White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group
Authors: Kim Bo-Gyeom , Kim Gakyung , Abe Yoshinari , Alonso Pino , Ameis Stephanie , Anticevic Alan , Arnold Paul D. , Balachander Srinivas , Banaj Nerisa , Bargalló Nuria , Batistuzzo Marcelo C. , Benedetti Francesco , Bertolín Sara , Beucke Jan Carl , Bollettini Irene , Brem Silvia , Brennan Brian P. , Buitelaar Jan K. , Calvo Rosa , Castelo-Branco Miguel , Cheng Yuqi , Chhatkuli Ritu Bhusal , Ciullo Valentina , Coelho Ana , Couto Beatriz , Dallaspezia Sara , Ely Benjamin A. , Ferreira Sónia , Fontaine Martine , Fouche Jean-Paul , Grazioplene Rachael , Gruner Patricia , Hagen Kristen , Hansen Bjarne , Hanna Gregory L. , Hirano Yoshiyuki , Höxter Marcelo Q. , Hough Morgan , Hu Hao , Huyser Chaim , Ikuta Toshikazu , Jahanshad Neda , James Anthony , Jaspers-Fayer Fern , Kasprzak Selina , Kathmann Norbert , Kaufmann Christian , Kim Minah , Koch Kathrin , Kvale Gerd , Kwon Jun Soo , Lazaro Luisa , Lee Junhee , Lochner Christine , Lu Jin , Manrique Daniela Rodriguez , Martínez-Zalacaín Ignacio , Masuda Yoshitada , Matsumoto Koji , Maziero Maria Paula , Menchón Jose M. , Minuzzi Luciano , Moreira Pedro Silva , Morgado Pedro , Narayanaswamy Janardhanan C. , Narumoto Jin , Ortiz Ana E. , Ota Junko , Pariente Jose C. , Perriello Chris , Picó-Pérez Maria , Pittenger Christopher , Poletti Sara , Real Eva , Reddy Y. C. Janardhan , van Rooij Daan , Sakai Yuki , Sato João Ricardo , Segalas Cinto , Shavitt Roseli G. , Shen Zonglin , Shimizu Eiji , Shivakumar Venkataram , Soreni Noam , Soriano-Mas Carles , Sousa Nuno , Sousa Mafalda Machado , Spalletta Gianfranco , Stern Emily R. , Stewart S. Evelyn , Szeszko Philip R. , Thomas Rajat , Thomopoulos Sophia I. , Vecchio Daniela , Venkatasubramanian Ganesan , Vriend Chris , Walitza Susanne , Wang Zhen , Watanabe Anri , Wolters Lidewij , Xu Jian , Yamada Kei , Yun Je-Yeon , Zarei Mojtaba , Zhao Qing , Zhu Xi ,   ENIGMA-OCD Working Group, Arai Honami , Araújo Ana Isabel , Araki Kentaro , Arnold Paul D. , Baker Justin T. , Bargalló Núria , Bertolín Sara , Best John R. , Boedhoe Premika S. W. , Bölte Sven , Brecke Vilde , Buitelaar Jan K. , Calvo Rosa , Cappi Carolina , Castelhano Joao , Chen Wei , Chihiro Sutoh , Cho Kang Ik Kevin , Choi Sunah , Costa Daniel , Dai Nan , Dalvie Shareefa , Denys Damiaan , Diniz Juliana B. , Duarte Isabel C. , Federico Calesella , Feusner Jamie D. , Fitzgerald Kate D. , Fridgeirsson Egill Axfjord , Grünblatt Edna , Hamatani Sayo , Hanna Gregory , He Mengxin , van den Heuvel Odile A. , Höxter Marcelo Q. , Hough Morgan , Ikari Keisuke , Ipser Jonathan , Jiang Hongyan , Jiang Linling , de Joode Niels T. , Kathmann Norbert , Kim Taekwan , Kitagawa Hitomi , Kuno Masaru , Bin Kwak Yoo , Kwon Jun Soo , van Leeuwen Wieke , Li Chiang-shan Ray , Li Na , Liu Yanni , liu Fang , Lopes Antonio Carlos , Lu Jin , Milaneschi Yuri , van Marle Hein , Mas Sergi , Mataix-Cols David , de Mathis Maria Alice , Mazieiro Maria Paula , Medland Sarah , Melo Renata , Miguel Euripedes C. , Morer Astrid , De Nadai Alessandro S. , Nakao Tomohiro , Nihei Masato , Norman Luke , Nurmi Erika L. , O’Neil Joseph , Oh Sanghoon , Okawa Sho , Piacentini John C. , Picó-Pérez Maria , Rodriguez Natalia , van Rooij Daan , Sato João R. , Segalas Cinto , Silva Renata , Soreni Noam , Stevens Michael , van der Straten Anouk , Takahashi Jumpei , Tanamatis Tais , Tang Jinsong , Thorsen Anders Lillevik , Tolin David , Uhlmann Anne , Vai Benedetta , van der Werf Ysbrand D. , Veltman Dick J. , Vetter Nora , Wang Jicai , Weeland Cees J. , van Wingen Guido A. , de Wit Stella J. , Wolff Nicole , Xu Xiufeng , Yoshida Tokiko , Zhang Fengrui , Thompson Paul M. , Bruin Willem B. , van Wingen Guido A. , Piras Federica , Piras Fabrizio , Stein Dan J. , van den Heuvel Odile A. , Simpson Helen Blair , Marsh Rachel , Cha Jiook 
Published: February 2024

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) “OCD vs. healthy controls” (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) “unmedicated OCD vs. healthy controls” (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) “medicated OCD vs. unmedicated OCD” (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6–79.1 in adults; 35.9–63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research.