Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis
Authors: Zhang-James Yanli , Helminen Emily C. , Liu Jinru ,   The ENIGMA-ADHD Working Group, Busatto Geraldo F. , Calvo Anna , Cercignani Mara , Chaim-Avancini Tiffany M. , Gabel Matt C. , Harrison Neil A. , Lazaro Luisa , Lera-Miguel Sara , Louza Mario R. , Nicolau Rosa , Rosa Pedro G. P. , Schulte-Rutte Martin , Zanetti Marcus V. , Ambrosino Sara , Asherson Philip , Banaschewski Tobias , Baranov Alexandr , Baumeister Sarah , Baur-Streubel Ramona , Bellgrove Mark A. , Biederman Joseph , Bralten Janita , Bramati Ivanei E. , Brandeis Daniel , Brem Silvia , Buitelaar Jan K. , Castellanos Francisco. X. , Chantiluke Kaylita C. , Christakou Anastasia , Coghill David , Conzelmann Annette , Cubillo Ana I. , Dale Anders M. , de Zeeuw Patrick , Doyle Alysa E. , Durston Sarah , Earl Eric A. , Epstein Jeffrey N. , Ethofer Thomas , Fair Damien A. , Fallgatter Andreas J. , Frodl Thomas , Gogberashvili Tinatin , Haavik Jan , Hartman Catharina A. , Heslenfeld Dirk J. , Hoekstra Pieter J. , Hohmann Sarah , Høvik Marie F. , Jahanshad Neda , Jernigan Terry L. , Kardatzki Bernd , Karkashadze Georgii , Kelly Clare , Kohls Gregor , Konrad Kerstin , Kuntsi Jonna , Lesch Klaus-Peter , Lundervold Astri J. , Malpas Charles B. , Mattos Paulo , McCarthy Hazel , Mehta Mitul A. , Namazova-Baranova Leyla , Nigg Joel T. , Novotny Stephanie E. , O’Gorman Tuura Ruth L. , Weiss Eileen Oberwelland , Oosterlaan Jaap , Oranje Bob , Paloyelis Yannis , Pauli Paul , Plessen Kerstin J. , Ramos-Quiroga J. Antoni , Reif Andreas , Reneman Liesbeth , Rubia Katya , Schrantee Anouk , Schwarz Lena , Schweren Lizanne J. S. , Seitz Jochen , Shaw Philip , Silk Tim J. , Skokauskas Norbert , Vila Juan Carlos Soliva , Stevens Michael C. , Sudre Gustavo , Tamm Leanne , Thompson Paul M. , Tovar-Moll Fernanda , van Erp Theo G. M. , Vance Alasdair , Vilarroya Oscar , Vives-Gilabert Yolanda , von Polier Georg G. , Walitza Susanne , Yoncheva Yuliya N. , Ziegler Georg C. , Franke Barbara , Hoogman Martine , Faraone Stephen V. 
Published: February 2021

AbstractAttention-deficit/hyperactivity disorder (ADHD) affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences of the disorder, it is not clear if adults with ADHD have similar neuroanatomical differences as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural differences for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that are common to ADHD in childhood and adulthood. These results support the continuity of ADHD’s brain differences from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity.