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    Stratifying the autistic phenotype using electrophysiological indices of social perception

    Mason, Luke and Moessnang, C. and Chatham, C. and Ham, L. and Tillmann, J. and Guillaume, D. and Claire, E. and Leblond, C. and CLiquet, F. and Bougeron, T. and Charman, T. and Oakley, B. and Banaschewski, T. and Meyer-Lindenberg, A. and Baron-Cohen, S. and Bolte, S. and Buitelaar, J. and Durston, S. and Loth, E. and Oranje, B. and Persico, A. and Dell'Acqua, F. and Ecker, C. and Johnson, Mark H. and Murphy, D and Jones, Emily J.H. (2022) Stratifying the autistic phenotype using electrophysiological indices of social perception. Science Translational Medicine 14 (658), ISSN 1946-6234.

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    Abstract

    Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties in social communication, but also great heterogeneity. To offer individualized medicine approaches, we need to better target interventions by stratifying autistic people into subgroups with different biological profiles and/or prognoses. We sought to validate neural responses to faces as a potential stratification factor in ASD by measuring neural (electroencephalography) responses to faces (critical in social interaction) in N = 436 children and adults with and without ASD. The speed of early-stage face processing (N170 latency) was on average slower in ASD than in age-matched controls. In addition, N170 latency was associated with responses to faces in the fusiform gyrus, measured with functional magnetic resonance imaging, and polygenic scores for ASD. Within the ASD group, N170 latency predicted change in adaptive socialization skills over an 18-month follow-up period; data-driven clustering identified a subgroup with slower brain responses and poor social prognosis. Use of a distributional data-driven cutoff was associated with predicted improvements of power in simulated clinical trials targeting social functioning. Together, the data provide converging evidence for the utility of the N170 as a stratification factor to identify biologically and prognostically defined subgroups in ASD.

    Metadata

    Item Type: Article
    School: School of Science > Psychological Sciences
    Research Centres and Institutes: Brain and Cognitive Development, Centre for (CBCD)
    Depositing User: Luke Mason
    Date Deposited: 24 Aug 2022 13:54
    Last Modified: 24 Aug 2022 17:11
    URI: https://eprints.bbk.ac.uk/id/eprint/48983

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