per subject, respectively, indicating that the cohort consisted of subjects with a high number of phenotypic abnormalities (median De Vries score for the cohort was 5). The prevalence of each phenotypic abnormality was comparable in patients with de novo or familial CNVs in comparison to those with only common CNVs, although a trend for increased frequency of cranial and forehead abnormalities was noted in subjects with rare de novo and familial CNVs. Two clusters of subjects were identified based on the prevalence of each fine phenotypic feature, with an average of 28.3 and 13.5 abnormal phenotypes/subject in the two clusters respectively (P < 0.05).

Conclusions

Our study is a rare example of using standardized, deep morphologic phenotype clustering with phenotype/CNV correlation in a cohort of subjects with ID. The composition of the cohort inevitably influences the phenotype/genotype association, and our studies show that the influence of the de novo CNVs on the phenotype is less obvious in cohorts consisting of subjects with a high number of phenotypic abnormalities. The outcome of phenotype/genotype analysis also depends on the choice of phenotypes assessed and standardized phenotyping is required to minimize variability.

Keywords:
Intellectual disability (ID); Copy number variants (CNVs); Phenotype/genotype analysis; Clustering of phenotypes