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  Shared endo-phenotypes of default mode dysfunction in attention deficit/hyperactivity disorder and autism spectrum disorder

Kernbach, J. M., Satterthwaite, T. D., Bassett, D. S., Smallwood, J., Margulies, D. S., Krall, S., Shaw, P., Varoquaux, G., Thirion, B., Konrad, K., & Bzdok, D. (2018). Shared endo-phenotypes of default mode dysfunction in attention deficit/hyperactivity disorder and autism spectrum disorder. Translational Psychiatry,. doi:10.1038/s41398-018-0179-6.

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アイテムのパーマリンク: https://hdl.handle.net/21.11116/0000-0001-E1FD-4 版のパーマリンク: https://hdl.handle.net/21.11116/0000-0003-A589-8
資料種別: 学術論文

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Kernbach_2018.pdf (出版社版), 2MB
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https://hdl.handle.net/21.11116/0000-0001-E1FF-2
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Kernbach_2018.pdf
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作成者

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 作成者:
Kernbach, Julius M. 1, 著者
Satterthwaite, Theodore D. 2, 著者
Bassett, Danielle S. 3, 4, 著者
Smallwood, Jonathan 5, 著者
Margulies, Daniel S.6, 著者           
Krall, Sarah1, 著者
Shaw, Philip 7, 著者
Varoquaux, Gaël 8, 著者
Thirion, Bertrand 8, 著者
Konrad, Kerstin 9, 10, 11, 著者
Bzdok, Danilo 1, 8, 9, 著者
所属:
1Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Germany, ou_persistent22              
2Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA, ou_persistent22              
3Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA, ou_persistent22              
4Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA, ou_persistent22              
5Department of Psychology, University of York, Heslington, United Kingdom, ou_persistent22              
6Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_1356546              
7Child Psychiatry Branch, National Institute of Mental Health, Bethesda, MD, USA, ou_persistent22              
8Neurospin Center, Gif-sur-Yvette, France, ou_persistent22              
9Jülich Aachen Research Alliance - JARA BRAIN, Jülich, Germany, ou_persistent22              
10Child Neuropsychology Section, Department of Child Psychiatry, RWTH Aachen University, Germany, ou_persistent22              
11Institute of Neuroscience and Medicine, Research Center Jülich, Germany, ou_persistent22              

内容説明

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 要旨: Categorical diagnoses from the Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) manuals are increasingly found to be incongruent with emerging neuroscientific evidence that points towards shared neurobiological dysfunction underlying attention deficit/hyperactivity disorder and autism spectrum disorder. Using resting-state functional magnetic resonance imaging data, functional connectivity of the default mode network, the dorsal attention and salience network was studied in 1305 typically developing and diagnosed participants. A transdiagnostic hierarchical Bayesian modeling framework combining Indian Buffet Processes and Latent Dirichlet Allocation was proposed to address the urgent need for objective brain-derived measures that can acknowledge shared brain network dysfunction in both disorders. We identified three main variation factors characterized by distinct coupling patterns of the temporoparietal cortices in the default mode network with the dorsal attention and salience network. The brain-derived factors were demonstrated to effectively capture the underlying neural dysfunction shared in both disorders more accurately, and to enable more reliable diagnoses of neurobiological dysfunction. The brain-derived phenotypes alone allowed for a classification accuracy reflecting an underlying neuropathology of 67.33% (+/-3.07) in new individuals, which significantly outperformed the 46.73% (+/-3.97) accuracy of categorical diagnoses. Our results provide initial evidence that shared neural dysfunction in ADHD and ASD can be derived from conventional brain recordings in a data-led fashion. Our work is encouraging to pursue a translational endeavor to find and further study brain-derived phenotypes, which could potentially be used to improve clinical decision-making and optimize treatment in the future.

資料詳細

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言語: eng - English
 日付: 2018-05-032018-02-032018-05-112018-07-17
 出版の状態: オンラインで出版済み
 ページ: -
 出版情報: -
 目次: -
 査読: 査読あり
 識別子（DOI, ISBNなど）: DOI: 10.1038/s41398-018-0179-6
PMID: 30018328
PMC: PMC6050263
 学位: -

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Project information

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Project name : The International Research Training Group (IRTG) / IRTG2150
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Funding program : -
Funding organization : International Training Group RWTH Uniklinik
Project name : -
Grant ID : -
Funding program : Amazon AWS Research Grant
Funding organization : Amazon
Project name : -
Grant ID : -
Funding program : START-Program
Funding organization : Faculty of Medicine, RWTH Aachen

出版物 1

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出版物名: Translational Psychiatry
  省略形 : Transl Psychiatry
種別: 学術雑誌
 著者・編者:
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出版社, 出版地: Nature Pub. Group
ページ: - 巻号: - 通巻号: 133 開始・終了ページ: - 識別子（ISBN, ISSN, DOIなど）: ISSN: 2158-3188
CoNE: https://pure.mpg.de/cone/journals/resource/2158-3188