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.

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) "OCD vs. healthy controls" (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) "unmedicated OCD vs. healthy controls" (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) "medicated OCD vs. unmedicated OCD" (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6-79.1 in adults; 35.9-63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research.

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.

Toward a neurocircuit-based taxonomy to guide treatment of obsessive-compulsive disorder.

An important challenge in mental health research is to translate findings from cognitive neuroscience and neuroimaging research into effective treatments that target the neurobiological alterations involved in psychiatric symptoms. To address this challenge, in this review we propose a heuristic neurocircuit-based taxonomy to guide the treatment of obsessive-compulsive disorder (OCD). We do this by integrating information from several sources. First, we provide case vignettes in which patients with OCD describe their symptoms and discuss different clinical profiles in the phenotypic expression of the condition. Second, we link variations in these clinical profiles to underlying neurocircuit dysfunctions, drawing on findings from neuropsychological and neuroimaging studies in OCD. Third, we consider behavioral, pharmacological, and neuromodulatory treatments that could target those specific neurocircuit dysfunctions. Finally, we suggest methods of testing this neurocircuit-based taxonomy as well as important limitations to this approach that should be considered in future research.

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.

Association between tDCS computational modeling and clinical outcomes in depression: data from the ELECT-TDCS trial.

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation intervention investigated for the treatment of depression. Clinical results have been heterogeneous, partly due to the variability of electric field (EF) strength in the brain owing to interindividual differences in head anatomy. Therefore, we investigated whether EF strength was correlated with behavioral changes in 16 depressed patients using simulated electric fields in real patient data from a controlled clinical trial. We hypothesized that EF strength in the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC), brain regions implicated in depression pathophysiology, would be associated with changes in depression, mood and anxiety scores. SimNIBS were used to simulate individual electric fields based on the MRI structural T1-weighted brain scans of depressed subjects. Linear regression models showed, at the end of the acute treatment phase, that simulated EF strength was inversely associated with negative affect in the bilateral ACC (left: ß = - 160.463, CI [- 291.541, - 29.385], p = 0.021; right: ß = - 189.194, CI [- 289.479, - 88.910], p = 0.001) and DLPFC (left: ß = - 93.210, CI [- 154.960, - 31.461], p = 0.006; right: ß = - 82.564, CI [- 142.867, - 22.262], p = 0.011) and with depression scores in the left ACC (ß = - 156.91, CI [- 298.51, - 15.30], p = 0.033). No association between positive affect or anxiety scores, and simulated EF strength in the investigated brain regions was found. To conclude, our findings show preliminary evidence that EF strength simulations might be associated with further behavioral changes in depressed patients, unveiling a potential mechanism of action for tDCS. Further studies should investigate whether individualization of EF strength in key brain regions impact clinical response.

Using supervised machine learning on neuropsychological data to distinguish OCD patients with and without sensory phenomena from healthy controls.

OBJECTIVES: While theoretical models link obsessive-compulsive disorder (OCD) with executive function deficits, empirical findings from the neuropsychological literature remain mixed. These inconsistencies are likely exacerbated by the challenge of high-dimensional data (i.e., many variables per subject), which is common across neuropsychological paradigms and necessitates analytical advances. More unique to OCD is the heterogeneity of symptom presentations, each of which may relate to distinct neuropsychological features. While researchers have traditionally attempted to account for this heterogeneity using a symptom-based approach, an alternative involves focusing on underlying symptom motivations. Although the most studied symptom motivation involves fear of harmful events, 60-70% of patients also experience sensory phenomena, consisting of uncomfortable sensations or perceptions that drive compulsions. Sensory phenomena have received limited attention in the neuropsychological literature, despite evidence that symptoms motivated by these experiences may relate to distinct cognitive processes. METHODS: Here, we used a supervised machine learning approach to characterize neuropsychological processes in OCD, accounting for sensory phenomena. RESULTS: Compared to logistic regression and other algorithms, random forest best differentiated healthy controls (n = 59; balanced accuracy = .70), patients with sensory phenomena (n = 29; balanced accuracy = .59), and patients without sensory phenomena (n = 46; balanced accuracy = .62). Decision-making best distinguished between groups based on sensory phenomena, and among the patient subsample, those without sensory phenomena uniquely displayed greater risk sensitivity compared to healthy controls (d = .07, p = .008). CONCLUSIONS: Results suggest that different cognitive profiles may characterize patients motivated by distinct drives. The superior performance and generalizability of the newer algorithms highlights the utility of considering multiple analytic approaches when faced with complex data. PRACTITIONER POINTS: Practitioners should be aware that sensory phenomena are common experiences among patients with OCD. OCD patients with sensory phenomena may be distinguished from those without based on neuropsychological processes.

Evolution of gamma knife capsulotomy for intractable obsessive-compulsive disorder.

For more than half a century, stereotactic neurosurgical procedures have been available to treat patients with severe, debilitating symptoms of obsessive-compulsive disorder (OCD) that have proven refractory to extensive, appropriate pharmacological, and psychological treatment. Although reliable predictors of outcome remain elusive, the establishment of narrower selection criteria for neurosurgical candidacy, together with a better understanding of the functional neuroanatomy implicated in OCD, has resulted in improved clinical efficacy for an array of ablative and non-ablative intervention techniques targeting the cingulum, internal capsule, and other limbic regions. It was against this backdrop that gamma knife capsulotomy (GKC) for OCD was developed. In this paper, we review the history of this stereotactic radiosurgical procedure, from its inception to recent advances. We perform a systematic review of the existing literature and also provide a narrative account of the evolution of the procedure, detailing how the procedure has changed over time, and has been shaped by forces of evidence and innovation. As the procedure has evolved and adverse events have decreased considerably, favorable response rates have remained attainable for approximately one-half to two-thirds of individuals treated at experienced centers. A reduction in obsessive-compulsive symptom severity may result not only from direct modulation of OCD neural pathways but also from enhanced efficacy of pharmacological and psychological therapies working in a synergistic fashion with GKC. Possible complications include frontal lobe edema and even the rare formation of delayed radionecrotic cysts. These adverse events have become much less common with new radiation dose and targeting strategies. Detailed neuropsychological assessments from recent studies suggest that cognitive function is not impaired, and in some domains may even improve following treatment. We conclude this review with discussions covering topics essential for further progress of this therapy, including suggestions for future trial design given the unique features of GKC therapy, considerations for optimizing stereotactic targeting and dose planning using biophysical models, and the use of advanced imaging techniques to understand circuitry and predict response. GKC, and in particular its modern variant, gamma ventral capsulotomy, continues to be a reliable treatment option for selected cases of otherwise highly refractory OCD.

Toward identifying reproducible brain signatures of obsessive-compulsive profiles: rationale and methods for a new global initiative.

BACKGROUND: Obsessive-compulsive disorder (OCD) has a lifetime prevalence of 2-3% and is a leading cause of global disability. Brain circuit abnormalities in individuals with OCD have been identified, but important knowledge gaps remain. The goal of the new global initiative described in this paper is to identify robust and reproducible brain signatures of measurable behaviors and clinical symptoms that are common in individuals with OCD. A global approach was chosen to accelerate discovery, to increase rigor and transparency, and to ensure generalizability of results. METHODS: We will study 250 medication-free adults with OCD, 100 unaffected adult siblings of individuals with OCD, and 250 healthy control subjects at five expert research sites across five countries (Brazil, India, Netherlands, South Africa, and the U.S.). All participants will receive clinical evaluation, neurocognitive assessment, and magnetic resonance imaging (MRI). The imaging will examine multiple brain circuits hypothesized to underlie OCD behaviors, focusing on morphometry (T1-weighted MRI), structural connectivity (Diffusion Tensor Imaging), and functional connectivity (resting-state fMRI). In addition to analyzing each imaging modality separately, we will also use multi-modal fusion with machine learning statistical methods in an attempt to derive imaging signatures that distinguish individuals with OCD from unaffected siblings and healthy controls (Aim #1). Then we will examine how these imaging signatures link to behavioral performance on neurocognitive tasks that probe these same circuits as well as to clinical profiles (Aim #2). Finally, we will explore how specific environmental features (childhood trauma, socioeconomic status, and religiosity) moderate these brain-behavior associations. DISCUSSION: Using harmonized methods for data collection and analysis, we will conduct the largest neurocognitive and multimodal-imaging study in medication-free subjects with OCD to date. By recruiting a large, ethno-culturally diverse sample, we will test whether there are robust biosignatures of core OCD features that transcend countries and cultures. If so, future studies can use these brain signatures to reveal trans-diagnostic disease dimensions, chart when these signatures arise during development, and identify treatments that target these circuit abnormalities directly. The long-term goal of this research is to change not only how we conceptualize OCD but also how we diagnose and treat it.

Is it time to change the gold standard of obsessive-compulsive disorder severity assessment? Factor structure of the Yale-Brown Obsessive-Compulsive Scale.

OBJECTIVES: The Yale-Brown Obsessive-Compulsive Scale has been considered the gold standard scale to assess obsessive-compulsive disorder severity. Previous studies using exploratory factor analysis and confirmatory factor analysis with this scale showed mixed findings in terms of factor structure and fit of models. Therefore, we used confirmatory factor analysis to compare different Yale-Brown Obsessive-Compulsive Scale models in a large sample aiming to identify the best model fit. METHODS: We assessed adult obsessive-compulsive disorder patients (n = 955) using three measures: Yale-Brown Obsessive-Compulsive Scale severity ratings, the Dimensional Yale-Brown Obsessive-Compulsive Scale and the clinical global impression scale. We tested all factor structures reported by previous studies to investigate which model best fitted the data: one-factor, two-factor, three-factor and their equivalent high-order solutions. We also investigated Yale-Brown Obsessive-Compulsive Scale items correlations with scores from the other measures of obsessive-compulsive disorder severity. RESULTS: Confirmatory factor analysis models presented mediocre to fair goodness-of-fit indexes. Severity items related to resistance to obsessions and compulsions presented low factor loadings. The model with the best fit indexes was a high-order model without obsessive-compulsive disorder resistance items. These items also presented small correlations with other obsessive-compulsive disorder severity measures. CONCLUSION: The obsessive-compulsive disorder field needs to discuss further improvements in the Yale-Brown Obsessive-Compulsive Scale and/or continue to search for better measures of obsessive-compulsive disorder severity.

Caudate volume differences among treatment responders, non-responders and controls in children with obsessive-compulsive disorder.

Treatment response in obsessive-compulsive disorder (OCD) is heterogeneous and the neurobiological underpinnings of such variability are unknown. To investigate this issue, we looked for differences in brain structures possibly associated with treatment response in children with OCD. 29 children with OCD (7-17 years) and 28 age-matched controls underwent structural magnetic resonance imaging. Patients then received treatment with fluoxetine or group cognitive-behavioral therapy during 14 weeks, and were classified as treatment responders or non-responders. The caudate nucleus, thalamus and orbitofrontal cortex were selected a priori, according to previous evidence of their association with OCD and its treatment. Gray matter (GM) volume comparisons between responders, non-responders and controls were performed, controlling for total GM volume. 17 patients were classified as responders. Differences among responders, non-responders and controls were found in both caudate nuclei (both p-values = 0.041), but after Bonferroni correction for multiple comparisons, these findings were non-significant. However, after excluding the effect of an outlier, findings were significant for the right caudate (p = 0.004). Pairwise comparisons showed larger caudate GM volume in responders versus non-responders and controls, bilaterally. The right caudate accounted for 20.2% of the variance in Y-BOCS changes after treatment in a linear regression model, with a positive correlation (p = 0.016). We present a possible neural substrate for treatment response in pediatric OCD, which is in line with previous evidence regarding the caudate nucleus. Considering the limitations, further research is needed to replicate this finding and elucidate the heterogeneity of treatment response in children with OCD (National Clinical Trials Registration Number: NCT01148316).

Brain structural correlates of sensory phenomena in patients with obsessive-compulsive disorder.

BACKGROUND: Sensory phenomena (SP) are uncomfortable feelings, including bodily sensations, sense of inner tension, "just-right" perceptions, feelings of incompleteness, or "urge-only" phenomena, which have been described to precede, trigger or accompany repetitive behaviours in individuals with obsessive-compulsive disorder (OCD). Sensory phenomena are also observed in individuals with tic disorders, and previous research suggests that sensorimotor cortex abnormalities underpin the presence of SP in such patients. However, to our knowledge, no studies have assessed the neural correlates of SP in patients with OCD. METHODS: We assessed the presence of SP using the University of São Paulo Sensory Phenomena Scale in patients with OCD and healthy controls from specialized units in São Paulo, Brazil, and Barcelona, Spain. All participants underwent a structural magnetic resonance examination, and brain images were examined using DARTEL voxel-based morphometry. We evaluated grey matter volume differences between patients with and without SP and healthy controls within the sensorimotor and premotor cortices. RESULTS: We included 106 patients with OCD and 87 controls in our study. Patients with SP (67% of the sample) showed grey matter volume increases in the left sensorimotor cortex in comparison to patients without SP and bilateral sensorimotor cortex grey matter volume increases in comparison to controls. No differences were observed between patients without SP and controls. LIMITATIONS: Most patients were medicated. Participant recruitment and image acquisition were performed in 2 different centres. CONCLUSION: We have identified a structural correlate of SP in patients with OCD involving grey matter volume increases within the sensorimotor cortex; this finding is in agreement with those of tic disorder studies showing that abnormal activity and volume increases within this region are associated with the urges preceding tic onset.

ORBITOFRONTAL THICKNESS AS A MEASURE FOR TREATMENT RESPONSE PREDICTION IN OBSESSIVE-COMPULSIVE DISORDER.

BACKGROUND: Early prediction of treatment response could reduce exposure to ineffective treatments and optimize the use of medical resources. Neuroimaging techniques have been used to identify biomarkers that are predictive of outcomes. The aims of this study were to investigate orbitofrontal cortex (OFC) thickness as a potential morphometric biomarker to discriminate outcomes in obsessive-compulsive disorder (OCD) and then to reexamine this biomarker in an independent cohort METHODS: Using a logistic regression model based on the mean baseline thickness of subregions of the OFC, we estimated the probability of treatment response in 29 treatment-naïve OCD patients who participated in a clinical trial. That algorithm was then tested in an independent cohort of 12 patients with a confirmed diagnosis of refractory OCD RESULTS: Among the treatment-naïve OCD patients, measures of OFC thickness statistically significantly differentiated responders (n = 13) and nonresponders (n = 16), with an overall classification accuracy of ≈80%, a sensitivity of 77% (10/13), and a specificity of 81% (13/16). Of the refractory OCD patients in the second independent cohort, 67% were correctly classified as nonresponders. The most discriminative measures in the initial cohort of treatment-naïve patients were the thicknesses of the left and right medial OFC (P = .009 and P = .028, respectively) CONCLUSIONS: We found OFC thickness to be a strong predictor of treatment response in treatment-naïve OCD patients. Although there are not yet any brain imaging biomarkers with clinical utility, our results highlight the potential of these measures as tools for predicting treatment outcomes in OCD.

Social skills in patients with obsessive-compulsive disorder before and after treatment.

OBJECTIVE: We aim to investigate whether: 1) social skills (SS) are impaired in obsessive-compulsive disorder (OCD); 2) SS would change over the course of treatment; and 3) severity of OCD, age of onset of OCD symptoms and illness duration would be associated with SS impairments. METHODS: 41 treatment-naive patients with OCD and 34 control participants (CP) were assessed using a SS inventory. Patients were reevaluated 12-weeks after standardized treatment. Group differences, as well as the treatment effect on OCD symptomatology over time, were analyzed with independent and paired tests, respectively. OCD severity, age at illness onset and illness duration were tested as predictors of SS. RESULTS: Patients had lower total SS scores compared to controls (p-value < 0.001). After treatment, although OCD symptomatology (p-value < 0.001) improved, there was no statistical difference in SS performance (p-value = 0.673). Earlier age of onset of OCD symptoms predicted worse SS total score (p-value = 0.016). CONCLUSION: This study suggests that, despite the amelioration of OCD symptomatology, there was no alteration in Social Skills (SS) performance. Subsequent treatment investigations incorporating larger sample sizes and extended follow-up periods could elucidate whether enhancements in social skills are likely to manifest over time.

Impact of the COVID-19 pandemic on the symptomatology and routine of medicated patients with obsessive-compulsive disorder.

OBJECTIVES: To study the impact of coronavirus disease 2019 on the routine of patients with obsessive-compulsive disorder (OCD) and changes in symptoms and suicidal-related behavior, mainly in those with cleaning symptoms. METHODS: In this cross-sectional study, 58 patients completed an online self-report questionnaire that included the Obsessive-Compulsive Inventory-Revised, Coronavirus Stress and Traumatic Events Scale, Coronavirus Health Impact Survey, Beck Anxiety and Beck Depression inventories, and Suicide-Related Behaviors Questionnaire. Comparisons were made with another pre-pandemic sample (n=524) regarding the last three measures. RESULTS: During the pandemic, the patients spent more days inside their homes (χ² = 33.39, p = 0.007), changed their alcohol consumption patterns (χ² = 87.6, p < 0.001), and increased social media usage (χ² = 68.83, p < 0.001). Participants with cleaning symptoms did not significantly differ from the others in relation to stress, anxiety/depressive symptoms, or suicidal-related behaviors. Finally, our sample did not differ from an equivalent OCD sample assessed before the pandemic in terms of anxiety and depressive symptom severity or suicidal-related behaviors. CONCLUSION: Overall, patients with OCD showed no lifestyle changes associated with higher stress levels during the pandemic. Patients with and without cleaning symptoms and patients before and during the pandemic presented similar results.

Assessing harmonized intelligence measures in a multinational study.

Studies examining the neurocognitive and circuit-based etiology of psychiatric illness are moving toward inclusive, global designs. A potential confounding effect of these associations is general intelligence; however, an internationally validated, harmonized intelligence quotient (IQ) measure is not available. We describe the procedures used to measure IQ across a five-site, multinational study and demonstrate the harmonized measure's cross-site validity. Culturally appropriate intelligence measures were selected: four short-form Wechsler intelligence tests (Brazil, Netherlands, South Africa, United States) and the Binet Kamat (India). Analyses included IQ scores from 255 healthy participants (age 18-50; 42% male). Regression analyses tested between-site differences in IQ scores, as well as expected associations with sociodemographic factors (sex, socioeconomic status, education) to assess validity. Harmonization (e.g., a priori selection of tests) yielded the compatibility of IQ measures. Higher IQ was associated with higher socioeconomic status, suggesting good convergent validity. No association was found between sex and IQ at any site, suggesting good discriminant validity. Associations between higher IQ and higher years of education were found at all sites except the United States. Harmonized IQ scores provide a measure of IQ with evidence of good validity that can be used in neurocognitive and circuit-based studies to control for intelligence across global sites.

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).