Age of onset of obsessive-compulsive disorder differentially affects white matter microstructure.

Previous diffusion MRI studies have reported mixed findings on white matter microstructure alterations in obsessive-compulsive disorder (OCD), likely due to variation in demographic and clinical characteristics, scanning methods, and underpowered samples. The OCD global study was created across five international sites to overcome these challenges by harmonizing data collection to identify consistent brain signatures of OCD that are reproducible and generalizable. Single-shell diffusion measures (e.g., fractional anisotropy), multi-shell Neurite Orientation Dispersion and Density Imaging (NODDI) and fixel-based measures, were extracted from skeletonized white matter tracts in 260 medication-free adults with OCD and 252 healthy controls. We additionally performed structural connectome analysis. We compared cases with controls and cases with early (<18) versus late (18+) OCD onset using mixed-model and Bayesian multilevel analysis. Compared with healthy controls, adult OCD individuals showed higher fiber density in the sagittal stratum (B[SE] = 0.10[0.05], P = 0.04) and credible evidence for higher fiber density in several other tracts. When comparing early (n = 145) and late-onset (n = 114) cases, converging evidence showed lower integrity of the posterior thalamic radiation -particularly radial diffusivity (B[SE] = 0.28[0.12], P = 0.03)-and lower global efficiency of the structural connectome (B[SE] = 15.3[6.6], P = 0.03) in late-onset cases. Post-hoc analyses indicated divergent direction of effects of the two OCD groups compared to healthy controls. Age of OCD onset differentially affects the integrity of thalamo-parietal/occipital tracts and the efficiency of the structural brain network. These results lend further support for the role of the thalamus and its afferent fibers and visual attentional processes in the pathophysiology of OCD.

Long-term impact of the COVID-19 pandemic on obsessive-compulsive disorder.

There is limited data on the long-term effect of the COVID-19 pandemic on obsessive-compulsive disorder (OCD). We report on the course of a cohort of individuals with OCD followed-up over a period of one year during the first wave of the COVID-19 pandemic in India. A cohort of 240 individuals registered at a specialty OCD clinic was regularly followed-up using standardized rating tools at three months, six months, and one year into the onset of the COVID-19 pandemic in India. These were compared with clinical ratings recorded in a comparable historical cohort of 207 individuals with OCD, followed up during a non-pandemic year. The pandemic and non-pandemic (historical control) cohorts did not differ in illness severity and rate of relapse. It was found that COVID-19-related anxiety declined over time. Among those patients who were treatment responders prior to the pandemic, COVID-19-related anxiety and non-adherence to medication predicted a relapse of symptoms. Contrary to our expectations, the rate of relapse and illness trajectory in the pandemic cohort did not differ from the non-pandemic cohort, suggesting that the pandemic did not impact our largely medication-adherent cohort. Adherence to treatment seemed to have a protective effect during the pandemic.

The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium.

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohen's d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohen's d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level.

Resting-state functional connectivity correlates of antipsychotic treatment in unmedicated schizophrenia.

BACKGROUND: Antipsychotics may modulate the resting state functional connectivity(rsFC) to improve clinical symptoms in schizophrenia(Sz). Existing literature has potential confounders like past medication effects and evaluating preselected regions/networks. We aimed to evaluate connectivity pattern changes with antipsychotics in unmedicated Sz using Multivariate pattern analysis(MVPA), a data-driven technique for whole-brain connectome analysis. METHODS: Forty-seven unmedicated patients with Sz(DSM-IV-TR) underwent clinical evaluation and neuroimaging at baseline and after 3-months of antipsychotic treatment. Resting-state functional MRI was analysed using group-MVPA to derive 5-components. The brain region with significant connectivity pattern changes with antipsychotics was identified, and post-hoc seed-to-voxel analysis was performed to identify connectivity changes and their association with symptom changes. RESULTS: Connectome-MVPA analysis revealed the connectivity pattern of a cluster localised to left anterior cingulate and paracingulate gyri (ACC/PCG) (peak coordinates:x = -04,y = +30,z = +26;k = 12;cluster-pFWE=0.002) to differ significantly after antipsychotics. Specifically, its connections with clusters of precuneus/posterior cingulate cortex(PCC) and left inferior temporal gyrus(ITG) correlated with improvement in positive and negative symptoms scores, respectively. CONCLUSION: ACC/PCG, a hub of the default mode network, seems to mediate the antipsychotic effects in unmedicated Sz. Evaluating causality models with data from randomised controlled design using the MVPA approach would further enhance our understanding of therapeutic connectomics in Sz.

Cross-national harmonization of neurocognitive assessment across five sites in a global study.

OBJECTIVE: Cross-national work on neurocognitive testing has been characterized by inconsistent findings, suggesting the need for improved harmonization. Here, we describe a prospective harmonization approach in an ongoing global collaborative study. METHOD: Visuospatial N-Back, Tower of London (ToL), Stop Signal task (SST), Risk Aversion (RA), and Intertemporal Choice (ITC) tasks were administered to 221 individuals from Brazil, India, the Netherlands, South Africa, and the USA. Prospective harmonization methods were employed to ensure procedural similarity of task implementation and processing of derived task measures across sites. Generalized linear models tested for between-site differences controlling for sex, age, education, and socioeconomic status (SES). Associations with these covariates were also examined and tested for differences by site with site-by-covariate interactions. RESULTS: The Netherlands site performed more accurately on N-Back and ToL than the other sites, except for the USA site on the N-Back. The Netherlands and the USA sites performed faster than the other three sites during the go events in the SST. Finally, the Netherlands site also exhibited a higher tolerance for delay discounting than other sites on the ITC, and the India site showed more risk aversion than other sites on the RA task. However, effect size differences across sites on the five tasks were generally small (i.e., partial eta-squared < 0.05) after dropping the Netherlands (on ToL, N-Back, ITC, and SST tasks) and India (on the RA task). Across tasks, regardless of site, the N-Back (sex, age, education, and SES), ToL (sex, age, and SES), SST (age), and ITC (SES) showed associations with covariates. CONCLUSIONS: Four out of the five sites showed only small between-site differences for each task. Nevertheless, despite our extensive prospective harmonization steps, task score performance deviated from the other sites in the Netherlands site (on four tasks) and the India site (on one task). Because the procedural methods were standardized across sites, and our analyses were adjusted for covariates, the differences found in cognitive performance may indicate selection sampling bias due to unmeasured confounders. Future studies should follow similar cross-site prospective harmonization procedures when assessing neurocognition and consider measuring other possible confounding variables for additional statistical control. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Global multi-center and multi-modal magnetic resonance imaging study of obsessive-compulsive disorder: Harmonization and monitoring of protocols in healthy volunteers and phantoms.

OBJECTIVES: We describe the harmonized MRI acquisition and quality assessment of an ongoing global OCD study, with the aim to translate representative, well-powered neuroimaging findings in neuropsychiatric research to worldwide populations. METHODS: We report on T1-weighted structural MRI, resting-state functional MRI, and multi-shell diffusion-weighted imaging of 140 healthy participants (28 per site), two traveling controls, and regular phantom scans. RESULTS: Human image quality measures (IQMs) and outcome measures showed smaller within-site variation than between-site variation. Outcome measures were less variable than IQMs, especially for the traveling controls. Phantom IQMs were stable regarding geometry, SNR, and mean diffusivity, while fMRI fluctuation was more variable between sites. CONCLUSIONS: Variation in IQMs persists, even for an a priori harmonized data acquisition protocol, but after pre-processing they have less of an impact on the outcome measures. Continuous monitoring IQMs per site is valuable to detect potential artifacts and outliers. The inclusion of both cases and healthy participants at each site remains mandatory.

Measurement fidelity of clinical assessment methods in a global study on identifying reproducible brain signatures of obsessive-compulsive disorder.

OBJECTIVE: To describe the steps of ensuring measurement fidelity of core clinical measures in a five-country study on brain signatures of obsessive-compulsive disorder (OCD). METHOD: We collected data using standardized instruments, which included the Yale-Brown Obsessive-Compulsive Scale (YBOCS), the Dimensional YBOCS (DYBOCS), the Brown Assessment of Beliefs Scale (BABS), the 17-item Hamilton Depression Scale (HAM-D), the Hamilton Anxiety Scale (HAM-A), and the Structured Clinical Interview for DSM-5 (SCID). Steps to ensure measurement fidelity included translating instruments, developing a clinical decision manual, and continuing reliability training with 11-13 transcripts of each instrument by 13 independent evaluators across sites over 4 years. We use multigroup confirmatory factor analysis (MGCFA) to report interrater reliability (IRR) among the evaluators and factor structure for each scale in 206 participants with OCD. RESULTS: The overall IRR for most scales was high (ICC > 0.94) and remained good to excellent throughout the study. Consistent factor structures (configural invariance) were found for all instruments across the sites, while similarity in the factor loadings for the items (metric invariance) could be established only for the DYBOCS and the BABS. CONCLUSIONS: It is feasible to achieve measurement fidelity of clinical measures in multisite, multilinguistic global studies, despite the challenges inherent to such endeavors. Future studies should not only report IRR but also consider reporting methods of standardization of data collection and measurement invariance to identify factor structures of core clinical measures. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Neurohemodynamic correlates of BDNF gene expression in schizophrenia patients with working memory deficits: A functional MRI study.

INTRODUCTION: Brain-derived neurotrophic factor (BDNF) is involved in neuroplasticity underlying cognitive deficits, including working memory deficits (WMD), in schizophrenia. Methodological challenges and inconsistencies are reported with peripheral BDNF levels. Left dorsolateral prefrontal cortex (DLPFC) is proposed to underlie WMD, though inconsistently. We aimed to explore the correlations between brain activation during working memory task-based functional Magnetic Resonance Imaging (fMRI) and BDNF gene expression in schizophrenia patients with WMD. METHODS: 26 patients with schizophrenia with established WMD were recruited for the study. Blood samples were collected to study lymphocyte BDNF gene expression. Patients underwent task-based fMRI to examine the working memory performance and related brain activation. Whole-brain analysis was performed with 2-back > 0-back and 2-back > rest contrast. The peak intensity values of the activation were used for correlation analysis. RESULTS: Whole brain analysis with 2-back > rest contrast revealed maximum activation in left DLPFC, Brodmann area 9 (t = 10.54, FWE corrected p < 0.05). The baseline BDNF gene expression correlated positively with the peak intensity of brain activation in left DLPFC (r = 0.365, p = 0.033). Negative symptom score negatively correlated with BDNF gene expression (r = -0.499, p = 0.005) and left DLPFC fMRI activation (r = -0.393, p = 0.023) respectively. CONCLUSION: We found a significant positive association between BDNF gene expression and the activation of the DLPFC during the working memory task. This novel observation needs further systematic evaluation to establish the potential role of peripheral BDNF expression in WMD in schizophrenia.

Superior temporal gyrus functional connectivity predicts transcranial direct current stimulation response in Schizophrenia: A machine learning study.

Transcranial direct current stimulation (tDCS) is a promising adjuvant treatment for persistent auditory verbal hallucinations (AVH) in Schizophrenia (SZ). Nonetheless, there is considerable inter-patient variability in the treatment response of AVH to tDCS in SZ. Machine-learned models have the potential to predict clinical response to tDCS in SZ. This study aims to examine the feasibility of identifying SZ patients with persistent AVH (SZ-AVH) who will respond to tDCS based on resting-state functional connectivity (rs-FC). Thirty-four SZ-AVH patients underwent resting-state functional MRI at baseline followed by add-on, twice-daily, 20-min sessions with tDCS (conventional/high-definition) for 5 days. A machine learning model was developed to identify tDCS treatment responders based on the rs-FC pattern, using the left superior temporal gyrus (LSTG) as the seed region. Functional connectivity between LSTG and brain regions involved in auditory and sensorimotor processing emerged as the important predictors of the tDCS treatment response. L1-regularized logistic regression model had an overall accuracy of 72.5% in classifying responders vs. non-responders. This model outperformed the state-of-the-art convolutional neural networks (CNN) model-both without (59.41%) and with pre-training (68.82%). It also outperformed the L1-logistic regression model trained with baseline demographic features and clinical scores of SZ patients. This study reports the first evidence that rs-fMRI-derived brain connectivity pattern can predict the clinical response of persistent AVH to add-on tDCS in SZ patients with 72.5% accuracy.

Emotion Processing Deficit in Euthymic Bipolar Disorder: A Potential Endophenotype.

Background: Emotion processing deficits have been described in patients with bipolar disorder (BD) and are considered one of the core cognitive abnormalities in BD with endophenotype potential. However, the literature on specific impairments in emotion processing cognitive strategies (directive/cortical/higher versus intuitive/limbic/lower) in euthymic adult BD patients and healthy first-degree relatives/high-risk (HR) subjects in comparison with healthy controls (HCs) is sparse. Methods: We examined facial emotion recognition deficits (FERD) in BD (N = 30), HR (N = 21), and HC (N = 30) matched for age (years), years of education, and sex using computer-administered face emotions-Matching And Labeling Task (eMALT). Results: The three groups were significantly different based on labeling accuracy scores for fear and anger (FA) (P < 0.001) and sad and disgust (SD) (P < 0.001). On post-hoc analysis, HR subjects exhibited a significant deficit in the labeling accuracy of FA facial emotions (P < 0.001) compared to HC. The BD group was found to have significant differences in all FA (P = 0.004) and SD (P = 0.003) emotion matching as well as FA (P = 0.001) and SD (P < 0.001) emotion labeling accuracy scores. Conclusions: BD in remission exhibits FERD in general, whereas specific labeling deficits of fear and anger emotions, indicating impaired directive higher order aspect of emotion processing, were demonstrated in HR subjects. This appears to be a potential endophenotype. These deficits could underlie the pathogenesis in BD, with possible frontolimbic circuitry impairment. They may have potential implications in functional recovery and prognosis of BD.

Functional near-infrared spectroscopy in schizophrenia patients with auditory verbal hallucinations: Preliminary observations.

Auditory Signal Detection (ASD) theory postulates that auditory verbal hallucinations (AVH) result from an aberrant association of meaningful connection to abstract noises. In this study, schizophrenia (SZ) patients with persistent AVH (N = 17) and matched controls (N = 25) performed an ASD task with concurrent functional near-infrared spectroscopy recording targetting the left dorsolateral prefrontal cortex (L-DLPFC) and left temporoparietal junction (L-TPJ). During the task, discriminability index had a significant negative correlation, and early deoxyhemoglobin (HbR) latency at L-TPJ positively correlated with AVH scores. Also, patients had significantly lower discriminability, early HbR latency at L-TPJ, and delayed latency at L-DLPFC. This finding suggests the presence of ASD abnormalities and impaired auditory processing in SZ patients with AVH supporting ASD-based pathogenesis.

Prediction of Obsessive-Compulsive Disorder: Importance of Neurobiology-Aided Feature Design and Cross-Diagnosis Transfer Learning.

BACKGROUND: Machine learning applications using neuroimaging provide a multidimensional, data-driven approach that captures the level of complexity necessary for objectively aiding diagnosis and prognosis in psychiatry. However, models learned from small training samples often have limited generalizability, which continues to be a problem with automated diagnosis of mental illnesses such as obsessive-compulsive disorder (OCD). Earlier studies have shown that features incorporating prior neurobiological knowledge of brain function and combining brain parcellations from various sources can potentially improve the overall prediction. However, it is unknown whether such knowledge-driven methods can provide a performance that is comparable to state-of-the-art approaches based on neural networks. METHODS: In this study, we apply a transparent and explainable multiparcellation ensemble learning framework EMPaSchiz (Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction) to the task of predicting OCD, based on a resting-state functional magnetic resonance imaging dataset of 350 subjects. Furthermore, we apply transfer learning using the features found effective for schizophrenia to OCD to leverage the commonality in brain alterations across these psychiatric diagnoses. RESULTS: We show that our knowledge-based approach leads to a prediction performance of 80.3% accuracy for OCD diagnosis that is better than domain-agnostic and automated feature design using neural networks. Furthermore, we show that a selection of reduced feature sets can be transferred from schizophrenia to the OCD prediction model without significant loss in prediction performance. CONCLUSIONS: This study presents a machine learning framework for OCD prediction with neurobiology-aided feature design using resting-state functional magnetic resonance imaging that is generalizable and reasonably interpretable.

Association of SAPAP3 allelic variants with symptom dimensions and pharmacological treatment response in obsessive-compulsive disorder.

Though several SAPAP3 gene knockout studies in mice have implicated its role in compulsivity, human studies have failed to demonstrate its association with obsessive-compulsive disorder (OCD). We examined the association between allelic variants of a single nucleotide polymorphism in the SAPAP3 gene (rs6662980) with specific aspects of the OCD phenotype. A total of 200 individuals with OCD were genotyped using the TaqMan assay. All participants were assessed using the Mini International Neuropsychiatric Interview and the Yale-Brown Obsessive-Compulsive Scale, and their response to serotonin reuptake inhibitors (SRIs) was evaluated over naturalistic treatment and follow-up. After correcting for multiple comparisons, the G allele at rs6662980 was found to be associated with contamination and washing symptoms (p = .003). Logistic regression analysis also showed that presence of the G allele predicted poor response to SRIs (odds ratio [OR] = 2.473, 95% confidence interval [1.157, 5.407], p = .021). Interaction between presence of the G allele and the Contamination and Washing factor score predicted greater SRI resistance (OR = 3.654, [2.761, 4.547], p = .004). We conclude that specific phenotypic manifestations of OCD, which include contamination and washing-related symptoms along with resistance to SRIs, may be affected by variations in the SAPAP3 gene. Limitations of the study are the lack of a dimensional measure for assessing OCD symptoms, the evaluation of treatment response over naturalistic follow-up, and that only a single locus in the SAPAP3 gene was examined. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

An overview of the first 5 years of the ENIGMA obsessive-compulsive disorder working group: The power of worldwide collaboration.

Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive-compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi-site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA-OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA.

Concurrent conventional & high-definition transcranial direct current stimulation for treatment of schizophrenia with co-morbid obsessive-compulsive disorder: A case report.

Non-invasive brain stimulation techniques such as conventional transcranial direct current stimulation (tDCS) and high definition tDCS (HD-tDCS) are increasingly being used as add-on treatment options in schizophrenia and obsessive-compulsive disorder (OCD). This is reporting of the use of a novel accelerated, symptom-specific, add-on tDCS (combining conventional and high definition) protocol in a patient with both schizophrenia and OCD. The intervention showed clinical utility by reducing both schizophrenia and OCD symptoms.

Plasma IL-6 levels in unmedicated, comorbidity free obsessive-compulsive disorder.

BACKGROUND: Obsessive-compulsive disorder (OCD) is increasingly being evaluated for a neuro-immune basis. Interleukin-6 (IL-6) is the most widely studied cytokine with a potential role in altering neurotransmission. The evidence for plasma IL-6 alterations in OCD has yielded mixed results. Psychotropic medications are known to modulate inflammatory processes and cytokine levels. METHODS: In this study, we recruited unmedicated, co-morbidity-free adult OCD patients (n = 49) and sex-matched healthy controls HC (n = 47) and compared their plasma IL-6 levels and their correlation with age at onset, duration of illness, and severity. RESULTS: IL-6 plasma level (ng/ml) in unmedicated OCD patients (1.31 ± 0.67) was significantly greater compared to HC (1.03 ± 0.47) [t = 2.33 (p = 0.02)]. The group differences persisted even after controlling for age and sex [F(1, 91) = 4.57, p = 0.035, η2 = 0.05]. Plasma IL-6 did not correlate significantly with any clinical variables. CONCLUSIONS: This study adds to the existing literature on immune alterations in OCD. Alterations in plasma IL-6 might have implications in the neurotransmitter alterations and stress-response in OCD. The current study results in unmedicated and comorbidity-free OCD patients give us a better understanding of the immune alterations in OCD. Future studies in such a population will probably help in reducing the heterogeneity of findings.

Identification of biomarkers that predict response to subthalamic nucleus deep brain stimulation in resistant obsessive-compulsive disorder: protocol for an open-label follow-up study.

INTRODUCTION: Deep brain stimulation (DBS) of bilateral anteromedial subthalamic nucleus (amSTN) has been found to be helpful in a subset of patients with severe, chronic and treatment-refractory obsessive-compulsive disorder (OCD). Biomarkers may aid in patient selection and optimisation of this invasive treatment. In this trial, we intend to evaluate neurocognitive function related to STN and related biosignatures as potential biomarkers for STN DBS in OCD. METHODS AND ANALYSIS: Twenty-four subjects with treatment-refractory OCD will undergo open-label STN DBS. Structural/functional imaging, electrophysiological recording and neurocognitive assessment would be performed at baseline. The subjects would undergo a structured clinical assessment for 12 months postsurgery. A group of 24 healthy volunteers and 24 subjects with treatment-refractory OCD who receive treatment as usual would be recruited for comparison of biomarkers and treatment response, respectively. Baseline biomarkers would be evaluated as predictors of clinical response. Neuroadaptive changes would be studied through a reassessment of neurocognitive functioning, imaging and electrophysiological activity post DBS. ETHICS AND DISSEMINATION: The protocol has been approved by the National Institute of Mental Health and Neurosciences Ethics Committee. The study findings will be disseminated through peer-reviewed scientific journals and scientific meetings.

Are There Familial Patterns of Symptom Dimensions in Obsessive-Compulsive Disorder?

Background: Obsessive-compulsive disorder (OCD) is a heterogeneous illness, and emerging evidence suggests that different symptom dimensions may have distinct underlying neurobiological mechanisms. We aimed to look for familial patterns in the occurrence of these symptom dimensions in a sample of families with at least two individuals affected with OCD. Methods: Data from 153 families (total number of individuals diagnosed with DSM-5 OCD = 330) recruited as part of the Accelerator Program for Discovery in Brain Disorders using Stem Cells (ADBS) was used for the current analysis. Multidimensional Item Response Theory (IRT) was used to extract dimensional scores from the Yale-Brown Obsessive-Compulsive Scale (YBOCS) checklist data. Using linear mixed-effects regression models, intra-class correlation coefficients (ICC), for each symptom dimension, and within each relationship type were estimated. Results: IRT yielded a four-factor solution with Factor 1 (Sexual/Religious/Aggressive), Factor 2 (Doubts/Checking), Factor 3 (Symmetry/Arranging), and Factor 4 (Contamination/Washing). All except for Factor 1 were found to have significant ICCs, highest for Factor 3 (0.41) followed by Factor 4 (0.29) and then Factor 2 (0.27). Sex-concordant dyads were found to have higher ICC values than discordant ones, for all the symptom dimensions. No major differences in the ICC values between parent-offspring and sib-pairs were seen. Conclusions: Our findings indicate that there is a high concordance of OCD symptom dimensions within multiplex families. Symptom dimensions of OCD might thus have significant heritability. In view of this, future genetic and neurobiological studies in OCD should include symptom dimensions as a key parameter in their analyses.