Resolving heterogeneity in obsessive–compulsive disorder through individualized differential structural covariance network analysis. (25th April 2022) - Han, Shaoqiang; Xu, Yinhuan; Guo, Hui-Rong; Fang, Keke; Wei, Yarui; Liu, Liang; Cheng, Junying; Zhang, Yong; Cheng, Jingliang
Abstract: Background: The high heterogeneity of obsessive–compulsive disorder (OCD) denies attempts of traditional case–control studies to derive neuroimaging biomarkers indicative of precision diagnosis and treatment. Methods: To handle the heterogeneity, we uncovered subject-level altered structural covariance by adopting individualized differential structural covariance network (IDSCN) analysis. The IDSCN measures how structural covariance edges in a patient deviated from those in matched healthy controls (HCs) yielding subject-level differential edges. One hundred patients with OCD and 106 HCs were recruited and whose T1-weighted anatomical images were acquired. We obtained individualized differential edges and then clustered patients into subtypes based on these edges. Results: Patients presented tremendously low overlapped altered edges while frequently shared altered edges within subcortical–cerebellum network. Two robust neuroanatomical subtypes were identified. Subtype 1 presented distributed altered edges while subtype 2 presented decreased edges between default mode network and motor network compared with HCs. Altered edges in subtype 1 predicted the total Yale-Brown Obsessive Compulsive Scale score while that in subtype 2 could not. Conclusions: We depict individualized structural covariance aberrance and identify that altered connections within subcortical–cerebellum network are shared by most patients with OCD. These 2 subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of OCD.