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Updated: Apr 30, 2026

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants
Published on: February 21, 2015
Phenotype profiling of patients with intellectual disability and copy number variations
Mónica Roselló1, Francisco Martínez1, Sandra Monfort1
1Unidad de Genética y Diagnóstico Prenatal, Hospital Universitari i Politècnic "La Fe", Avenida Campanar 21, 46009 Valencia, Spain.
Background:
Nowadays the microarray technology allows whole-genome analysis with a high resolution and performance for the genetic diagnosis in any patient with intellectual disability or autism spectrum disorder. However in the immediate future, with the development of massive sequencing systems for application at clinical diagnosis, it will be necessary to have clinical criteria to guide studies.
Aim:
To perform an exhaustive clinical definition of patients with pathogenic copy number variations in order to establish the clinical criteria most suggestive of this kind of genomic rearrangements.
Method:
We designed and implemented a database to collect 190 different clinical variables (pregnancy, neonatal, facial dysmorphism, congenital anomalies, neurological features and family history) in a series of 246 patients, with developmental delay/intellectual disability. All cases were studied with array comparative genomic hybridization.
Results:
We have found a pathogenic genomic imbalance in 73 patients. Frequency analysis of all clinical variables showed that growth disorder, abnormalities of hands, low-set ears and hypertelorism are the more frequent features among patients with genomic rearrangements. However other clinical features, such as genital abnormalities and aggressiveness, are more specifically associated with pathogenic copy number variations in spite of their low frequencies in the overall series, yielding higher statistical significance values than other traits.
Conclusions:
The genotype-phenotype comparison may be useful to set in the future the main clinical manifestations associated with deletions, duplications and unbalanced translocations. Theses analyses will improve the clinical indications and protocols to implement genomic arrays in the genetic study of patients with neurodevelopment disorders.
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