Significant heterogeneity across aetiologies, neurobiology and clinical phenotypes have been observed in individuals with autism spectrum disorder (ASD). Neuroimaging-based neuroanatomical studies of ASD have often reported inconsistent findings which may, in part, be attributable to an insufficient understanding of the relationship between factors influencing clinical heterogeneity and their relationship to brain anatomy. To this end, we performed a large-scale examination of cortical morphometry in ASD, with a specific focus on the impact of three potential sources of heterogeneity: sex, age and full-scale intelligence (FIQ). To examine these potentially subtle relationships, we amassed a large multi-site dataset that was carefully quality controlled (yielding a final sample of 1327 from the initial dataset of 3145 magnetic resonance images; 491 individuals with ASD). Using a meta-analytic technique to account for inter-site differences, we identified greater cortical thickness in individuals with ASD relative to controls, in regions previously implicated in ASD, including the superior temporal gyrus and inferior frontal sulcus. Greater cortical thickness was observed in sex specific regions; further, cortical thickness differences were observed to be greater in younger individuals and in those with lower FIQ, and to be related to overall clinical severity. This work serves as an important step towards parsing factors that influence neuroanatomical heterogeneity in ASD and is a potential step towards establishing individual-specific biomarkers.
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R code used to conduct the prospective meta-analyses described here is available from the corresponding authors upon request.
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MRC AIMS Consortium:
Anthony J. Bailey (Oxford), Simon Baron-Cohen (Cambridge), Patrick F. Bolton (IoPPN), Edward T. Bullmore (Cambridge), Sarah Carrington (Oxford), Marco Catani (IoPPN), Bhismadev Chakrabarti (Cambridge), Michael C. Craig (IoPPN), Eileen M. Daly (IoPPN), Sean C. L. Deoni (IoPPN), Christine Ecker (IoPPN), Francesca Happé (IoPPN), Julian Henty (Cambridge), Peter Jezzard (Oxford), Patrick Johnston (IoPPN), Derek K. Jones (IoPPN), Meng-Chuan Lai (Cambridge), Michael V. Lombardo (Cambridge), Anya Madden (IoPPN), Diane Mullins (IoPPN), Clodagh M. Murphy (IoPPN), Declan G. M. Murphy (IoPPN), Greg Pasco (Cambridge), Amber N. V. Ruigrok (Cambridge), Susan A. Sadek (Cambridge), Debbie Spain (IoPPN), Rose Stewart (Oxford), John Suckling (Cambridge), Sally J. Wheelwright (Cambridge) and Steven C. Williams (IoPPN).
This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund, awarded to McGill University for the Healthy Brains for Healthy Lives initiative, in the form of a graduate student fellowship to SAB. The Autism Imaging Multicentre Study Consortium was funded by the Medical Research Council United Kingdom grant G0400061. The Cambridge Family Study of Autism was funded by a Clinical Scientist Fellowship from the UK Medical Research Council (MRC) (G0701919). AR was supported by funding from the Intramural Research Program of the NIMH (Clinical trial reg. no. NCT00001246, clinicaltrials.gov; NIH Annual Report Number, ZIA MH002794, Protocol ID 89-M-0006). The Toronto sample was gathered from studies supported by grants MOP-119541, MOP-106582 and MOP-14237 from the Canadian Institutes of Health Research (to MT), and from the POND Network, funded by the Ontario Brain Institute (grant IDS-I l-02 to EA and JL), an independent non-profit corporation, funded partially by the Ontario government. The opinions, results and conclusions are those of the authors and no endorsement by the Ontario Brain Institute is intended or should be inferred. JL received funding from the Canadian Institute for Health Research. MMC received funding from the Canadian Institute for Health Research, the Natural Sciences and Engineering Research Council, the Fonds de recherche du Québec – Santé and McGill University’s Healthy Brains for Healthy Lives initative. SBC was supported by the Autism Research Trust. DGM was supported in this work by funding from the MRC UK, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, and King’s College London (Medical Research Council grant no. G0400061 to DGMM). DGM, SBC, AR, JS, CE, and RH are also supported by EU-AIMS and AIMS-2 TRIALS. EU-AIMS receives support from the Innovative Medicines Initiative (IMI) Joint Undertaking (JU) under grant agreement no. 115300, the resources of which are composed of financial contributions from the European Union's Seventh Framework Programme (grant FP7/2007- 2013). AIMS-2 TRIALS received support from EFPIA and AUTISM SPEAKS, Autistica, and SFARI, and funding from the IMI 2 JU under grant agreement no. 777394, with support from the European Union's Horizon 2020 research and innovation programme. MVL was supported by an ERC Starting Grant (ERC-2017-STG; 755816). M-CL was supported by the O'Brien Scholars Program within the Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health and the Hospital for Sick Children, Toronto, and the Slifka-Ritvo Award for Innovation in Autism Research by the Alan B. Slifka Foundation and the International Society for Autism Research. The authors would like to thank the investigators and participants in the ABIDE dataset. Funding sources for each individual sites are provided on the official ABIDE website (http://fcon_1000.projects.nitrc.org/indi/abide/).
Conflict of interest
DGM reported receiving honoraria from Roche for being on a scientific advisory board. No other conflicts of interest were reported.
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The Medical Research Council Autism Imaging Multicentre Study Consortium (MRC AIMS Consortium) is a UK collaboration between the Institute of Psychiatry, Psychology and Neuroscience (IoPPN) at King’s College, London, the Autism Research Centre, University of Cambridge, and the Autism Research Group, University of Oxford. Members of MRC AIMS Consortium are listed at the end of the article.
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Bedford, S.A., Park, M.T.M., Devenyi, G.A. et al. Large-scale analyses of the relationship between sex, age and intelligence quotient heterogeneity and cortical morphometry in autism spectrum disorder. Mol Psychiatry 25, 614–628 (2020). https://doi.org/10.1038/s41380-019-0420-6
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