Dataset Information

Pathogenic/likely pathogenic mutations identified in Vietnamese children diagnosed with autism spectrum disorder using high-resolution SNP genotyping platform.

ABSTRACT: Among the most prevalent neurodevelopmental disorders, Autism Spectrum Disorder (ASD) is highly diverse showing a broad phenotypic spectrum. ASD also couples with a broad range of mutations, both de novo and inherited. In this study, we used a proprietary SNP genotyping chip to analyze the genomic DNA of 250 Vietnamese children diagnosed with ASD. Our Single Nucleotide Polymorphism (SNP) genotyping chip directly targets more than 800 thousand SNPs in the genome. Our primary focus was to identify pathogenic/likely pathogenic mutations that are potentially linked to more severe symptoms of autism. We identified and validated 23 pathogenic/likely pathogenic mutations in this initial study. The data shows that these mutations were detected in several cases spanning multiple biological pathways. Among the confirmed SNPs, mutations were identified in genes previously known to be strongly associated with ASD such as SLCO1B1, ACADSB, TCF4, HCP5, MOCOS, SRD5A2, MCCC2, DCC, and PRKN while several other mutations are known to associate with autistic traits or other neurodevelopmental disorders. Some mutations were found in multiple patients and some patients carried multiple pathogenic/likely pathogenic mutations. These findings contribute to the identification of potential targets for therapeutic solutions in what is considered a genetically heterogeneous neurodevelopmental disorder.

SUBMITTER: Bui DT

PROVIDER: S-EPMC10825208 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Pathogenic/likely pathogenic mutations identified in Vietnamese children diagnosed with autism spectrum disorder using high-resolution SNP genotyping platform.

Bui Duyen T DT Ton Anh N V ANV Nguyen Chi T D CTD Nguyen Son H SH Tran Hao K HK Nguyen Xuan T XT Nguyen Hang T HT Pham Giang L T GLT Tran Dong S DS Harrington Jillian J Pham Hiep N HN Pham Tuyen N V TNV Cao Tuan A TA

Scientific reports 20240129 1

Among the most prevalent neurodevelopmental disorders, Autism Spectrum Disorder (ASD) is highly diverse showing a broad phenotypic spectrum. ASD also couples with a broad range of mutations, both de novo and inherited. In this study, we used a proprietary SNP genotyping chip to analyze the genomic DNA of 250 Vietnamese children diagnosed with ASD. Our Single Nucleotide Polymorphism (SNP) genotyping chip directly targets more than 800 thousand SNPs in the genome. Our primary focus was to identify ...[more]

PMID: 38287090

Similar Datasets

Project description:BackgroundA population segment of autistic adults are under-identified due, in part, to historic changes in criteria for diagnosing autism and diagnostic biases related to gender, socioeconomic status, and other individual characteristics such as intellectual functioning. Some of these individuals, described as the "lost generation", may choose to self-diagnose. Although little is known about this population, it is possible that they share similar self-conceptualizations or internalized stigma as their diagnosed counterparts. This study reports on the structural validity of the Autism Spectrum Identity Scale (ASIS) with individuals diagnosed and self-diagnosed with autism and compares the demographic characteristics, stigma, self-concept, and quality of life of these two groups.MethodsOver 1000 adults diagnosed (n = 893) or self-diagnosed (n = 245) with autism were recruited through organizations serving the autism community to participate in a nationally distributed online survey that included demographic questions and measures for stigma, self-concept, quality of life, and wellbeing. The diagnosed dataset was randomly split with exploratory factor analysis performed on a training dataset. Split-half cross-validation was used to predict the factor structure of the holdout dataset. Then, the full diagnosed dataset structure was used to determine the generalizability of the factor structure to the self-diagnosed dataset. The diagnosed and self-diagnosed were also compared for differences in gender, age, employment status, diagnostic term preference, and factors of self-concept (autism identity and self-esteem), stigma, and quality of life.ResultsFactor analysis of diagnosed participants yielded a four-factor structure, consistent with previous research, with strong split-sample cross-validation and good internal consistency. Factor predictions of the self-diagnosed dataset from the diagnosed dataset ranged from .97 - 1.00 with similar internal consistency. Self-diagnosed participants were more likely to be older, women, or employed and less likely to be students or prefer the term "autism" than those with an autism diagnosis. The groups were remarkably similar in reported stigma, self-esteem, quality of life and in ASIS factors; both groups reported lower quality of life than the general population.ConclusionsThe ASIS demonstrated the same internal structure with both the diagnosed and self-diagnosed. The profile of self-diagnosed participants matches the profile hypothesized for the "lost generation" and others at risk of being under-identified for autism. Both populations appear to be similarly struggling with employment, stigma, and quality of life. Future research should examine whether self-diagnosed individuals meet criteria for autism or could benefit from interventions, programs, or services serving autism communities.

Project description:BackgroundNatural selection has molded evolution across all taxa. At an arguable date of around 330,000 years ago there were already at least two different types of cattle that became ancestors of nearly all modern cattle, the Bos taurus taurus more adapted to temperate climates and the tropically adapted Bos taurus indicus. After domestication, human selection exponentially intensified these differences. To better understand the genetic differences between these subspecies and detect genomic regions potentially under divergent selection, animals from the International Bovine HapMap Experiment were genotyped for over 770,000 SNP across the genome and compared using smoothed F(ST). The taurine sample was represented by ten breeds and the contrasting zebu cohort by three breeds.ResultsEach cattle group evidenced similar numbers of polymorphic markers well distributed across the genome. Principal components analyses and unsupervised clustering confirmed the well-characterized main division of domestic cattle. The top 1% smoothed F(ST), potentially associated to positive selection, contained 48 genomic regions across 17 chromosomes. Nearly half of the top F(ST) signals (n = 22) were previously detected using a lower density SNP assay. Amongst the strongest signals were the BTA7:~50 Mb and BTA14:~25 Mb; both regions harboring candidate genes and different patterns of linkage disequilibrium that potentially represent intrinsic differences between cattle types. The bottom 1% of the smoothed F(ST) values, potentially associated to balancing selection, included 24 regions across 13 chromosomes. These regions often overlap with copy number variants, including the highly variable region at BTA23:~24 Mb that harbors a large number of MHC genes. Under these regions, 318 unique Ensembl genes are annotated with a significant overrepresentation of immune related pathways.ConclusionsGenomic regions that are potentially linked to purifying or balancing selection processes in domestic cattle were identified. These regions are of particular interest to understand the natural and human selective pressures to which these subspecies were exposed to and how the genetic background of these populations evolved in response to environmental challenges and human manipulation.

Dataset Information

Pathogenic/likely pathogenic mutations identified in Vietnamese children diagnosed with autism spectrum disorder using high-resolution SNP genotyping platform.

Publications

Pathogenic/likely pathogenic mutations identified in Vietnamese children diagnosed with autism spectrum disorder using high-resolution SNP genotyping platform.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets