A critical review of the impact of candidate copy number variants on autism spectrum disorder

Seyedeh Sedigheh Abedini; Shiva Akhavantabasi; Yuheng Liang; Julian Ik-Tsen Heng; Roohallah Alizadehsani; Iman Dehzangi; Denis C Bauer; Hamid Alinejad-Rokny

doi:10.1016/j.mrrev.2024.108509

A critical review of the impact of candidate copy number variants on autism spectrum disorder

Mutat Res Rev Mutat Res. 2024 Jul 6:794:108509. doi: 10.1016/j.mrrev.2024.108509. Online ahead of print.

Authors

Seyedeh Sedigheh Abedini¹, Shiva Akhavantabasi², Yuheng Liang³, Julian Ik-Tsen Heng⁴, Roohallah Alizadehsani⁵, Iman Dehzangi⁶, Denis C Bauer⁷, Hamid Alinejad-Rokny⁸

Affiliations

¹ UNSW BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia; School of Biotechnology & Biomolecular Sciences, UNSW Sydney, Sydney, NSW 2052, Australia.
² Department of Molecular Biology and Genetics, Yeni Yuzyil University, Istanbul, Turkey; Ghiaseddin Jamshid Kashani University, Andisheh University Town, Danesh Blvd, 3441356611, Abyek, Qazvin, Iran.
³ UNSW BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.
⁴ Curtin Health Innovation Research Institute, Curtin University, Bentley 6845, Australia.
⁵ Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Victoria, Australia.
⁶ Center for Computational and Integrative Biology, Rutgers University, Camden, NJ 08102, USA; Department of Computer Science, Rutgers University, Camden, NJ 08102, USA.
⁷ Transformational Bioinformatics, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, Australia; Applied BioSciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, Australia.
⁸ UNSW BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia; Tyree Institute of Health Engineering (IHealthE), UNSW Sydney, Sydney, NSW 2052, Australia. Electronic address: h.alinejad@unsw.edu.au.

PMID: 38977176
DOI: 10.1016/j.mrrev.2024.108509

Abstract

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder (NDD) influenced by genetic, epigenetic, and environmental factors. Recent advancements in genomic analysis have shed light on numerous genes associated with ASD, highlighting the significant role of both common and rare genetic mutations, as well as copy number variations (CNVs), single nucleotide polymorphisms (SNPs) and unique de novo variants. These genetic variations disrupt neurodevelopmental pathways, contributing to the disorder's complexity. Notably, CNVs are present in 10 %-20 % of individuals with autism, with 3 %-7 % detectable through cytogenetic methods. While the role of submicroscopic CNVs in ASD has been recently studied, their association with genomic loci and genes has not been thoroughly explored. In this review, we focus on 47 CNV regions linked to ASD, encompassing 1632 genes, including protein-coding genes and long non-coding RNAs (lncRNAs), of which 659 show significant brain expression. Using a list of ASD-associated genes from SFARI, we detect 17 regions harboring at least one known ASD-related protein-coding gene. Of the remaining 30 regions, we identify 24 regions containing at least one protein-coding gene with brain-enriched expression and a nervous system phenotype in mouse mutants, and one lncRNA with both brain-enriched expression and upregulation in iPSC to neuron differentiation. This review not only expands our understanding of the genetic diversity associated with ASD but also underscores the potential of lncRNAs in contributing to its etiology. Additionally, the discovered CNVs will be a valuable resource for future diagnostic, therapeutic, and research endeavors aimed at prioritizing genetic variations in ASD.

Keywords: Autism spectrum disorder; CNV; Copy number variants; Gene expression; Integrative analysis; LncRNA.

Publication types

Review