Kristen Hagen

Cognitive-behavioral therapy (CBT) is a widely used treatment for mental disorders, yet the biological mechanisms underlying its effects and the factors contributing to treatment response remain poorly understood. DNA methylation, an epigenetic mechanism shaped by both genetic and environmental influences, may provide insights into individual differences in psychotherapy outcomes. We performed an epigenome-wide association study of psychotherapy response in 889 adults with obsessive-compulsive disorder (OCD) receiving the Bergen 4-Day Treatment, an intensive, concentrated exposure-based intervention. Saliva samples were collected before treatment, immediately after treatment, and at 3-month follow-up. DNA methylation was profiled using the Illumina EPIC v2 array. We identified three classes of differentially methylated regions (DMRs): (1) ten baseline DMRs associated with subsequent treatment response, (2) 23 DMRs showing stable associations with response across time points, and (3) three DMRs exhibiting longitudinal methylation changes associated with response. These loci were annotated to genes involved in neuroplasticity, neurodevelopment, stress response, immune function, mitochondrial processes, and gene regulation. Additional sex-stratified analyses identified several sex-specific DNA methylation signals associated with treatment response. Most baseline and time-stable methylation signals were influenced by genetic variation, whereas longitudinal signals showed no significant local genetic effects. In addition, modest shifts in monocyte and CD4+ T-cell proportions were associated with treatment response. These findings suggest that response to exposure-based psychotherapy in OCD is associated with both trait-like and dynamic peripheral epigenetic variation. Pre-treatment DNA methylation profiles may ultimately help predict treatment outcomes and support future precision psychiatry approaches.

Obsessive-compulsive disorder (OCD) has been increasingly linked to alterations in functional connectivity (FC) across large-scale brain networks, particularly the default mode (DMN), salience (SN), and central executive network (CEN), known as the triple-networks. However, little is known about how connectivity patterns evolve following treatment. We examined both static and dynamic resting-state FC in 25 adults with OCD and 21 matched healthy controls (HCs) at baseline, one week, and three months following intensive exposure and response prevention (ERP) using the Bergen 4-Day Treatment (B4DT). Independent component analysis (ICA) and sliding-window approaches were used to evaluate network connectivity within and between the triple networks. At baseline, adults with OCD showed stronger static connectivity within the DMN and SN and spent more time in a dynamic connectivity state characterized by strong connectivity within the DMN and decoupling between the DMN and SN compared to controls. Following the 4-day intensive treatment, these abnormal patterns normalized and remained stable at the three-month follow-up. A higher number of transitions between states was associated with reductions in the severity of OCD, anxiety, and depressive symptoms. Additional correlation analyses indicated that higher baseline SN-CEN connectivity was associated with greater symptom severity, while post-treatment reductions in CEN and CEN-SN static connectivity were linked to improvements in depressive symptoms. These findings suggest that effective ERP promotes a normalization of both static and dynamic connectivity within and between the triple networks. Thus, dynamic metrics, alongside static measures, may serve as clinically meaningful biomarkers of therapeutic response.

Background. Studies applying machine learning to obsessive-compulsive disorder (OCD) typically report accuracy in homogeneous samples but rarely assess model reliability, generalizability, and interpretability needed for clinical use. Methods. We applied a transformer-based deep learning model, the Multi-Band Brain Net, to the ENIGMA-OCD cohort - the largest available resting-state functional magnetic resonance imaging (rs-fMRI) dataset in OCD with 1,706 participants (869 cases with OCD, 837 controls) across 23 sites worldwide. We evaluated model reliability by calculating calibration - the model's ability to "know what it doesn't know". We assessed generalizability using leave-one-site-out validation to test performance on unseen sites with different scanners, acquisition protocols, and patient populations. Finally, we examined interpretability by analyzing model attention weights to identify the neural connectivity patterns that influence model predictions. Results. The model achieved modest but competitive classification performance (AUROC = .653, SD = .039). Crucially, while large-scale pretraining on the UK Biobank (N = 40,783) did not boost accuracy, it significantly enhanced model calibration by reducing overconfident predictions. Leave-one-site-out validation showed a generalization gap across sites (AUROC = .427-.819). Pretraining did not close this gap but removed scanner manufacturer bias. Finally, attention-based mapping identified biologically plausible patterns of widespread hypoconnectivity in OCD relative to healthy controls, particularly in low-frequency bands involving the default mode, salience, and somatomotor networks. These findings aligned with known OCD neurobiology. Conclusions. This study provides a framework for developing more reliable and trustworthy clinical artificial intelligence for OCD.

Objective Cognitive behavioral therapy (CBT) is an effective first-line treatment for obsessive-compulsive disorder (OCD), yet it remains difficult to predict who will respond to this intervention. This study investigates associations between neural activity during inhibitory control tasks and CBT outcomes, and whether task-based fMRI data could serve as a predictive marker of individual CBT response. Methods Using fMRI data from individuals performing an inhibitory control task across five samples (n=130, age range=8-57, 54% female) of the ENIGMA-OCD consortium, univariate associations were analyzed between activity during response inhibition and error processing and three CBT outcomes: response, remission, and pre-post treatment change in symptom severity. Random forest and support vector machine models using leave-one-sample-out cross-validation were used for prediction of CBT response and remission from fMRI activity and clinical data. Results Remission after CBT was associated with weaker activity in default mode regions during response inhibition and in the right supramarginal gyrus during error processing. Greater symptom reduction was linked to weaker pre-treatment activity across frontoparietal, dorsal attention, visual, and subcortical regions during response inhibition, but to stronger default mode activity during error processing. Despite these robust group-level effects, machine learning models failed to predict individual outcomes above chance level with either neuroimaging or clinical data. Conclusion Weaker activity during response inhibition in a widespread network, as well as stronger activity in default mode regions during error processing before treatment, appear beneficial to CBT response. However, these findings cannot yet be translated into individually predictive markers of CBT outcome.

Cognitive behavioral therapy (CBT) is a well‐established, evidence‐based treatment for common mental disorders such as depression, anxiety disorders, and obsessive‐compulsive disorder (OCD). However, treatment outcomes vary widely, and a substantial proportion of patients do not achieve sufficient improvement. Robust predictors of individual differences in symptom change are currently lacking. Genetic differences have been suggested to play a role, but existing evidence is inconclusive. This study investigated the extent to which common genetic variants—single nucleotide polymorphisms (SNPs)—contribute to variability in symptom change. The sample was derived from the MULTI‐PSYCH and NORDiC cohorts, comprising 3113 adults and children treated with CBT for depression, panic disorder, social anxiety disorder, or OCD. We performed a genome‐wide association study (GWAS) of symptom change following CBT and estimated the proportion of variance attributed to SNPs. Secondary analyses included GWAS and SNP‐based heritability estimation of additional clinically relevant outcomes: pre‐ and post‐treatment symptom severity and remission status. No variants reached genome‐wide significance. We estimated SNP‐based heritability of symptom change at = 0.221 (SE = 0.123). These results suggest that common genetic variation may contribute modestly to treatment outcomes. Much larger samples would be required to obtain more precise estimates and to detect genome‐wide significant loci.

Brain disorders are increasingly understood as disorders of distributed brain circuits, yet functional connectivity (FC), the dominant framework for mapping them, treats the brain as a collection of pairwise relationships between regions and cannot represent pathology distributed across coordinated sets of connections. We introduce a Hodge-Laplacian topological framework that localizes higher-order “loop” (1-cycle) organization within functional connectome, maps each loop to specific edges and networks, and yields a subject-level measure of loop expression. Applied to resting-state fMRI from the ENIGMA-OCD consortium (1,024 patients and 1,028 controls across 28 sites), the framework identified 93 loop-level abnormalities in obsessive–compulsive disorder (OCD), concentrated in frontoparietal and somatomotor systems. The edges forming these loops largely showed no significant differences between groups, indicating that the abnormalities were invisible to conventional FC analysis. The frontoparietal and somatomotor loop clusters recurred across the clinical subgroups, suggesting convergence on a shared higher-order phenotype. Robustness analyses showed the loop signal reflected higher-order organization rather than an artifact of individual edges, the network backbone, or any single site. These results indicate that coordinated, multi-edge pathology exists and can be localized even when pairwise analyses fail to detect it, positioning higher-order topology as a generalizable axis for mapping circuit pathology across psychiatric and neurological disorders.

Background: Panic disorder (PD) significantly impacts individuals’ daily lives and overall well-being. While cognitive behavioral therapy (CBT) is the gold standard for PD treatment, there is a growing interest in brief interventions to improve accessibility and reduce treatment burden. This study explored the feasibility and preliminary outcomes of a brief, four-session CBT intervention for PD, grounded in an intention-focused approach. The treatment emphasized modifying patients’ intentions underlying avoidance and safety behaviors during exposure tasks, aiming to enhance engagement and therapeutic effect. Methods: This naturalistic effectiveness study involved 27 patients from the Norwegian Specialist Health Care clinic who were referred for PD treatment. Participants received the Bergen Repeated One-Session Treatment (BrOST), a brief, intention-focused cognitive behavioral intervention delivered in four individual sessions over a period of two to three weeks. Standardized self-report measures were administered to assess the severity of panic symptoms, general anxiety, depressive symptoms, and treatment satisfaction. Results: The treatment resulted in significant reductions in PD severity from pretreatment to one week posttreatment, with sustained improvements at three months. There were also notable reductions in symptoms of anxiety and depression. High levels of treatment satisfaction were reported by the patients. These findings suggest that the BrOST could be a promising alternative to traditional CBT protocols. Conclusion: This study indicated that the BrOST may be a promising brief CBT intervention for individuals with PD. Larger and more controlled studies are warranted. Trial registration: The study was reviewed by the Regional Committee for Medical Research Ethics Northern Norway, REK North (REK Midt 2023/ 701114).

Background: This study investigated the associations among treatment motivation, patient adherence, and treatment outcomes in a group of outpatients with difficult-to-treat obsessive–compulsive disorder (OCD). Methods: A total of 163 relapsed or nonresponding patients were treated with the Bergen 4-day treatment. Motivation was measured with a modified version of the Nijmegen Motivational List 2 (NML2) prior to the start of treatment. During treatment, patients rated their own adherence using the Patient Exposure and Response Prevention (EX/RP) Adherence Scale (PEAS). Treatment outcomes were assessed with the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) at posttreatment and 3-month follow-up. Results: The NML2 items related to commitment showed a weak but significant association with treatment outcomes but were not significant when patient adherence was controlled for. Higher adherence was strongly associated with better treatment outcomes. Discussion: Self-reported motivation before the start of treatment had limited predictive validity, whereas in- and between-session patient adherence, which could reflect one aspect of the motivation construct (treatment engagement), was important for recovery. Trial registration: ClinicalTrials.gov identifier: NCT02656342 (First registered: 2015–11–30).

Background: Obsessive-compulsive disorder (OCD) is a debilitating psychiatric condition influenced by both genetic and environmental risk factors. Epigenetic modifications, such as DNA methylation, may offer insights into biologically meaningful differences associated with the disorder. Methods: We conducted the largest methylome-wide association study (MWAS) of OCD to date, analyzing saliva DNA samples from 414 individuals with OCD and 384 controls using the Illumina EPICv2 array. Differentially methylated positions (DMPs) and regions (DMRs) were identified, with additional analyses including sex-stratified comparisons, methylation quantitative trait loci (mQTL) mapping, and assessments of cell-type composition differences. Results: We identified 35 DMPs and 17 DMRs associated with OCD, mapping to genes involved in neurotransmission, neurodevelopment, synaptic function, and gene regulation. Sex-stratified analyses revealed additional sex-specific methylation signals, highlighting biological differences between males and females. Most associated loci were influenced by genetic variation (mQTLs). Differences in estimated cell composition and the identification of immune-related genes suggest a potential role for immune system processes. Correlation analyses between brain and saliva methylation indicated that several findings may reflect brain-relevant biology. Conclusions: Our findings emphasize the importance of integrating epigenetic, genetic, and sex-specific data to advance our understanding of OCD. DNA methylation may ultimately contribute to progress toward clinically relevant precision medicine approaches.

Background: Treatment readiness factors, such as treatment credibility and expectancy, are postulated to be predictors of outcomes within the context of cognitive behavioral therapy (CBT). Concentrated exposure therapy (cET) is a form of short-term, intensive, exposure-based CBT that has shown promising results. This study investigated whether treatment expectancy and credibility predict cET treatment outcomes in patients with difficult-to-treat (nonresponders and patients with relapse following CBT) obsessive-compulsive disorder (OCD). Methods: A total of 163 patients underwent 4 days of cET treatment. Treatment credibility and expectancy were measured using the Credibility/Expectancy Questionnaire (CEQ) prior to the start of treatment. OCD symptom severity was measured using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) at pretreatment, posttreatment, 3-month follow-up, and 1-year follow-up. Work- and social functioning were measured before treatment and at the 1-year follow-up. Results: Higher CEQ scores were significantly associated with lower Y-BOCS score at posttreatment and follow-up after controlling for age, sex, and pretreatment OCD, anxiety, and depression levels. The CEQ scores were also significantly associated with work- and social functioning at the 1-year follow-up. A receiver operating characteristic analysis suggested a mean item cutoff point of 92.5 (0-100 scale) for the CEQ, and 87% of the patients classified as having high expectancy had a positive treatment response. Conclusions: This study confirmed that treatment expectancy and credibility are predictors of cET outcomes in patients with OCD. Higher scores on the CEQ were linked to better treatment results, both immediately and up to one year later. These insights highlight the need to consider patients’ attitudes toward treatment in the early treatment phase. Trial registration: ClinicalTrials.gov identifier: NCT02656342 (First registered: 2015-11-30).