ArticleTranslational psychiatry2020
Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters.
Article in Translational psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 4 of them syntheses that pooled it.
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Who cites it
50 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder.Nature genetics · 2025Pooled it
- Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review.JAMA network open · 2023Pooled it
- Shape analysis of subcortical structures in obsessive-compulsive disorder and the relationship with comorbid anxiety, depression, and medication use: A meta-analysis by the OCD Brain Imaging Consortium.Brain and behavior · 2022Pooled it
- ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.Translational psychiatry · 2020Pooled it
- Regional Cerebellar Volumetrics in Obsessive-Compulsive Disorder: An ENIGMA-OCD Study.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Article
- A 3D Brain Geometry Toolkit for Multisite Neuroimaging Analysis.bioRxiv : the preprint server for biology · 2026Article
- Altered frontal and occipital cortical microstructure in obsessive-compulsive disorder - a multisite mega-analysis.Molecular psychiatry · 2026Article
- Multimodal network localization of brain abnormalities and neuromodulation target identification in obsessive-compulsive disorder.Scientific reports · 2026Article
- Toward trustworthy clinical AI for obsessive-compulsive disorder: reliability, generalizability, and interpretability of a transformer model across the ENIGMA-OCD consortium.medRxiv : the preprint server for health sciences · 2026Article
- Global scientific trends on neuroimaging in obsessive-compulsive disorder in the early twenty-first century: a bibliometric analysis and visualization analysis.Annals of general psychiatry · 2026Review
- Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder.medRxiv : the preprint server for health sciences · 2025Article
- Brain Network Abnormalities in Obsessive-Compulsive Disorder: Insights from Edge Functional Connectivity Analysis.Behavioral sciences (Basel, Switzerland) · 2025Article
- Altered eotaxin-1 and interleukin-34 levels in obsessive-compulsive disorder: a case-control observational study in Bangladesh.Osong public health and research perspectives · 2025Article
- Unraveling Gender Differences in Obsessive-Compulsive Disorder: A Focus on Key Micronutrients.Cureus · 2025Article
- Adaptive Whole-Brain Dynamics Predictive Method: Relevancy to Mental Disorders.Research (Washington, D.C.) · 2025Article
- Artificial Intelligence in Obsessive-Compulsive Disorder: A Systematic Review.Current treatment options in psychiatry · 2025Review
- Ketogenic Diet as a Nutritional Metabolic Intervention for Obsessive-Compulsive Disorder: A Narrative Review.Nutrients · 2024Review
- Current best practices and future opportunities for reproducible findings using large-scale neuroimaging in psychiatry.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions.Human brain mapping · 2024Article
- Atypical neurocognitive functioning in children and adolescents with obsessive-compulsive disorder (OCD).European child & adolescent psychiatry · 2024Article
Corrections and comments
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Authors and funding
92 authors.
Funding
Abstract
No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker.
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