The genetic landscape of autism spectrum disorder in the Middle Eastern population

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Abstract

Introduction: Autism spectrum disorder (ASD) is characterized by aberrations in social interaction and communication associated with repetitive behaviors and interests, with strong clinical heterogeneity. Genetic factors play an important role in ASD, but about 75% of ASD cases have an undetermined genetic risk.

Methods: We extensively investigated an ASD cohort made of 102 families from the Middle Eastern population of Qatar. First, we investigated the copy number variations (CNV) contribution using genome-wide SNP arrays. Next, we employed Next Generation Sequencing (NGS) to identify de novo or inherited variants contributing to the ASD etiology and its associated comorbid conditions in families with complete trios (affected child and the parents).

Results: Our analysis revealed 16 CNV regions located in genomic regions implicated in ASD. The analysis of the 88 ASD cases identified 41 genes in 39 ASD subjects with de novo (n = 24) or inherited variants (n = 22). We identified three novel de novo variants in new candidate genes for ASD ( DTX4, ARMC6, and B3GNT3). Also, we have identified 15 de novo variants in genes that were previously implicated in ASD or related neurodevelopmental disorders ( PHF21A, WASF1, TCF20, DEAF1, MED13, CREBBP, KDM6B, SMURF1, ADNP, CACNA1G, MYT1L, KIF13B, GRIA2, CHM, and KCNK9). Additionally, we defined eight novel recessive variants ( RYR2, DNAH3, TSPYL2, UPF3B KDM5C, LYST, and WNK3), four of which were X-linked.

Conclusion: Despite the ASD multifactorial etiology that hinders ASD genetic risk discovery, the number of identified novel or known putative ASD genetic variants was appreciable. Nevertheless, this study represents the first comprehensive characterization of ASD genetic risk in Qatar's Middle Eastern population.

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PLINK: a tool set for whole-genome association and population-based linkage analyses.

Shaun Purcell, Benjamin M. Neale, Kathe Todd-Brown … (2007)

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

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The mutational constraint spectrum quantified from variation in 141,456 humans

Konrad J. Karczewski, Laurent C. Francioli, Grace Tiao … (2021)

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

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Second-generation PLINK: rising to the challenge of larger and richer datasets

Christopher Chang, Carson Chow, Laurent Tellier … (2015)

PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for even faster and more scalable implementations of key functions. In addition, GWAS and population-genetic data now frequently contain probabilistic calls, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, O(sqrt(n))-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. This will be followed by PLINK 2.0, which will introduce (a) a new data format capable of efficiently representing probabilities, phase, and multiallelic variants, and (b) extensions of many functions to account for the new types of information. The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.

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Author and article information

Contributors

Yasser Al-Sarraj: URI : https://loop.frontiersin.org/people/1021511/overviewRole: Role: Role: Role: Role: Role: Role:

Rowaida Z. Taha: URI : https://loop.frontiersin.org/people/1829604/overviewRole: Role: Role: Role:

Eman Al-Dous: Role: Role: Role:

Dina Ahram: Role: Role: Role:

Somayyeh Abbasi: Role: Role: Role:

Eman Abuazab: Role: Role: Role:

Hibah Shaath: URI : https://loop.frontiersin.org/people/999696/overviewRole: Role: Role:

Wesal Habbab: Role: Role: Role:

Khaoula Errafii‬: Role: Role: Role:

Yosra Bejaoui: URI : https://loop.frontiersin.org/people/531769/overviewRole: Role: Role:

Maryam AlMotawa: URI : https://loop.frontiersin.org/people/1074471/overviewRole: Role: Role:

Namat Khattab: Role: Role: Role:

Yasmin Abu Aqel: Role: Role: Role:

Karim E. Shalaby: Role: Role: Role:

Amina Al-Ansari: Role: Role: Role:

Marios Kambouris: URI : https://loop.frontiersin.org/people/910757/overviewRole: Role: Role:

Adel Abouzohri: Role: Role: Role:

Iman Ghazal: URI : https://loop.frontiersin.org/people/2543049/overviewRole: Role: Role:

Mohammed Tolfat: Role: Role: Role:

Fouad Alshaban: URI : https://loop.frontiersin.org/people/2392050/overviewRole: Role: Role:

Hatem El-Shanti: URI : https://loop.frontiersin.org/people/1835693/overviewRole: Role: Role: Role: Role:

Omar M. E. Albagha: URI : https://loop.frontiersin.org/people/40172/overviewRole: Role: Role: Role: Role: Role: Role:

Journal

Journal ID (nlm-ta): Front Genet

Journal ID (iso-abbrev): Front Genet

Journal ID (publisher-id): Front. Genet.

Title: Frontiers in Genetics

Publisher: Frontiers Media S.A.

ISSN (Electronic): 1664-8021

Publication date (Electronic): 20 March 2024

Publication date Collection: 2024

Volume: 15

Electronic Location Identifier: 1363849

Affiliations

[1] ¹ College of Health and Life Sciences , Hamad Bin Khalifa University , Doha, Qatar

[2] ² Qatar Biomedical Research Institute (QBRI) , Hamad Bin Khalifa University , Doha, Qatar

[3] ³ Qatar Genome Program , Qatar Foundation Research , Development and Innovation , Qatar Foundation , Doha, Qatar

[4] ⁴ Quest Diagnostics Nichols Institute , San Juan Capistrano, CA, United States

[5] ⁵ Pathology & Laboratory Medicine Department , Genetics Division , Sidra Medicine , Doha, Qatar

[6] ⁶ The Shafallah Center for Children with Special Needs , Doha, Qatar

[7] ⁷ Department of Pediatrics , Carver College of Medicine , University of Iowa , Iowa City, IA, United States

Author notes

Edited by: Mehdi Pirooznia, Johnson & Johnson, United States

Reviewed by: Sheng Wang, University of California, San Francisco, United States

Yonatan Perez, University of California, San Francisco, United States

Boting Ning, Johnson & Johnson, United States

*Correspondence: Yasser Al-Sarraj, yalsarraj@ 123456qf.org.qa ; Omar M. E. Albagha, oalbagha@ 123456hbku.edu.qa

Article

Publisher ID: 1363849

DOI: 10.3389/fgene.2024.1363849

PMC ID: 10987745

PubMed ID: 38572415

SO-VID: 0d6e1006-e921-48c0-8c30-50ef2cc15f56

Copyright © Copyright © 2024 Al-Sarraj, Taha, Al-Dous, Ahram, Abbasi, Abuazab, Shaath, Habbab, Errafii‬, Bejaoui, AlMotawa, Khattab, Aqel, Shalaby, Al-Ansari, Kambouris, Abouzohri, Ghazal, Tolfat, Alshaban, El-Shanti and Albagha.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

History

Date received : 31 December 2023

Date accepted : 04 March 2024

Funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research was funded by start-up grants to OA. from the college of health and life sciences and the Qatar Biomedical Research Institute at Hamad Bin Khalifa University. YA. and EA. are supported by a Ph.D. scholarship from Hamad Bin Khalifa University. The recruitment of patients was initiated by funds from Shafallah Medical Genetics Center and the Shafallah Center for Children with Special Needs. The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of Qatar Biomedical Research Institute (Protocol No.010-002). (As an extension from the IRB of Shafallah).

Custom metadata

section-at-acceptance Genetics of Common and Rare Diseases

ScienceOpen disciplines: Genetics

Keywords: autism spectrum disorder (asd),neurodevelopmental disorders,epilepsy,next-generation sequencing (ngs),copy number variation (cnv), de novo mutation,genetics

Data availability:

ScienceOpen disciplines: Genetics

Keywords: autism spectrum disorder (asd), neurodevelopmental disorders, epilepsy, next-generation sequencing (ngs), copy number variation (cnv), de novo mutation, genetics

The genetic landscape of autism spectrum disorder in the Middle Eastern population

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Genomic Prediction

Most cited references 155

PLINK: a tool set for whole-genome association and population-based linkage analyses.

The mutational constraint spectrum quantified from variation in 141,456 humans

Second-generation PLINK: rising to the challenge of larger and richer datasets

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