Gene functional networks and autism spectrum characteristics in young people with intellectual disability: a dimensional
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Gene functional networks and autism spectrum characteristics in young people with intellectual disability: a dimensional phenotyping study Diandra Brkić1†, Elise Ng‑Cordell1,2†, Sinéad O’Brien1, Gaia Scerif2, Duncan Astle1 and Kate Baker1*
Abstract Background: The relationships between specific genetic aetiology and phenotype in neurodevelopmental disorders are complex and hotly contested. Genes associated with intellectual disability (ID) can be grouped into networks according to gene function. This study explored whether individuals with ID show differences in autism spectrum characteristics (ASC), depending on the functional network membership of their rare, pathogenic de novo genetic variants. Methods: Children and young people with ID of known genetic origin were allocated to two broad functional net‑ work groups: synaptic physiology (n = 29) or chromatin regulation (n = 23). We applied principle components analysis to the Social Responsiveness Scale to map the structure of ASC in this population and identified three components— Inflexibility, Social Understanding and Social Motivation. We then used Akaike information criterion to test the best fitting models for predicting ASC components, including demographic factors (age, gender), non-ASC behavioural factors (global adaptive function, anxiety, hyperactivity, inattention), and gene functional networks. Results: We found that, when other factors are accounted for, the chromatin regulation group showed higher levels of Inflexibility. We also observed contrasting predictors of ASC within each network group. Within the chromatin regu‑ lation group, Social Understanding was associated with inattention, and Social Motivation was predicted by hyperac‑ tivity. Within the synaptic group, Social Understanding was associated with hyperactivity, and Social Motivation was linked to anxiety. Limitations: Functional network definitions were manually curated based on multiple sources of evidence, but a data-driven approach to classification may be more robust. Sample sizes for rare genetic diagnoses remain small, miti‑ gated by our network-based approach to group comparisons. This is a cross-sectional study across a wide age range, and longitudinal data within focused age groups will be informative of developmental trajectories across network groups. Conclusion: We report that gene functional networks can predict Inflexibility, but not other ASC dimensions. Contrasting behavioural associations within each group suggest network-specific developmental pathways from
*Correspondence: kate.baker@mrc‑cbu.cam.ac.uk † Diandra Brkić, Elise Ng-Cordell have contributed equally to this work 1 MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK Full list of author information is available at the end of the article © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in a
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