Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters
Authors: Bruin Willem B. , Taylor Luke , Thomas Rajat M. , Shock Jonathan P , Zhutovsky Paul , Abe Yoshinari , Alonso Pino , Ameis Stephanie H. , Anticevic Alan , Arnold Paul D. , Assogna Francesca , Benedetti Francesco , Beucke Jan C. , Boedhoe Premika S.W. , Bollettini Irene , Bose Anushree , Brem Silvia , Brennan Brian P. , Buitelaar Jan K , Calvo Rosa , Cheng Yuqi , Cho Kang Ik K. , Dallaspezia Sara , Denys Damiaan , Ely Benjamin A. , Feusner Jamie D. , Fitzgerald Kate D. , Fouche Jean-Paul , Fridgeirsson Egill A. , Gruner Patricia , Gürsel Deniz A. , Hauser Tobias U. , Hirano Yoshiyuki , Hoexter Marcelo Q. , Hu Hao , Huyser Chaim , Ivanov Iliyan , James Anthony , Jaspers-Fayer Fern , Kathmann Norbert , Kaufmann Christian , Koch Kathrin , Kuno Masaru , Kvale Gerd , Kwon Jun Soo , Liu Yanni , Lochner Christine , Lázaro Luisa , Marques Paulo , Marsh Rachel , Martínez-Zalacaín Ignacio , Mataix-Cols David , Menchón José M. , Minuzzi Luciano , Moreira Pedro S. , Morer Astrid , Morgado Pedro , Nakagawa Akiko , Nakamae Takashi , Nakao Tomohiro , Narayanaswamy Janardhanan C. , Nurmi Erika L. , O’Neill Joseph , Pariente Jose C. , Perriello Chris , Piacentini John , Piras Fabrizio , Piras Federica , Reddy Y.C. Janardhan , Rus-Oswald Oana G. , Sakai Yuki , Sato João R. , Schmaal Lianne , Shimizu Eiji , Simpson H. Blair , Soreni Noam , Soriano-Mas Carles , Spalletta Gianfranco , Stern Emily R. , Stevens Michael C. , Stewart S. Evelyn , Szeszko Philip R. , Tolin David F. , Venkatasubramanian Ganesan , Wang Zhen , Yun Je-Yeon , van Rooij Daan ,   ENIGMA-OCD consortium, Thompson Paul M. , van den Heuvel Odile A. , Stein Dan J. , van Wingen Guido A. 
Published: November 2019

Objective

No 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.

Method

We included 46 data sets with neuroimaging and clinical data from adult (≥18 years) and pediatric (<18 years) samples. T1images 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.

Results

Classification 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.

Conclusions

Parcellated 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.