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Multivariate classification provides a neural signature of Tourette disorder

Published online by Cambridge University Press:  03 November 2021

Giuseppe A. Zito Open the ORCID record for Giuseppe A. Zito [Opens in a new window] ,
Andreas Hartmann ,
Benoît Béranger ,
Samantha Weber ,
Selma Aybek ,
Johann Faouzi ,
Emmanuel Roze ,
Marie Vidailhet  and
Yulia Worbe
Giuseppe A. Zito
Affiliation:
Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, Paris Brain Institute, Movement Investigation and Therapeutics Team, Paris, France Support Centre for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, Bern CH-3010, Switzerland
Andreas Hartmann
Affiliation:
Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, Paris Brain Institute, Movement Investigation and Therapeutics Team, Paris, France National Reference Center for Tourette Syndrome, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
Benoît Béranger
Affiliation:
Center for NeuroImaging Research (CENIR), Paris Brain Institute, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMR, 7225, Paris, France
Samantha Weber
Affiliation:
Psychosomatics Unit of the Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, Bern CH-3010, Switzerland
Selma Aybek
Affiliation:
Psychosomatics Unit of the Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, Bern CH-3010, Switzerland
Johann Faouzi
Affiliation:
Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, ICM, Inria Paris, Aramis project-team, Paris, France
Emmanuel Roze
Affiliation:
Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, Paris Brain Institute, Movement Investigation and Therapeutics Team, Paris, France
Marie Vidailhet
Affiliation:
Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, Paris Brain Institute, Movement Investigation and Therapeutics Team, Paris, France
Yulia Worbe*
Affiliation:
Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, Paris Brain Institute, Movement Investigation and Therapeutics Team, Paris, France National Reference Center for Tourette Syndrome, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière, Paris, France Department of Neurophysiology, Saint-Antoine Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
*
Author for correspondence: Yulia Worbe, E-mail: yulia.worbe@aphp.fr
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Abstract

Background

Tourette disorder (TD), hallmarks of which are motor and vocal tics, has been related to functional abnormalities in large-scale brain networks. Using a fully data driven approach in a prospective, case–control study, we tested the hypothesis that functional connectivity of these networks carries a neural signature of TD. Our aim was to investigate (i) the brain networks that distinguish adult patients with TD from controls, and (ii) the effects of antipsychotic medication on these networks.

Methods

Using a multivariate analysis based on support vector machine (SVM), we developed a predictive model of resting state functional connectivity in 48 patients and 51 controls, and identified brain networks that were most affected by disease and pharmacological treatments. We also performed standard univariate analyses to identify differences in specific connections across groups.

Results

SVM was able to identify TD with 67% accuracy (p = 0.004), based on the connectivity in widespread networks involving the striatum, fronto-parietal cortical areas and the cerebellum. Medicated and unmedicated patients were discriminated with 69% accuracy (p = 0.019), based on the connectivity among striatum, insular and cerebellar networks. Univariate approaches revealed differences in functional connectivity within the striatum in patients v. controls, and between the caudate and insular cortex in medicated v. unmedicated TD.

Conclusions

SVM was able to identify a neuronal network that distinguishes patients with TD from control, as well as medicated and unmedicated patients with TD, holding a promise to identify imaging-based biomarkers of TD for clinical use and evaluation of the effects of treatment.

Keywords

Tourette disorderresting state fMRImultivariate analysissupport vector machine
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 6 , April 2023 , pp. 2361 - 2369
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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