Christine Ecker1, Derek S Andrews2, Christina M Gudbrandsen2, Andre F Marquand3, Cedric E Ginestet4, Eileen M Daly2, Clodagh M Murphy5, Meng-Chuan Lai6, Michael V Lombardo7, Amber N V Ruigrok8, Edward T Bullmore9, John Suckling9, Steven C R Williams10, Simon Baron-Cohen8, Michael C Craig11, Declan G M Murphy5. 1. Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Goethe University, Frankfurt am Main, Germany2Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England. 2. Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England. 3. Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands4Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England. 4. Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England. 5. Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England6Behavioural Genetics Clinic, Adult Autism Service, Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley Foundation National Health Service Trust, London, England. 6. Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, England8Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health, The Hospital for Sick Children, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada9Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei. 7. Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, England10Department of Psychology and Center for Applied Neuroscience, University of Cyprus, Nicosia. 8. Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, England. 9. Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, England. 10. Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England. 11. Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England12National Autism Unit, Bethlem Royal Hospital, South London and Maudsley Foundation National Health Service Trust, London, England.
Abstract
Importance: Autism spectrum disorder (ASD) is 2 to 5 times more common in male individuals than in female individuals. While the male preponderant prevalence of ASD might partially be explained by sex differences in clinical symptoms, etiological models suggest that the biological male phenotype carries a higher intrinsic risk for ASD than the female phenotype. To our knowledge, this hypothesis has never been tested directly, and the neurobiological mechanisms that modulate ASD risk in male individuals and female individuals remain elusive. Objectives: To examine the probability of ASD as a function of normative sex-related phenotypic diversity in brain structure and to identify the patterns of sex-related neuroanatomical variability associated with low or high probability of ASD. Design, Setting, and Participants: This study examined a cross-sectional sample of 98 right-handed, high-functioning adults with ASD and 98 matched neurotypical control individuals aged 18 to 42 years. A multivariate probabilistic classification approach was used to develop a predictive model of biological sex based on cortical thickness measures assessed via magnetic resonance imaging in neurotypical controls. This normative model was subsequently applied to individuals with ASD. The study dates were June 2005 to October 2009, and this analysis was conducted between June 2015 and July 2016. Main Outcomes and Measures: Sample and population ASD probability estimates as a function of normative sex-related diversity in brain structure, as well as neuroanatomical patterns associated with low or high ASD probability in male individuals and female individuals. Results: Among the 98 individuals with ASD, 49 were male and 49 female, with a mean (SD) age of 26.88 (7.18) years. Among the 98 controls, 51 were male and 47 female, with a mean (SD) age of 27.39 (6.44) years. The sample probability of ASD increased significantly with predictive probabilities for the male neuroanatomical brain phenotype. For example, biological female individuals with a more male-typic pattern of brain anatomy were significantly (ie, 3 times) more likely to have ASD than biological female individuals with a characteristically female brain phenotype (P = .72 vs .24, respectively; χ21 = 20.26; P < .001; difference in P values, 0.48; 95% CI, 0.29-0.68). This finding translates to an estimated variability in population prevalence from 0.2% to 1.3%, respectively. Moreover, the patterns of neuroanatomical variability carrying low or high ASD probability were sex specific (eg, in inferior temporal regions, where ASD has different neurobiological underpinnings in male individuals and female individuals). Conclusions and Relevance: These findings highlight the need for considering normative sex-related phenotypic diversity when determining an individual's risk for ASD and provide important novel insights into the neurobiological mechanisms mediating sex differences in ASD prevalence.
Importance: Autism spectrum disorder (ASD) is 2 to 5 times more common in male individuals than in female individuals. While the male preponderant prevalence of ASD might partially be explained by sex differences in clinical symptoms, etiological models suggest that the biological male phenotype carries a higher intrinsic risk for ASD than the female phenotype. To our knowledge, this hypothesis has never been tested directly, and the neurobiological mechanisms that modulate ASD risk in male individuals and female individuals remain elusive. Objectives: To examine the probability of ASD as a function of normative sex-related phenotypic diversity in brain structure and to identify the patterns of sex-related neuroanatomical variability associated with low or high probability of ASD. Design, Setting, and Participants: This study examined a cross-sectional sample of 98 right-handed, high-functioning adults with ASD and 98 matched neurotypical control individuals aged 18 to 42 years. A multivariate probabilistic classification approach was used to develop a predictive model of biological sex based on cortical thickness measures assessed via magnetic resonance imaging in neurotypical controls. This normative model was subsequently applied to individuals with ASD. The study dates were June 2005 to October 2009, and this analysis was conducted between June 2015 and July 2016. Main Outcomes and Measures: Sample and population ASD probability estimates as a function of normative sex-related diversity in brain structure, as well as neuroanatomical patterns associated with low or high ASD probability in male individuals and female individuals. Results: Among the 98 individuals with ASD, 49 were male and 49 female, with a mean (SD) age of 26.88 (7.18) years. Among the 98 controls, 51 were male and 47 female, with a mean (SD) age of 27.39 (6.44) years. The sample probability of ASD increased significantly with predictive probabilities for the male neuroanatomical brain phenotype. For example, biological female individuals with a more male-typic pattern of brain anatomy were significantly (ie, 3 times) more likely to have ASD than biological female individuals with a characteristically female brain phenotype (P = .72 vs .24, respectively; χ21 = 20.26; P < .001; difference in P values, 0.48; 95% CI, 0.29-0.68). This finding translates to an estimated variability in population prevalence from 0.2% to 1.3%, respectively. Moreover, the patterns of neuroanatomical variability carrying low or high ASD probability were sex specific (eg, in inferior temporal regions, where ASD has different neurobiological underpinnings in male individuals and female individuals). Conclusions and Relevance: These findings highlight the need for considering normative sex-related phenotypic diversity when determining an individual's risk for ASD and provide important novel insights into the neurobiological mechanisms mediating sex differences in ASD prevalence.
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Authors: Daan van Rooij; Evdokia Anagnostou; Celso Arango; Guillaume Auzias; Marlene Behrmann; Geraldo F Busatto; Sara Calderoni; Eileen Daly; Christine Deruelle; Adriana Di Martino; Ilan Dinstein; Fabio Luis Souza Duran; Sarah Durston; Christine Ecker; Damien Fair; Jennifer Fedor; Jackie Fitzgerald; Christine M Freitag; Louise Gallagher; Ilaria Gori; Shlomi Haar; Liesbeth Hoekstra; Neda Jahanshad; Maria Jalbrzikowski; Joost Janssen; Jason Lerch; Beatriz Luna; Mauricio Moller Martinho; Jane McGrath; Filippo Muratori; Clodagh M Murphy; Declan G M Murphy; Kirsten O'Hearn; Bob Oranje; Mara Parellada; Alessandra Retico; Pedro Rosa; Katya Rubia; Devon Shook; Margot Taylor; Paul M Thompson; Michela Tosetti; Gregory L Wallace; Fengfeng Zhou; Jan K Buitelaar Journal: Am J Psychiatry Date: 2017-11-17 Impact factor: 18.112