Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis
Yanli Zhang‐James, Emily C. Helminen, Jinru Liu, The ENIGMA-ADHD Working Group, Geraldo F. Busatto, Anna Calvo, Mara Cercignani, Tiffany M. Chaim‐Avancini, Matt C. Gabel, Neil A. Harrison, Luisa Lázaro, Sara Lera‐Miguel, Mário R. Louzã, Rosa Nicolau, Pedro G. P. Rosa, Martin Schulte-Rutte, Marcus V. Zanetti, Sara Ambrosino, Philip Asherson, Tobias Banaschewski, Baranov Aa, Sarah Baumeister, Ramona Baur‐Streubel, Mark A. Bellgrove, Joseph Biederman, Janita Bralten, Ivanei E. Bramati, Daniel Brandeis, Silvia Brem, Jan K. Buitelaar, F. Xavier Castellanos, Kaylita Chantiluke, Anastasia Christakou, David Coghill, Annette Conzelmann, Ana I. Cubillo, Anders M. Dale, Patrick de Zeeuw, Alysa E. Doyle, Sarah Durston, Eric Earl, Jeffrey N. Epstein, Thomas Ethofer, Damien A. Fair, Andreas J. Fallgatter, Thomas Frodl, Tinatin Yu. Gogberashvili, Jan Haavik, Catharina A. Hartman, Dirk J. Heslenfeld, Pieter J. Hoekstra, Sarah Hohmann, Marie F. Høvik, Neda Jahanshad, Terry L. Jernigan, Bernd Kardatzki, Georgii Karkashadze, Clare Kelly, Gregor Kohls, Kerstin Konrad, Jonna Kuntsi, Klaus‐Peter Lesch, Astri J. Lundervold, Charles B. Malpas, Paulo Mattos, Hazel McCarthy, Mitul A. Mehta, Leyla S. Namazova-Baranova, Joel T. Nigg, Stephanie Novotny, Ruth Tuura, Eileen Oberwelland Weiß, Jaap Oosterlaan, Bob Oranje, Yannis Paloyelis, Paul Pauli, Kerstin Jessica Plessen, Josep Antoni Ramos‐Quiroga, Andreas Reif, Liesbeth Reneman, Katya Rubia, Anouk Schrantee, Lena A. Schwarz, Lizanne Schweren, Jochen Seitz, Philip Shaw, Timothy J. Silk, Norbert Skokauskas, Juan Vila, Michael C. Stevens, Gustavo Sudre, Leanne Tamm, Paul M. Thompson, Fernanda Tovar‐Moll, Theo G.M. van Erp, Alasdair Vance, Óscar Vilarroya, Yolanda Vives‐Gilabert, Georg G. von Polier, Susanne Walitza
Abstract
Attention-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.