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Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters

By Willem B. Bruin, Luke Taylor, Rajat Mani Thomas, Jonathan P Shock, Paul Zhutovsky, Yoshinari Abe, Pino Alonso, Stephanie H Ameis, Alan Anticevic, Paul D Arnold, Francesca Assogna, Francesco Benedetti, Jan C. Beucke, Premika SW Boedhoe, Irene Bollettini, Anushree Bose, Silvia Brem, Brian P. Brennan, Jan K. Buitelaar, Rosa Calvo, Yuqi Cheng, Kang Ik K. Cho, Sara Dallaspezia, Damiaan Denys, Benjamin A. Ely, Jamie D. Feusner, Kate D. Fitzgerald, Jean-Paul Fouche, Egill A. Fridgeirsson, Patricia Gruner, Deniz A. Gürsel, Tobias U Hauser, Yoshiyuki Hirano, Marcelo Q. Hoexter, Hao Hu, Chaim Huyser, Iliyan Ivanov, Anthony James, Fern Jaspers-Fayer, Norbert Kathmann, Christian Kaufmann, Kathrin Koch, Masaru Kuno, Gerd Kvale, Jun Soo Kwon, Yanni Liu, Christine Lochner, Luisa Lázaro, Paulo Marques, Rachel Marsh, Ignacio Martínez-Zalacaín, David Mataix-Cols, José M Menchón, Luciano Minuzzi, Pedro S Moreira, Astrid Morer, Pedro Morgado, Akiko Nakagawa, Takashi Nakamae, Tomohiro Nakao, Janardhanan C. Narayanaswamy, Erika L. Nurmi, Joseph O’Neill, Jose C Pariente, Chris Perriello, John Piacentini, Fabrizio Piras, Federica Piras, Y.C. Janardhan Reddy, Oana G. Rus-Oswald, Yuki Sakai, Joao Ricardo Sato, Lianne Schmaal, Eiji Shimizu, H. Blair Simpson, Noam Soreni, Carles Soriano-Mas, Gianfranco Spalletta, Emily R. Stern, Michael C. Stevens, S. Evelyn Stewart, Philip R. Szeszko, David F. Tolin, Ganesan Venkatasubramanian, Zhen Wang, Je-Yeon Yun, Daan van Rooij, ENIGMA-OCD consortium, Paul M. Thompson, Odile A. van den Heuvel, Dan J. Stein, Guido A. van Wingen

Posted 26 Nov 2019
medRxiv DOI: 10.1101/19012567

ObjectiveNo diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Magnetic resonance imaging (MRI) studies have provided evidence for structural abnormalities in distinct brain regions, but effect sizes are small and have limited clinical relevance. To investigate whether individual patients can be distinguished from healthy controls, we performed multivariate analysis of structural neuroimaging data from the ENIGMA-OCD consortium. MethodWe included 46 data sets with neuroimaging and clinical data from adult ([&ge;]18 years) and pediatric (<18 years) samples. T1 images from 2,304 OCD patients and 2,068 healthy controls were analyzed using standardized processing to extract regional measures of cortical thickness, surface area and subcortical volume. Machine learning classification performance was tested using cross-validation, and possible effects of clinical variables were investigated by stratification. ResultsClassification performance for OCD versus controls using the complete sample with different classifiers and cross-validation strategies was poor (AUC--0.57 (standard deviation (SD)=0.02;Pcorr=0.19) to 0.62 (SD=0.03;Pcorr<.001)). When models were validated on completely new data from other sites, model performance did not exceed chance-level (AUC--0.51 (SD=0.11;Pcorr>.99) to 0.54 (SD=0.08;Pcorr>.99)). In contrast, good classification performance (>0.8 AUC) was achieved within subgroups of patients split according to their medication status. ConclusionsParcellated structural MRI data do not enable good distinction between patients with OCD and controls. However, classifying subgroups of patients based on medication status enables good identification at the individual subject level. This underlines the need for longitudinal studies on the short- and long-term effects of medication on brain structure.

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