Dataset Information

Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing.

ABSTRACT: Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited genetic variants predicted to be deleterious (loss-of-function and damaging missense mutations). Among ASD probands, we identified deleterious de novo mutations in six of 32 (19%) families and X-linked or autosomal inherited alterations in ten of 32 (31%) families (some had combinations of mutations). The proportion of families identified with such putative mutations was larger than has been previously reported; this yield was in part due to the comprehensive and uniform coverage afforded by WGS. Deleterious variants were found in four unrecognized, nine known, and eight candidate ASD risk genes. Examples include CAPRIN1 and AFF2 (both linked to FMR1, which is involved in fragile X syndrome), VIP (involved in social-cognitive deficits), and other genes such as SCN2A and KCNQ2 (linked to epilepsy), NRXN1, and CHD7, which causes ASD-associated CHARGE syndrome. Taken together, these results suggest that WGS and thorough bioinformatic analyses for de novo and rare inherited mutations will improve the detection of genetic variants likely to be associated with ASD or its accompanying clinical symptoms.

SUBMITTER: Jiang YH

PROVIDER: S-EPMC3738824 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing.

Jiang Yong-hui YH Yuen Ryan K C RK Jin Xin X Wang Mingbang M Chen Nong N Wu Xueli X Ju Jia J Mei Junpu J Shi Yujian Y He Mingze M Wang Guangbiao G Liang Jieqin J Wang Zhe Z Cao Dandan D Carter Melissa T MT Chrysler Christina C Drmic Irene E IE Howe Jennifer L JL Lau Lynette L Marshall Christian R CR Merico Daniele D Nalpathamkalam Thomas T Thiruvahindrapuram Bhooma B Thompson Ann A Uddin Mohammed M Walker Susan S Luo Jun J Anagnostou Evdokia E Zwaigenbaum Lonnie L Ring Robert H RH Wang Jian J Lajonchere Clara C Wang Jun J Shih Andy A Szatmari Peter P Yang Huanming H Dawson Geraldine G Li Yingrui Y Scherer Stephen W SW

American journal of human genetics 20130711 2

Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited geneti ...[more]

PMID: 23849776

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Project description:Human genetic studies have implicated more than a hundred genes in Autism Spectrum Disorder (ASD). Understanding how variation in implicated genes influence expression of co-occurring conditions and drug response can inform more effective, personalized approaches for treatment of individuals with ASD. Rapidly translating this information into the clinic requires efficient algorithms to sort through the myriad of genes implicated by rare gene-damaging single nucleotide and copy number variants, and common variation detected in genome-wide association studies (GWAS). To pinpoint genes that are more likely to have clinically relevant variants, we developed a functional annotation pipeline. We defined clinical relevance in this project as any ASD associated gene with evidence indicating a patient may have a complex, co-occurring condition that requires direct intervention (e.g., sleep and gastrointestinal disturbances, attention deficit hyperactivity, anxiety, seizures, depression), or is relevant to drug development and/or approaches to maximizing efficacy and minimizing adverse events (i.e., pharmacogenomics). Starting with a list of all candidate genes implicated in all manifestations of ASD (i.e., idiopathic and syndromic), this pipeline uses databases that represent multiple lines of evidence to identify genes: (1) expressed in the human brain, (2) involved in ASD-relevant biological processes and resulting in analogous phenotypes in mice, (3) whose products are targeted by approved pharmaceutical compounds or possessing pharmacogenetic variation and (4) whose products directly interact with those of genes with variants recommended to be tested for by the American College of Medical Genetics (ACMG). Compared with 1000 gene sets, each with a random selection of human protein coding genes, more genes in the ASD set were annotated for each category evaluated (p ≤ 1.99 × 10-2). Of the 956 ASD-implicated genes in the full set, 18 were flagged based on evidence in all categories. Fewer genes from randomly drawn sets were annotated in all categories (x = 8.02, sd = 2.56, p = 7.75 × 10-4). Notably, none of the prioritized genes are represented among the 59 genes compiled by the ACMG, and 78% had a pathogenic or likely pathogenic variant in ClinVar. Results from this work should rapidly prioritize potentially actionable results from genetic studies and, in turn, inform future work toward clinical decision support for personalized care based on genetic testing.

Project description:Autism spectrum disorder (ASD) is a highly heritable condition caused by a combination of environmental and genetic factors such as de novo and inherited variants, as well as rare or common variants among hundreds of related genes. Previous genome-wide association studies have identified susceptibility genes; however, most ASD-associated genes remain undiscovered. This study aimed to examine rare de novo variants to identify genetic risk factors of ASD using whole exome sequencing (WES), functional characterization, and genetic network analyses of identified variants using Korean familial dataset. We recruited children with ASD and their biological parents. The clinical best estimate diagnosis of ASD was made according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5TM), using comprehensive diagnostic instruments. The final analyses included a total of 151 individuals from 51 families. Variants were identified and filtered using the GATK Best Practices for bioinformatics analysis, followed by genome alignments and annotation to the reference genome assembly GRCh37 (liftover to GRCh38), and further annotated using dbSNP 154 build databases. To evaluate allele frequencies of de novo variants, we used the dbSNP, gnomAD exome v2.1.1, and genome v3.0. We used Ingenuity Pathway Analysis (IPA, Qiagen) software to construct networks using all identified de novo variants with known autism-related genes to find probable relationships. We identified 36 de novo variants with potential relations to ASD; 27 missense, two silent, one nonsense, one splice region, one splice site, one 5' UTR, and one intronic SNV and two frameshift deletions. We identified six networks with functional relationships. Among the interactions between de novo variants, the IPA assay found that the NF-κB signaling pathway and its interacting genes were commonly observed at two networks. The relatively small cohort size may affect the results of novel ASD genes with de novo variants described in our findings. We did not conduct functional experiments in this study. Because of the diversity and heterogeneity of ASD, the primary purpose of this study was to investigate probable causative relationships between novel de novo variants and known autism genes. Additionally, we based functional relationships with known genes on network analysis rather than on statistical analysis. We identified new variants that may underlie genetic factors contributing to ASD in Korean families using WES and genetic network analyses. We observed novel de novo variants that might be functionally linked to ASD, of which the variants interact with six genetic networks.

Dataset Information

Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing.

Publications

Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing.

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