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

Translational Psychiatry - Tập 8 Số 1
Julius M. Kernbach1, Theodore D. Satterthwaite2, Danielle S. Bassett2, Jonathan Smallwood3, Daniel S. Margulies4,5, S.C. Krall1, Philip Shaw6, Gaël Varoquaux7,8, Bertrand Thirion8, Kerstin Konrad9, Danilo Bzdok10,8
1RWTH - Rheinisch-Westfälische Technische Hochschule Aachen University (RWTH Aachen Templergraben 55 52062 Aachen (Hausanschrift) 52056 Aachen (Postanschrift) - Germany)
2University of Pennsylvania (3451 Walnut Street, Philadelphia, PA 19104 | 215-898-5000 - United States)
3University of York [York, UK] (Heslington, York, YO10 5DD - United Kingdom)
4ICM - Institut du Cerveau = Paris Brain Institute (47-83 Boulevard de l'Hôpital 75651 Paris Cedex 13 - France)
5IMPNSC - Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (P.O. box 500355 04303 Leipzig - Germany)
6National Institute of Child Health and Human Development [Bethesda] (Bethesda, MD 20892, USA - United States)
7Inria Saclay - Ile de France (1 rue Honoré d'Estienne d'Orves Bâtiment Alan Turing Campus de l'École Polytechnique 91120 Palaiseau - France)
8PARIETAL - Modelling brain structure, function and variability based on high-field MRI data (Neurospin, CEA Saclay, Bâtiment 145, 91191 Gif-sur-Yvette Cedex - France)
9Jülich Aachen Research Alliance (JARA) (Germany)
10Department of Psychiatry, Psychotherapy and Psychosomatics [Aachen] (Pauwelsstraße 30 52074 Aachen - Germany)

Tóm tắt

AbstractCategorical 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.

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Translational Psychiatry

Tập 8 Số 1

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