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Multiple Genetic Rare Variants in Autism Spectrum Disorders: A Single-Center Targeted NGS Study

Authors :
Andrea Legati
Sara Bulgheroni
Barbara Garavaglia
Valeria Tessarollo
Chiara Pantaleoni
Daria Riva
Silvia Annunziata
Stefano D'Arrigo
Chiara Reale
Source :
Applied Sciences, Vol 11, Iss 8096, p 8096 (2021), Applied Sciences, Volume 11, Issue 17
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Many studies based on chromosomal microarray and next-generation sequencing (NGS) have identified hundreds of genes associated with autism spectrum disorder (ASD) risk, demonstrating that there are several complex genetic factors that contribute to ASD risk. We performed targeted NGS gene panels for 120 selected genes, in a clinical population of 40 children with well-characterized ASD. The variants identified were annotated and filtered, focusing on rare variants with a minimum allele frequency &lt<br />1% in GnomAD. We found 147 variants in 39 of the 40 patients. It was possible to perform family segregation analysis in 28 of the 40 patients. We found 4 de novo and 101 inherited variants. For the inherited variants, we observed that all the variants identified in the patients came equally from the paternal and maternal genetic makeup. We identified 9 genes that are more frequently mutated than the others, and upon comparing the mutational frequency of these 9 genes in our cohort and the mutational frequency in the GnomAD population, we found significantly increased frequencies of rare variants in our study population. This study supports the hypothesis that ASD is the result of a combination of rare deleterious variants (low contribution) and many low-risk alleles (genetic background), highlighting the importance of MET and SLIT3 and the potentially stronger involvement of FAT1 and VPS13B in ASD. Taken together, our findings reinforce the importance of using gene panels to understand the contribution of the different genes already associated with ASD in the pathogenesis of the disease.

Details

Language :
English
ISSN :
20763417
Volume :
11
Issue :
8096
Database :
OpenAIRE
Journal :
Applied Sciences
Accession number :
edsair.doi.dedup.....3f4b925442deb2a7a5ab0bfb288af32a