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Updated: Jun 7, 2025

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants
Published on: February 21, 2015
Copy Number Variants in 30 Saudi Pediatric Patients with Neurodevelopmental Disorders: From Unknown Significance to
Raniah Saleem Alotibi1,2, Mariam M Al Eissa3,4, Taghrid Aloraini5,6
1Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
Background:
Structural variants (SVs), such as copy number variants (CNVs), insertions, deletions, inversions, and translocations, contribute significantly to genetic diversity and disease etiology. CNVs, which involve the duplication or deletion of DNA segments, are particularly impactful on genes crucial for biological functions and disease processes.
Objective:
To reassess unclassified SVs that may be underlying unresolved neurodevelopmental disorders among Saudi patients.
Methodology:
In this retrospective study conducted at King Saud Medical City, Riyadh, Saudi Arabia, 30 probands with neurodevelopmental disorders and congenital malformations were examined using next-generation sequencing methods-exome sequencing, gene panels, or SNP arrays (the Illumina platform). Reclassification was aided by online tools such as VarSome and ClinVar, with pathogenicity assessments using the ClinGen CNV Pathogenicity Calculator based on American College of Medical Genetics and Genomics criteria for CNV loss and gain, and dosage sensitivity.
Results:
A total of 31 CNVs were analyzed, of which 2 were reclassified: one as benign and the other as pathogenic. The pathogenic CNV, [3p13p12.3 (70411134_75249376) x1], included a deletion of the FOXP1 gene and was associated with an intellectual developmental disorder, language impairment, possible autistic features, psychomotor impairment, developmental regression, and epilepsy.
Conclusion:
This study underscores the importance of continuously documenting and revisiting unclassified CNVs in accessible databases to enhance the diagnosis and understanding of complex genotype-phenotype relationships. Reclassifying these CNVs not only accelerates diagnostic processes but also enriches our insight into their significant roles in health and disease.
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