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Neurological Diseases With Autism Spectrum Disorder: Role of ASD Risk Genes.

ABSTRACT: Autism spectrum disorder (ASD) is frequently comorbid with other neurological disorders such as intellectual disability (ID) or global development delay (GDD) and epilepsy. The pathogenesis of ASD is complex. So far, studies have identified more than 1000 ASD risk genes. Most of them were also reported to relate with other neurological diseases, and only several of them have been confirmed as pathogenic genes for autism. Little is known about the roles of these risk genes in neurological diseases with ASD. In the present study, we recruited a cohort of 158 neurological disorder probands with 163 variants of 48 ASD risk genes. Of these, 50 individuals (31.6%) were diagnosed with ASD. In the ASD patient subset, we identified several rarely reported candidate genes including DOLK, USH2A, and HUWE1. In a comparison of patients with neurological disorders with and without ASD, we found that ID/GDD was frequently comorbid with ASD whereas epilepsy was more common in the non-ASD group. Statistical analyses of all possible risk factors implicated that variants in synaptic genes, especially non-voltage-gated ion channel genes and in transcriptional and chromosome genes were related to ASD, but none of the investigated environmental factors was. Our results are useful for the future diagnosis and prognosis of patients with neurological disorders and emphasize the utility of genetic screening.

SUBMITTER: Xiong J

PROVIDER: S-EPMC6470315 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Neurological Diseases With Autism Spectrum Disorder: Role of ASD Risk Genes.

Xiong Juan J Chen Shimeng S Pang Nan N Deng Xiaolu X Yang Lifen L He Fang F Wu Liwen L Chen Chen C Yin Fei F Peng Jing J

Frontiers in neuroscience 20190411

Autism spectrum disorder (ASD) is frequently comorbid with other neurological disorders such as intellectual disability (ID) or global development delay (GDD) and epilepsy. The pathogenesis of ASD is complex. So far, studies have identified more than 1000 ASD risk genes. Most of them were also reported to relate with other neurological diseases, and only several of them have been confirmed as pathogenic genes for autism. Little is known about the roles of these risk genes in neurological disease ...[more]

PMID: 31031587

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Project description:Background: Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social interaction, restricted interest and repetitive behavior. Oxidative stress in response to environmental exposure plays a role in virtually every human disease and represents a significant avenue of research into the etiology of ASD. The aim of this study was to explore the diagnostic utility of four urinary biomarkers of oxidative stress. Methods: One hundred and thirty-nine (139) children and adolescents with ASD (89% male, average age = 10.0 years, age range = 2.1 to 18.1 years) and 47 healthy children and adolescents (49% male, average age 9.2, age range = 2.5 to 20.8 years) were recruited for this study. Their urinary 8-OH-dG, 8-isoprostane, dityrosine and hexanoil-lisine were determined by using the ELISA method. Urinary creatinine was determined with the kinetic Jaffee reaction and was used to normalize all biochemical measurements. Non-parametric tests and support vector machines (SVM) with three different kernel functions (linear, radial, polynomial) were used to explore and optimize the multivariate prediction of an ASD diagnosis based on the collected biochemical measurements. The SVM models were first trained using data from a random subset of children and adolescents from the ASD group (n = 70, 90% male, average age = 9.7 years, age range = 2.1 to 17.8 years) and the control group (n = 24, 45.8% male, average age = 9.4 years, age range = 2.5 to 20.8 years) using bootstrapping, with additional synthetic minority over-sampling (SMOTE), which was utilized because of unbalanced data. The computed SVM models were then validated using the remaining data from children and adolescents from the ASD (n = 69, 88% male, average age = 10.2 years, age range = 4.3 to 18.1 years) and the control group (n = 23, 52.2% male, average age = 8.9 years, age range = 2.6 to 16.7 years). Results: Using a non-parametric test, we found a trend showing that the urinary 8-OH-dG concentration was lower in children with ASD compared to the control group (unadjusted p = 0.085). When all four biochemical measurements were combined using SVMs with a radial kernel function, we could predict an ASD diagnosis with a balanced accuracy of 73.4%, thereby accounting for an estimated 20.8% of variance (p < 0.001). The predictive accuracy expressed as the area under the curve (AUC) was solid (95% CI = 0.691-0.908). Using the validation data, we achieved significantly lower rates of classification accuracy as expressed by the balanced accuracy (60.1%), the AUC (95% CI = 0.502-0.781) and the percentage of explained variance (R2 = 3.8%). Although the radial SVMs showed less predictive power using the validation data, they do, together with ratings of standardized SVM variable importance, provide some indication that urinary levels of 8-OH-dG and 8-isoprostane are predictive of an ASD diagnosis. Conclusions: Our results indicate that the examined urinary biomarkers in combination may differentiate children with ASD from healthy peers to a significant extent. However, the etiological importance of these findings is difficult to assesses, due to the high-dimensional nature of SVMs and a radial kernel function. Nonetheless, our results show that machine learning methods may provide significant insight into ASD and other disorders that could be related to oxidative stress.

Dataset Information

Neurological Diseases With Autism Spectrum Disorder: Role of ASD Risk Genes.

Publications

Neurological Diseases With Autism Spectrum Disorder: Role of ASD Risk Genes.

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