OBJECTIVE: We aimed to determine whether individuals with obsessive-compulsive disorder (OCD) and demographically matched healthy individuals can be clustered into distinct clinical subtypes based on dimensional measures of their self-reported compulsivity (OBQ-44 and IUS-12) and impulsivity (UPPS-P). METHODS: Participants (n=217) were 103 patients with a clinical diagnosis of OCD; 79 individuals from the community who were "OCD-likely" according to self-report (Obsessive-Compulsive Inventory-Revised scores equal or greater than 21); and 35 healthy controls. All data were collected between 2013 and 2015 using self-report measures that assessed different aspects of compulsivity and impulsivity. Principal component analysis revealed two components broadly representing an individual's level of compulsivity and impulsivity. Unsupervised clustering grouped participants into four subgroups, each representing one part of an orthogonal compulsive-impulsive phenotype. RESULTS: Clustering converged to yield four subgroups: one group low on both compulsivity and impulsivity, comprised mostly of healthy controls and demonstrating the lowest OCD symptom severity; two groups showing roughly equal clinical severity, but with opposing drivers (i.e., high compulsivity and low impulsivity, and vice versa); and a final group high on both compulsivity and impulsivity and recording the highest clinical severity. Notably, the largest cluster of individuals with OCD was characterized by high impulsivity and low compulsivity. Our results suggest that both impulsivity and compulsivity mediate obsessive-compulsive symptomatology. CONCLUSIONS: Individuals with OCD can be clustered into distinct subtypes based on measures of compulsivity and impulsivity, with the latter being found to be one of the more defining characteristics of the disorder. These dimensions may serve as viable and novel treatment targets.
OBJECTIVE: We aimed to determine whether individuals with obsessive-compulsive disorder (OCD) and demographically matched healthy individuals can be clustered into distinct clinical subtypes based on dimensional measures of their self-reported compulsivity (OBQ-44 and IUS-12) and impulsivity (UPPS-P). METHODS:Participants (n=217) were 103 patients with a clinical diagnosis of OCD; 79 individuals from the community who were "OCD-likely" according to self-report (Obsessive-Compulsive Inventory-Revised scores equal or greater than 21); and 35 healthy controls. All data were collected between 2013 and 2015 using self-report measures that assessed different aspects of compulsivity and impulsivity. Principal component analysis revealed two components broadly representing an individual's level of compulsivity and impulsivity. Unsupervised clustering grouped participants into four subgroups, each representing one part of an orthogonal compulsive-impulsive phenotype. RESULTS: Clustering converged to yield four subgroups: one group low on both compulsivity and impulsivity, comprised mostly of healthy controls and demonstrating the lowest OCD symptom severity; two groups showing roughly equal clinical severity, but with opposing drivers (i.e., high compulsivity and low impulsivity, and vice versa); and a final group high on both compulsivity and impulsivity and recording the highest clinical severity. Notably, the largest cluster of individuals with OCD was characterized by high impulsivity and low compulsivity. Our results suggest that both impulsivity and compulsivity mediate obsessive-compulsive symptomatology. CONCLUSIONS: Individuals with OCD can be clustered into distinct subtypes based on measures of compulsivity and impulsivity, with the latter being found to be one of the more defining characteristics of the disorder. These dimensions may serve as viable and novel treatment targets.
Authors: Lucy Albertella; Mike E Le Pelley; Samuel R Chamberlain; Fred Westbrook; Rico S C Lee; Leonardo F Fontenelle; Jon E Grant; Rebecca A Segrave; Eugene McTavish; Murat Yücel Journal: J Behav Ther Exp Psychiatry Date: 2020-05-01
Authors: Christine Lochner; Lucy Albertella; Martin Kidd; Zelal Kilic; Konstantinos Ioannidis; Jon E Grant; Murat Yücel; Dan J Stein; Samuel R Chamberlain Journal: J Psychiatr Res Date: 2022-06-28 Impact factor: 5.250
Authors: Linden Parkes; Jeggan Tiego; Kevin Aquino; Leah Braganza; Samuel R Chamberlain; Leonardo F Fontenelle; Ben J Harrison; Valentina Lorenzetti; Bryan Paton; Adeel Razi; Alex Fornito; Murat Yücel Journal: Neuroimage Date: 2019-08-02 Impact factor: 6.556
Authors: Ilana Frydman; Paulo Mattos; Ricardo de Oliveira-Souza; Murat Yücel; Samuel R Chamberlain; Jorge Moll; Leonardo F Fontenelle Journal: Compr Psychiatry Date: 2019-12-16 Impact factor: 3.735
Authors: Lucy Albertella; Kristian Rotaru; Erynn Christensen; Amelia Lowe; Mary-Ellen Brierley; Karyn Richardson; Samuel R Chamberlain; Rico S C Lee; Edouard Kayayan; Jon E Grant; Sam Schluter-Hughes; Campbell Ince; Leonardo F Fontenelle; Rebecca Segrave; Murat Yücel Journal: Front Psychiatry Date: 2021-02-23 Impact factor: 4.157