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  Multidimensional neuroanatomical subtyping of autism spectrum disorder

Hong, S.-J., Valk, S. L., Di Martino, A., Milham, M. P., & Bernhardt, B. C. (2018). Multidimensional neuroanatomical subtyping of autism spectrum disorder. Cerebral Cortex, 28(10), 3578-3588. doi:10.1093/cercor/bhx229.

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 Creators:
Hong, Seok-Jun 1, Author
Valk, Sofie L.2, Author           
Di Martino, Adriana3, Author
Milham, Michael P.4, 5, Author
Bernhardt, Boris C.1, Author           
Affiliations:
1Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, QC, Canada, ou_persistent22              
2Department Social Neuroscience, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634552              
3Department of Child and Adolescent Psychiatry, Child Study Center, New York University Langone Medical Center, NY, USA, ou_persistent22              
4Center for the Developing Brain, Child Mind Institute, New York, NY, USA, ou_persistent22              
5Center for Biomedical Imaging and Neuromodulation (C-BIN), Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA, ou_persistent22              

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Free keywords: Autism; Biomarker; Biotype; Computational neuroanatomy; Magnetic resonance imaging; Subtype
 Abstract: Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with multiple biological etiologies and highly variable symptoms. Using a novel analytical framework that integrates cortex-wide MRI markers of vertical (i.e., thickness, tissue contrast) and horizontal (i.e., surface area, geodesic distance) cortical organization, we could show that a large multi-centric cohort of individuals with ASD falls into 3 distinctive anatomical subtypes (ASD-I: cortical thickening, increased surface area, tissue blurring; ASD-II: cortical thinning, decreased distance; ASD-III: increased distance). Bootstrap analysis indicated a high consistency of these biotypes across thousands of simulations, while analysis of behavioral phenotypes and resting-state fMRI showed differential symptom load (i.e., Autism Diagnostic Observation Schedule; ADOS) and instrinsic connectivity anomalies in communication and social-cognition networks. Notably, subtyping improved supervised learning approaches predicting ADOS score in single subjects, with significantly increased performance compared to a subtype-blind approach. The existence of different subtypes may reconcile previous results so far not converging on a consistent pattern of anatomical anomalies in autism, and possibly relate the presence of diverging corticogenic and maturational anomalies. The high accuracy for symptom severity prediction indicates benefits of MRI biotyping for personalized diagnostics and may guide the development of targeted therapeutic strategies.

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Language(s): eng - English
 Dates: 2017-07-172017-03-012017-08-232017-09-142018-10-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1093/cercor/bhx229
PMID: 28968847
 Degree: -

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Funding organization : Montreal Neurological Institute (MNI)
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Funding organization : SickKids Foundation
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Funding organization : Canadian Institutes of Health Research (CIHR)
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Funding organization : National Sciences and Engineering Research Council of Canada (NSERC)
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Funding organization : Fonts de la Reserche du Quebec—Sante (FRQS)
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Funding organization : International Max Planck Research School (IMPRS)
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Grant ID : U01MH099059 ; R01 AG047596
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Funding organization : National Institutes of Health (NIH)

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Title: Cerebral Cortex
Source Genre: Journal
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Publ. Info: New York, NY : Oxford University Press
Pages: - Volume / Issue: 28 (10) Sequence Number: - Start / End Page: 3578 - 3588 Identifier: ISSN: 1047-3211
CoNE: https://pure.mpg.de/cone/journals/resource/954925592440