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Unveiling genetic insights: Array-CGH and WES discoveries in a cohort of 122 children with essential autism spectrum disorder

Authors :
Paola Granata
Alessandra Zito
Dario Cocciadiferro
Antonio Novelli
Chiara Pessina
Tommaso Mazza
Matteo Ferri
Paolo Piccinelli
Chiara Luoni
Cristiano Termine
Mauro Fasano
Rosario Casalone
Source :
BMC Genomics, Vol 25, Iss 1, Pp 1-17 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Background Autistic Spectrum Disorder (ASD) is a neurodevelopmental disorder with a strong genetic component and high heterogeneity. Essential ASD refers to patients who do not have other comorbidities. This study aimed to investigate the genetic basis of essential ASD using whole exome sequencing (WES) and array-comparative genomic hybridization (array-CGH). Results In a cohort of 122 children with essential ASD, WES detected 382 variants across 223 genes, while array-CGH identified 46 copy number variants (CNVs). The combined use of WES and array-CGH revealed pathogenic variants in four patients (3.1% detection rate) and likely pathogenic variants in 34 patients (27.8% detection rate). Only one patient had a pathogenic CNV (0.8% detection rate). Including likely pathogenic variants, the overall detection rate was 31.2%. Additionally, 33 de novo heterozygous sequence variants were identified by WES, with three classified as pathogenic and 13 as likely pathogenic. Sequence variants were found in 85 genes already associated with ASD, and 138 genes not previously included in the SFARI dataset were identified as potential new candidate genes. Conclusions The study enhances genetic understanding of essential ASD and identifies new candidate genes of interest. The findings suggest that using both array-CGH and WES in patients with essential ASD can improve the detection of pathogenic and likely pathogenic genetic variants, contributing to better diagnosis and potentially guiding future research and treatment strategies.

Details

Language :
English
ISSN :
14712164
Volume :
25
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Genomics
Publication Type :
Academic Journal
Accession number :
edsdoj.872fb87bc0864d7fb98d4d1990882c75
Document Type :
article
Full Text :
https://doi.org/10.1186/s12864-024-11077-5