Dataset Information

New insights in the interpretation of array-CGH: autism spectrum disorder and positive family history for intellectual disability predict the detection of pathogenic variants.

ABSTRACT:

Background

Array-CGH (aCGH) is presently used into routine clinical practice for diagnosis of patients with intellectual disability (ID), multiple congenital anomalies (MCA), and autism spectrum disorder (ASD). ACGH could detect small chromosomal imbalances, copy number variations (CNVs), and closely define their size and gene content. ACGH detects pathogenic imbalances in 14-20 % of patients with ID. The aims of this study were: to establish clinical clues potentially associated with pathogenic CNVs and to identify cytogenetic indicators to predict the pathogenicity of the variants of uncertain significance (VOUS) in a large cohort of paediatric patients.

Methods

We enrolled 214 patients referred for either: ID, and/or ASD and/or MCA to genetic services at the Federico II University of Naples, Department of Translational Medicine. For each patient we collected clinical and imaging data. All the patients were tested with aCGH or as first-tier test or as part of a wider diagnostic work-up.

Results

Pathologic data were detected in 65 individuals (30 %) and 46 CNVs revealed a known syndrome. The pathological CNVs were usually deletions showing the highest gene-dosage content. The positive family history for ID/ASD/MCA and ASD were good indicators for detecting pathological chromosomal rearrangements. Other clinical features as eyes anomalies, hearing loss, neurological signs, cutaneous dyscromia and endocrinological problems seem to be potential predictors of pathological CNVs. Among patients carrying VOUS we analyzed genetic features including CNVs size, presence of deletion or duplication, genic density, multiple CNVs, to clinical features. Higher gene density was found in patients affected by ID. This result suggest that higher gene content has more chances to include pathogenic gene involved and causing ID in these patients.

Conclusion

Our study suggest the use of aCGH as first-tier test in patients with neurdevelopmental phenotypes. The inferred results have been used for building a flow-chart to be applied for children with ID.

SUBMITTER: Cappuccio G

PROVIDER: S-EPMC4830019 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Publications

New insights in the interpretation of array-CGH: autism spectrum disorder and positive family history for intellectual disability predict the detection of pathogenic variants.

Cappuccio Gerarda G Vitiello Francesco F Casertano Alberto A Fontana Paolo P Genesio Rita R Bruzzese Dario D Ginocchio Virginia Maria VM Mormile Angela A Nitsch Lucio L Andria Generoso G Melis Daniela D

Italian journal of pediatrics 20160412

<h4>Background</h4>Array-CGH (aCGH) is presently used into routine clinical practice for diagnosis of patients with intellectual disability (ID), multiple congenital anomalies (MCA), and autism spectrum disorder (ASD). ACGH could detect small chromosomal imbalances, copy number variations (CNVs), and closely define their size and gene content. ACGH detects pathogenic imbalances in 14-20 % of patients with ID. The aims of this study were: to establish clinical clues potentially associated with pa ...[more]

PMID: 27072107

Similar Datasets

Project description:UNLABELLED: BACKGROUND: Array comparative genomic hybridization (CGH) has been repeatedly shown to be a successful tool for the identification of genomic variations in a clinical population. During the last decade, the implementation of array CGH has resulted in the identification of new causative submicroscopic chromosome imbalances and copy number variations (CNVs) in neuropsychiatric (neurobehavioral) diseases. Currently, array-CGH-based technologies have become an integral part of molecular diagnosis and research in individuals with neuropsychiatric disorders and children with intellectual disability (mental retardation) and congenital anomalies. Here, we introduce the Russian cohort of children with intellectual disability, autism, epilepsy and congenital anomalies analyzed by BAC array CGH and a novel bioinformatic strategy. RESULTS: Among 54 individuals highly selected according to clinical criteria and molecular and cytogenetic data (from 2426 patients evaluated cytogenetically and molecularly between November 2007 and May 2012), chromosomal imbalances were detected in 26 individuals (48%). In two patients (4%), a previously undescribed condition was observed. The latter has been designated as meiotic (constitutional) genomic instability resulted in multiple submicroscopic rearrangements (including CNVs). Using bioinformatic strategy, we were able to identify clinically relevant CNVs in 15 individuals (28%). Selected cases were confirmed by molecular cytogenetic and molecular genetic methods. Eight out of 26 chromosomal imbalances (31%) have not been previously reported. Among them, three cases were co-occurrence of subtle chromosome 9 and 21 deletions. CONCLUSIONS: We conducted an array CGH study of Russian patients suffering from intellectual disability, autism, epilepsy and congenital anomalies. In total, phenotypic manifestations of clinically relevant genomic variations were found to result from genomic rearrangements affecting 1247 disease-causing and pathway-involved genes. Obviously, a significantly lesser part of them are true candidates for intellectual disability, autism or epilepsy. The success of our preliminary array CGH and bioinformatic study allows us to expand the cohort. According to the available literature, this is the first comprehensive array CGH evaluation of a Russian cohort of children with neuropsychiatric disorders and congenital anomalies.

Dataset Information

New insights in the interpretation of array-CGH: autism spectrum disorder and positive family history for intellectual disability predict the detection of pathogenic variants.

Background

Methods

Results

Conclusion

Publications

New insights in the interpretation of array-CGH: autism spectrum disorder and positive family history for intellectual disability predict the detection of pathogenic variants.

Similar Datasets

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