De la classification des motifs à la stratification: vers la conceptualisation de l'hétérogénéité des "troubles du spectre de l'autisme"

Aperçu: G.M.

Les approches de classification des motifs et de stratification ont été de plus en plus utilisées dans la recherche sur les "troubles du spectre de l'autisme" (TSA) au cours des dix dernières années dans le but de les traduire en applicabilité clinique.

Nous présentons ici une analyse documentaire approfondie sur ces deux approches. Nous avons examiné au total 635 études, dont 57 études de classification des motifs et 19 études de stratification. 

Nous avons observé une grande variance entre les études de classification de modèles en termes de performance prédictive allant d’environ 60% à 98%, ce qui est entre autres facteurs susceptibles d’être liés au biais d’échantillonnage, aux procédures de validation différentes d’une étude à l’autre, à l’hétérogénéité des TSA et à la qualité des données. 

Les études de stratification étaient moins prévalentes avec seulement deux études rapportant des réplications et quelques-unes seulement montrant une validation externe. 

En résumé, la cartographie des différences biologiques au niveau individuel avec les TSA est un défi majeur pour le domaine. Conceptualiser ces cartographies et trajectoires individuelles menant au diagnostic de TSA deviendra un défi majeur dans un proche avenir.

Neurosci Biobehav Rev. 2019 Jul 19. pii: S0149-7634(19)30319-7. doi: 10.1016/j.neubiorev.2019.07.010.

From pattern classification to stratification: towards conceptualizing the heterogeneity of Autism Spectrum Disorder

Wolfers T¹, Floris DL², Dinga R³, van Rooij D², Isakoglou C², Kia SM², Zabihi M², Llera A², Chowdanayaka R⁴, Kumar VJ⁵, Peng H⁶, Laidi C⁷, Batalle D⁸, Dimitrova R⁸, Charman T⁹, Loth E¹⁰, Lai MC¹¹, Jones E¹², Baumeister S¹³, Moessnang C¹³, Banaschewski T¹³, Ecker C¹⁴, Dumas G¹⁵, O'Muircheartaigh J¹⁶, Murphy D¹⁶, Buitelaar JK¹⁷, Marquand AF¹⁸, Beckmann CF¹⁹.

Author information

1

Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, the Netherlands; Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, the Netherlands. Electronic address: t.wolfers@donders.ru.nl.

2

Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, the Netherlands; Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, the Netherlands.

3

Department of Psychiatry, Amsterdam UMC, Amsterdam, the Netherlands.

4

Department of Genetics and Genomics, University of Mysore, Mysuru, India.

5

Max Planck Institute for Biological Cybernetics, Tübingen, Germany.

6

Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, the Netherlands; Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, United Kingdom.

7

Institut National de la Santé et de la Recherche Médicale (INSERM), U955, Institut Mondor de Recherche Biomédicale, Pôle de Psychiatrie, Assistance Publique-Hôpitaux de Paris (AP-HP), Faculté de Médecine de Créteil, DHU PePsy, Hôpitaux Universitaires Mondor, Créteil, France.

8

Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

9

Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.

10

Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.

11

Centre for Addiction and Mental Health and The Hospital for Sick Children, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.

12

Centre for Brain and Cognitive Development, Birkbeck, University of London, London, United Kingdom.

13

Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

14

Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe-University, Frankfurt am Main, Germany; Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.

15

Human Genetics and Cognitive Functions, Institut Pasteur, Université Paris Diderot, Sorbonne Paris Cité, CNRS UMR3571 / USR 3756, Paris, France.

16

Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom.

17

Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, the Netherlands; Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, the Netherlands; Karakter Child and Adolescent Psychiatry University Center, Radboud University Medical Center, Nijmegen, The Netherlands.

18

Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, the Netherlands; Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, the Netherlands; Department of Neuroimaging, Institute of Psychiatry, King's College London, London, United Kingdom.

19

Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, the Netherlands; Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, the Netherlands; Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, United Kingdom.

Abstract

Pattern classification and stratification approaches have increasingly been used in research on Autism Spectrum Disorder (ASD) over the last ten years with the goal of translation towards clinical applicability. Here, we present an extensive scoping literature review on those two approaches. We screened a total of 635 studies, of which 57 pattern classification and 19 stratification studies were included. We observed large variance across pattern classification studies in terms of predictive performance from about 60% to 98% accuracy, which is among other factors likely linked to sampling bias, different validation procedures across studies, the heterogeneity of ASD and differences in data quality. Stratification studies were less prevalent with only two studies reporting replications and just a few showing external validation. In summary, mapping biological differences at the level of the individual with ASD is a major challenge for the field now. Conceptualizing those mappings and individual trajectories that lead to the diagnosis of ASD, will become a major challenge in the near future.

Copyright © 2019. Published by Elsevier Ltd.

PMID:31330196

DOI:10.1016/j.neubiorev.2019.07.010