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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., et al. (2018). Shared endo-phenotypes of default mode dysfunction in attention deficit/hyperactivity disorder and autism spectrum disorder. Translational Psychiatry, 133. doi:10.1038/s41398-018-0179-6.

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Genre: Journal Article


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Kernbach, Julius M. 1, Author
Satterthwaite, Theodore D. 2, Author
Bassett, Danielle S. 3, 4, Author
Smallwood, Jonathan 5, Author
Margulies, Daniel S.6, Author              
Krall, Sarah1, Author
Shaw, Philip 7, Author
Varoquaux, Gaël 8, Author
Thirion, Bertrand 8, Author
Konrad, Kerstin 9, 10, 11, Author
Bzdok, Danilo 1, 8, 9, Author
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              


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 Abstract: 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.


Language(s): eng - English
 Dates: 2018-05-032018-02-032018-05-112018-07-17
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41398-018-0179-6
PMID: 30018328
PMC: PMC6050263
 Degree: -



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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
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Funding program : Amazon AWS Research Grant
Funding organization : Amazon
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Funding program : START-Program
Funding organization : Faculty of Medicine, RWTH Aachen

Source 1

Title: Translational Psychiatry
  Abbreviation : Transl Psychiatry
Source Genre: Journal
Publ. Info: Nature Pub. Group
Pages: - Volume / Issue: - Sequence Number: 133 Start / End Page: - Identifier: ISSN: 2158-3188
CoNE: https://pure.mpg.de/cone/journals/resource/2158-3188