Aug 2026· Psychiatry research. Neuroimaging· Vol 363, pp.
112312
· 0 citations· 58 references
Medicine
TL;DR
Evidence from functional neuroimaging subtyping studies in OCD supports a neuroimaging-based framework for personalized treatment selection but require prospective validation.
Abstract
Obsessive-compulsive disorder (OCD) exhibits substantial clinical heterogeneity that may reflect underlying neurobiological diversity. Neuroimaging-based subtyping may advance precision psychiatry by identifying biologically distinct subgroups with differential treatment responses. This study systematically synthesized evidence from functional neuroimaging subtyping studies in OCD to identify reproducible neurobiological subtypes, characterize their clinical profiles, and establish a consensus-based classification framework. We reviewed 40 original studies employing machine learning, clustering, normative modeling, or classification approaches, encompassing approximately 8,150 patients. Consensus clustering identified three reproducible neurobiological subtypes. The Limbic-Hyperactive subtype, comprising approximately 40% of patients, exhibited amygdala and insula hyperconnectivity, elevated anxiety levels, predominant contamination and washing symptoms, and favorable response to cognitive-behavioral therapy. The Fronto-Striatal-Hypoconnected subtype, comprising approximately 35% of patients, demonstrated reduced orbitofrontal-striatal connectivity, cognitive inflexibility, predominant checking and ordering symptoms, and a favorable response to selective serotonin reuptake inhibitors. The Global-Disrupted subtype, comprising approximately 25% of patients, exhibited widespread connectivity disruption, greater symptom severity, and poor treatment response. Support vector machine classification achieved 81.5% accuracy for subtype assignment, though classification of OCD versus healthy controls showed limited generalizability in multisite settings (AUC 0.567-0.673). These findings support a neuroimaging-based framework for personalized treatment selection but require prospective validation.
Results indicate that multi-omics integration, in addition to explaining the molecular architecture of MDD, also characterizes patient subgroups with pathophysiological mechanisms, dimensions of symptoms, and disease treatment, which demonstrates that there is a shift in psychiatry toward a more mechanistic approach.
Elham Amjad, B. Sokouti· OBM Neurobiology· 0 citations
The findings suggest that robust, individualized brain-based predictions for mental health outcomes remain challenging with the available data and sample size.
Marija Tochadse, Julia Klawohn, Christian Kaufmann et al.· Scientific Reports· 0 citations
BACKGROUNDS
Obsessive-compulsive disorder (OCD) has been consistently associated with alterations in cortico-striato-thalamo-cortical (CSTC) circuits, as demonstrated by numerous resting-state fMRI studies. However, given the high prevalence of comorbid anxiety disorders and anxiety-related traits in OCD patients, prev...
Xiao-Zhu Wei, Jie He, Xun Li et al.· Biological Psychiatry: Cogni...· 0 citations
This approach advances efforts toward precision neuropsychopharmacology by identifying reproducible brain–behavior relationships that may inform treatment selection and mechanistic targeting and provides a scalable framework for biologically informed subtyping in MDD.
K. Dunlop· International Journal of Neu...· 0 citations
Introduction: Obsessive–compulsive disorder (OCD) is clinically heterogeneous, and the neurocognitive characteristics of autogenous and reactive obsessional presentations remain insufficiently understood. This study compared neurocognitive performance and exploratory clinical–cognitive associations in strictly classifi...
Hatice Ayça Kaloğlu, Mehmet Ünler, Buket Koparal et al.· Brain Science· 0 citations
This study provides a data-driven characterization of cognitive heterogeneity in MDD, identifying two cognitive dimensions spanning from relative preservation to widespread impairment, and provides preliminary biological context for interpreting cognitive heterogeneity in MDD.
Yu-Shun Yan, Jia'ao Yu, Liang Zuo et al.· Psychiatry and Clinical Neur...· 0 citations
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