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

Research output: Contribution to journalReview articlepeer-review

Thomas Wolfers, Dorothea L Floris, Richard Dinga, Daan van Rooij, Christina Isakoglou, Seyed Mostafa Kia, Mariam Zabihi, Alberto Llera, Rajanikanth Chowdanayaka, Vinod J Kumar, Han Peng, Charles Laidi, Dafnis Batalle, Ralica Dimitrova, Tony Charman, Eva Loth, Meng-Chuan Lai, Emily Jones, Sarah Baumeister, Caroline Moessnang & 8 more Tobias Banaschewski, Christine Ecker, Guillaume Dumas, Jonathan O'Muircheartaigh, Declan Murphy, Jan K Buitelaar, Andre F Marquand, Christian F Beckmann

Original languageEnglish
Pages (from-to)240-254
Number of pages15
JournalNeuroscience and biobehavioral reviews
Early online date19 Jul 2019
Accepted/In press15 Jul 2019
E-pub ahead of print19 Jul 2019
PublishedSep 2019

Bibliographical note

Copyright © 2019. Published by Elsevier Ltd.


King's Authors


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.

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