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

• Published in: BMC genetics Vol. 15; no. 1; p. 82
• Main Authors: Qiao, Ying, Mercier, Eloi, Dastan, Jila, Hurlburt, Jane, McGillivray, Barbara, Chudley, Albert E, Farrell, Sandra, Bernier, Francois P, Lewis, ME Suzanne, Pavlidis, Paul, Rajcan-Separovic, Evica
• Format: Journal Article
• Language: English
• Published: London BioMed Central 16.07.2014
• Subjects: Autism; Bioinformatics; Biomedical and Life Sciences; Biomedicine; Children & youth; Clinical-Molecular Genetics and Cytogenetics; Comparative Genomic Hybridization; Cytogenetics; Data analysis; Databases, Genetic; DNA Copy Number Variations; Gene Function; Genes; Genetic Association Studies; Genetic Variation; Genetics; Genomes; Genotype & phenotype; Human Genetics; Humans; Intellectual Disability - genetics; Medical research; Ontology; Phenotype; Research Article; Studies; Womens health; Clustering of phenotypes; Intellectual disability (ID); Phenotype/genotype analysis; Copy number variants (CNVs)
• ISSN: 1471-2350; 1471-2156; 1471-2350; 1471-2156
• DOI: 10.1186/1471-2350-15-82

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.