Dataset Information

Copy number variation in Williams-Beuren syndrome: suitable diagnostic strategy for developing countries.

ABSTRACT: BACKGROUND: Williams-Beuren syndrome (WBS; OMIM 194050) is caused by a hemizygous contiguous gene microdeletion at 7q11.23. Supravalvular aortic stenosis (SVAS), mental retardation, and overfriendliness comprise typical symptoms of WBS. Although fluorescence in situ hybridization (FISH) is considered the gold standard technique, the microsatellite DNA markers and multiplex ligation-dependent probe amplification (MLPA) could be used for to confirm the diagnosis of WBS. RESULTS: We have evaluated a total cohort of 88 patients with a suspicion clinical diagnosis of WBS using a collection of five markers (D7S1870, D7S489, D7S613, D7S2476, and D7S489_A) and a commercial MLPA kit (P029). The microdeletion was present in 64 (72.7%) patients and absent in 24 (27.3%) patients. The parental origin of deletion was maternal in 36 of 64 patients (56.3%) paternal in 28 of 64 patients (43.7%). The deletion size was 1.55 Mb in 57 of 64 patients (89.1%) and 1.84 Mb in 7 of 64 patients (10.9%). The results were concordant using both techniques, except for four patients whose microsatellite markers were uninformative. There were no clinical differences in relation to either the size or parental origin of the deletion. CONCLUSION: MLPA was considered a faster and more economical method in a single assay, whereas the microsatellite markers could determine both the size and parental origin of the deletion in WBS. The microsatellite marker and MLPA techniques are effective in deletion detection in WBS, and both methods provide a useful diagnostic strategy mainly for developing countries.

SUBMITTER: Dutra RL

PROVIDER: S-EPMC3285034 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Copy number variation in Williams-Beuren syndrome: suitable diagnostic strategy for developing countries.

Dutra Roberta L RL Honjo Rachel S RS Kulikowski Leslie D LD Fonseca Fernanda M FM Pieri Patrícia C PC Jehee Fernanda S FS Bertola Debora R DR Kim Chong A CA

BMC research notes 20120109

<h4>Background</h4>Williams-Beuren syndrome (WBS; OMIM 194050) is caused by a hemizygous contiguous gene microdeletion at 7q11.23. Supravalvular aortic stenosis (SVAS), mental retardation, and overfriendliness comprise typical symptoms of WBS. Although fluorescence in situ hybridization (FISH) is considered the gold standard technique, the microsatellite DNA markers and multiplex ligation-dependent probe amplification (MLPA) could be used for to confirm the diagnosis of WBS.<h4>Results</h4>We ha ...[more]

PMID: 22226172

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Project description:OBJECTIVE:Copy number variations (CNVs) represent a significant genetic risk for several neurodevelopmental disorders including epilepsy. As knowledge increases, reanalysis of existing data is essential. Reliable estimates of the contribution of CNVs to epilepsies from sizeable populations are not available. METHODS:We assembled a cohort of 1255 patients with preexisting array comparative genomic hybridization or single nucleotide polymorphism array based CNV data. All patients had "epilepsy plus," defined as epilepsy with comorbid features, including intellectual disability, psychiatric symptoms, and other neurological and nonneurological features. CNV classification was conducted using a systematic filtering workflow adapted to epilepsy. RESULTS:Of 1097 patients remaining after genetic data quality control, 120 individuals (10.9%) carried at least one autosomal CNV classified as pathogenic; 19 individuals (1.7%) carried at least one autosomal CNV classified as possibly pathogenic. Eleven patients (1%) carried more than one (possibly) pathogenic CNV. We identified CNVs covering recently reported (HNRNPU) or emerging (RORB) epilepsy genes, and further delineated the phenotype associated with mutations of these genes. Additional novel epilepsy candidate genes emerge from our study. Comparing phenotypic features of pathogenic CNV carriers to those of noncarriers of pathogenic CNVs, we show that patients with nonneurological comorbidities, especially dysmorphism, were more likely to carry pathogenic CNVs (odds ratio = 4.09, confidence interval = 2.51-6.68; P = 2.34 × 10-9 ). Meta-analysis including data from published control groups showed that the presence or absence of epilepsy did not affect the detected frequency of CNVs. SIGNIFICANCE:The use of a specifically adapted workflow enabled identification of pathogenic autosomal CNVs in 10.9% of patients with epilepsy plus, which rose to 12.7% when we also considered possibly pathogenic CNVs. Our data indicate that epilepsy with comorbid features should be considered an indication for patients to be selected for a diagnostic algorithm including CNV detection. Collaborative large-scale CNV reanalysis leads to novel declaration of pathogenicity in unexplained cases and can promote discovery of promising candidate epilepsy genes.

Project description:BackgroundDetection of copy number variation (CNV) in genes associated with disease is important in genetic diagnostics, and next generation sequencing (NGS) technology provides data that can be used for CNV detection. However, CNV detection based on NGS data is in general not often used in diagnostic labs as the data analysis is challenging, especially with data from targeted gene panels. Wet lab methods like MLPA (MRC Holland) are widely used, but are expensive, time consuming and have gene-specific limitations. Our aim has been to develop a bioinformatic tool for CNV detection from NGS data in medical genetic diagnostic samples.ResultsOur computational pipeline for detection of CNVs in NGS data from targeted gene panels utilizes coverage depth of the captured regions and calculates a copy number ratio score for each region. This is computed by comparing the mean coverage of the sample with the mean coverage of the same region in other samples, defined as a pool. The pipeline selects pools for comparison dynamically from previously sequenced samples, using the pool with an average coverage depth that is nearest to the one of the samples. A sliding window-based approach is used to analyze each region, where length of sliding window and sliding distance can be chosen dynamically to increase or decrease the resolution. This helps in detecting CNVs in small or partial exons. With this pipeline we have correctly identified the CNVs in 36 positive control samples, with sensitivity of 100% and specificity of 91%. We have detected whole gene level deletion/duplication, single/multi exonic level deletion/duplication, partial exonic deletion and mosaic deletion. Since its implementation in mid-2018 it has proven its diagnostic value with more than 45 CNV findings in routine tests.ConclusionsWith this pipeline as part of our diagnostic practices it is now possible to detect partial, single or multi-exonic, and intragenic CNVs in all genes in our target panel. This has helped our diagnostic lab to expand the portfolio of genes where we offer CNV detection, which previously was limited by the availability of MLPA kits.

Dataset Information

Copy number variation in Williams-Beuren syndrome: suitable diagnostic strategy for developing countries.

Publications

Copy number variation in Williams-Beuren syndrome: suitable diagnostic strategy for developing countries.

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