Na Liu

Obsessive-compulsive disorder (OCD) is a complex psychiatric disorder. While existing studies have revealed abnormalities in brain structure and function associated with OCD, there is a paucity of research integrating these two aspects, and the transcriptional patterns underlying these abnormalities remain unclear. This study is a multiscale, exploratory investigation designed to generate hypotheses rather than to test causal mechanisms. We aimed to investigate aberrations in brain structure–function coupling (SFC) in OCD patients and, by integrating gene expression profiles and neurotransmitter maps, to explore the potential molecular and genetic bases of these changes. We recruited 100 medication-free OCD patients and 90 healthy controls, and employed multimodal imaging techniques to systematically analyze abnormalities in static SFC in OCD patients. Subsequently, we conducted transcriptomic analysis to identify genes associated with SFC abnormalities and performed spatial correlation analysis with neurotransmitter atlases to investigate potential links between SFC dysregulation and transcriptional patterns. Our findings demonstrated that OCD patients exhibit significant SFC abnormalities in the right temporoparietal junction (rTPJ). These SFC abnormalities are significantly associated with 2,421 gene expression profiles and the serotonin neurotransmitter system. Gene enrichment analysis revealed that these aberrant genes are primarily involved in key biological processes, such as brain development, synaptic signaling, cell projection development, and regulation of neuronal processes. By integrating multimodal imaging, transcriptomic, and neurotransmitter data, this study provides multiscale evidence for the potential molecular basis of SFC abnormalities in the rTPJ of OCD patients, offering preliminary insights into a possible pathological pathway of OCD.

Background: Depressive symptoms are highly prevalent in individuals with obsessive-compulsive disorder (OCD) and substantially complicate clinical management. However, the feature structure associated with depressive symptoms in OCD remains insufficiently characterized, particularly from an integrative, multivariate perspective. This study aimed to identify key features associated with depressive symptoms in OCD and to elucidate their interrelationships using machine learning and network analysis. Methods: A multicenter sample of 1,293 patients with OCD was recruited from 15 specialized OCD clinics across China. An extreme gradient boosting (XGBoost) model was developed to predict depressive symptoms, with hyperparameter optimization conducted using Optuna and feature contributions quantified via SHAP values. Multivariable logistic regression was used to examine independent associations, and network analysis was applied to explore the co-occurrence structure among key features. Results: The XGBoost model identified anxiety, psychosocial functioning, mental state, obsessing, functional impairment, perceived stress, and gender as the most informative features associated with depressive symptoms in OCD. SHAP analyses indicated that higher anxiety levels, poorer psychosocial functioning, and a more negative self-rated mental state contributed most strongly to increased predicted risk. Network analysis further demonstrated that anxiety, mental state, obsessing, and psychosocial functioning occupied central positions within the network. Anxiety showed prominent bridging properties, exhibiting strong associations with obsessing, perceived stress, and mental state, suggesting its integrative role across emotional, cognitive, and functional domains. Conclusions: Depressive symptoms in OCD are embedded within a tightly interconnected configuration of emotional, cognitive, and functional features, with anxiety occupying a central and bridging position across analytical approaches. The combined application of machine learning and network analysis provides a complementary framework for identifying salient features and elucidating their interrelationships in OCD patients with depressive symptoms, with potential implications for clinical assessment and targeted intervention.

Objective Obsessive–compulsive disorder (OCD) is a neurodevelopmental disorder, related to the central insulin signaling pathway. We investigate the relationship among central insulin signaling pathway gene polymorphisms/brain functional and clinical features in early-onset OCD(EO-OCD). Methods Candidate single nucleotide polymorphisms(SNPs) were genotyped and functional magnetic resonance imaging (FMRI) was performed EO-OCD and HCs. The MATRICS Consensus Cognitive Battery (MCCB) was used to evaluate those groups, and a mediating effect model to explore the relationship among polymorphisms-brain functional-clinical features in EO-OCD. Results In EO-OCD, Rac GTPase-activating protein 1(RACGAP1) rs297941 was the key polymorphism to insulin signaling pathway. The amplitude of low-frequency fluctuation (ALFF) in right precuneus were greater in EO-OCD patients with an A allele than the GG genotype and the ALFF in right supramarginal and postcentral was decreased. The functional connectivity (FC) between right supramarginal and left/right supplementary motor areas, between right cerebellum and left angular of inferior parietal border, and between left angular and right cerebellum was enhanced in A allele. The mediating effect model showed rs297941 influenced information processing speed and obsessive thoughts through intermediary effects of ALFF in right postcentral and enhanced FC between left angular and right cerebellum. Conclusion Rs297941 was signiffcantly to EO-OCD. Abnormal FC/ALFF play a mediating role between rs297941 and information processing speed in EO-OCD.

Background: Sensory phenomena (SP) affect 60%–80% of obsessive‐compulsive (OC) disorder (OCD) patients, demonstrate dimension‐specific symptom associations, yet their mechanistic role in OCD’s network architecture remains unexamined. Methods: In this cross‐sectional study, 1350 clinician‐diagnosed OCD patients from the China OCD Cohort (COCC) underwent standardized assessments using the University of São Paulo SP Scale (USP‐SPS), Yale‐Brown OC Scale (Y‐BOCS), OC Inventory‐Revised (OCI‐R), and Beck Depression Inventory‐II/Beck Anxiety Inventory (BDI‐II/BAI). Network analysis was utilized to identify core/bridge symptoms and test network differences across early/late‐onset and SP‐severity subgroups. Results: SP‐positive OCD patients ( n = 850) demonstrated earlier disease onset ( p < 0.001), more severe compulsions ( p = 0.010), and greater depression than SP‐negative patients ( n = 500). Network analysis in the SP‐positive cohort identified SP symptoms as central network drivers, though with considerable heterogeneity across subtypes: muscle‐joint/bone sensation (strength = 3.41) and sound “just‐right” (strength = 2.73) exhibited the highest centrality, while other SP subtypes showed more modest or selective connectivity. Anxiety was the primary bridge symptom (bridge strength = 1.60), with the strongest cross‐domain link between “look ‘just‐right’” and “ordering.” The network architecture remained stable across subgroups, though elevated SP severity significantly increased global connectivity ( S = 5.343, p = 0.002) without altering topology. Conclusion: SP may represent a clinically meaningful dimension of OCD psychopathology, within which SP subtypes operate as a heterogeneous set of experiences rather than a uniform construct, differentially shaping symptom connectivity. Anxiety serves as a critical bridge between SP and OC symptoms, while SP severity functions as a symptom network intensifier rather than a structural reorganizer. Future studies should explore whether precision interventions targeting anxiety and sensory‐channel‐specific pathways may improve treatment outcomes for refractory OCD with SP. Trial Registration: Chinese Clinical Trial Registry: ChiCTR2100051536

This study aimed to assess the reliability and validity of the Chinese version of The University of São Paulo Sensory Phenomena Scale (USP-SPS). A total of 256 participants (including 184 patients with obsessive-compulsive disorder (OCD) and 72 healthy controls) completed USP-SPS, Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Obsessive-Compulsive Inventory-Revised (OCI-R), Beck Depression Inventory Revised (BDI-II), and Beck Anxiety Inventory (BAI). The internal consistency, test-retest reliability (assessed in a 30-participant subsample over a 1-week interval), the structural validity, and convergent and discriminant validity of the USP-SPS were measured. Exploratory factor analysis yielded a six-factor structure accounting for 59.87% of the total variance, with all items demonstrating salient factor loadings (range = 0.48-0.86). The Chinese version of the USP-SPS severity scale showed moderate correlations with the OCI-R total score (r = 0.35), ordering (r = 0.35), mental neutralisation (r = 0.31), and BAI (r = 0.31), all p < 0.001. Psychometric evaluation demonstrated excellent internal consistency (Cronbach's α = 0.94 for the severity scale in the OCD cohort; KR-20 = 0.80 for the symptom checklist in all participants) and good test-retest reliability (ICC = 0.77) over a 1-week interval. The Chinese version of USP-SPS is a reliable and valid assessment of sensory phenomena in patients with OCD.