Deriving and validating biomarkers associated with autism spectrum disorders from a large-scale resting-state database

Resting-state functional magnetic resonance imaging (MRI) has been used to investigate the brain activity related to autism spectrum disorder (ASD). In this study, we applied information from a large-scale dataset, the Autism Brain Imaging Data Exchange (ABIDE), to clinical applications. We recruite...

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Bibliographic Details
Published in:Scientific reports 2019-06, Vol.9 (1), p.9043-10, Article 9043
Main Authors: Chen, Chia-Min, Yang, Pinchen, Wu, Ming-Ting, Chuang, Tzu-Chao, Huang, Teng-Yi
Format: Article
Language:English
Subjects:
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Adolescent
Autism
Autistic Disorder - metabolism
Biomarkers
Biomarkers - metabolism
Brain mapping
Child
Databases, Factual
Executive function
Female
Functional magnetic resonance imaging
Humanities and Social Sciences
Humans
Male
multidisciplinary
Neural networks
Neuroimaging
NMR
Nuclear magnetic resonance
Science
Science (multidisciplinary)
Surveys and Questionnaires
Therapeutic applications
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Summary:Resting-state functional magnetic resonance imaging (MRI) has been used to investigate the brain activity related to autism spectrum disorder (ASD). In this study, we applied information from a large-scale dataset, the Autism Brain Imaging Data Exchange (ABIDE), to clinical applications. We recruited 21 patients with ASD and 23 individuals with neurotypical development (TD). We applied ASD biomarkers derived from ABIDE datasets and subsequently investigated the relationship between the MRI biomarkers and indicators from clinical screening questionnaires, the social responsiveness scale (SRS), and the Swanson, Nolan, and Pelham Questionnaire IV. The results indicated that the biomarkers generated from the default mode and executive control networks significantly differed between the participants with ASD and TD. In particular, the biomarkers derived from the default mode network were negatively correlated with the raw scores and model factors of the SRS. In summary, this study transferred the efforts of the global autism research community to clinical applications and identified connectivity-based biomarkers in ASD.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-019-45465-9