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

Abstract

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.

Fig. 1. A biplot of principal component analysis (PCA) using the diffusion tensor estimates of the major white matter fascicules across the 18 international sites.

A PCA biplot before applying NeuroCombat. (Left: Adult, Right: Pediatric). Some sites (e.g., site B) show apparent clusters distinct from the rest of the sites. B PCA biplot after applying NeuroCombat. (Left: Adult, Right: Pediatric).

Fig. 2. Classification of OCD diagnosis and medication status using diffusion tensor estimates.

A Classification performances in adult samples. B Classification performances in pediatric samples.

Fig. 3. Sample characteristics and prediction performance (ROC AUC) across sites.

A In adult samples. B In pediatric samples. Left: Violin plots of sociodemographic, clinical, and 763 brain features across sites, Right: Box plot of the area under the receiver operating 764 characteristic curve (ROC AUC) for the leave-one-site-out (LOSO) cross validation in the 765 diagnosis classification task (OCD vs. HC).

Fig. 4. Top 10 features of classification models in adults.

A Top 10 features contribute to the classification of OCD from HC in adults. B Top 10 features contribute to the classification of unmedicated OCD from HC in adults. C Top 10 features contribute to the classification of medicated OCD from unmedicated OCD in adults. Note: The color legend represents DTI measures: red for FA, yellow for MD, green for AD, and blue for RD. Regions with multiple DTI measures are highlighted in purple.

Fig. 5. Top 10 features of classification models in pediatrics.

A Top 10 features contribute to the classification of OCD from HC in pediatrics. B Top 10 features contribute to the classification of unmedicated OCD from HC in pediatrics. C Top 10 features contribute to the classification of medicated OCD from unmedicated OCD in pediatrics. Note: The color legend represents DTI measures: red for FA, yellow for MD, green for AD, and blue for RD. Regions with multiple DTI measures are highlighted in purple.