Identifying Distinct Electrophysiological Endophenotypes in Autism Spectrum Disorder: A Large-Scale Machine Learning Approach Integrating Auditory Brainstem Response and Behavioral Phenotyping
Abstract
Background Our study aimed to explore the correlations between Auditory Brainstem Response outcomes and Autism phenotypes.Methods A total of 1883 children with or suspected of being with ASD were enrolled. The related features were acquired by using the Autism Behavior Checklist (ABC), Children Autism Rating Scale (CARS) and ABR outcomes. The cluster analysis was conducted to detect potential subgroups within our samples, and the ANOVA analysis was conducted to reveal the differences among these subgroups using data from clinical assessments. The Pearson Correlation analysis was conducted to depict the associations between ABR results and different autism phenotypes.Results Our results revealed different brainstem vulnerabilities across six ASD clusters. Cluster 6 exhibited robust language-associated temporal alternations, while cluster 4 displayed sensory-related pontine-mesencephalic delays. Besides, compromised olivary function uniquely presented correlations with ABC total scores in cluster 2. Notably, less affected auditory pathways were found in clusters with high-functioning performance.Conclusion Our findings confirmed that compromised ABR components did not display in uniform formats but rather differed across different subgroups. Furthe research is needed to validate these neurophysiological markers, promoting precise personalized interventions tailored to ASD phenotypes.
Keywords
Citation Information
@article{qingjiezhang2026,
title={Identifying Distinct Electrophysiological Endophenotypes in Autism Spectrum Disorder: A Large-Scale Machine Learning Approach Integrating Auditory Brainstem Response and Behavioral Phenotyping},
author={Qingjie Zhang and Chunmei Ren and Xianrong Liang and Guojun Yun and Kanglong Peng},
journal={Journal of Neurodevelopmental Disorders},
year={2026},
doi={https://doi.org/10.21203/rs.3.rs-9288120/v1}
}
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