Abstract
No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker.
Highlights
IntroductionObsessive-compulsive disorder (OCD) is a severe and debilitating condition that occurs in 2–3% of the
Obsessive-compulsive disorder (OCD) is a severe and debilitating condition that occurs in 2–3% of theBruin et al Translational Psychiatry (2020)10:342population[1]
Results for the main classifications between OCD patients and healthy controls (HC) using neuroimaging data only resulted in area under the receiver operator curve (AUC) of 0.61, while use of covariates only resulted in AUC of 0.58, and using neuroimaging data following correction for covariates resulted in AUC
Summary
Obsessive-compulsive disorder (OCD) is a severe and debilitating condition that occurs in 2–3% of the. It is characterized by recurrent, intrusive, irrational and distressing thoughts (obsessions) and repetitive behaviors or mental acts (compulsions)[2]. Circuits, as well as distributed changes in limbic, parietal and cerebellar regions[4,5]. These findings have recently been confirmed by different meta-analyses and megaanalyses of neuroimaging studies, based on results that were reported in the literature or by using original data within different consortia[6,7,8,9,10]. Inference has been at the group-level, and the small effect sizes reported preclude clinical application
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
