Abstract
INTRODUCTION: Obsessive-Compulsive Personality Disorder (OCPD) is a complex mental condition marked by excessive perfectionism, orderliness, and rigidity, often starting in adolescence or early adulthood; it affects 1.9% to 7.8% of the population. The disorder differs from Obsessive-Compulsive Disorder (OCD) in an apparent compromise of personality, distorted self-representation, and altered perception of others. Although the two disorders present evident differences, unlike OCD, the neural bases of OCPD are understudied. The few studies conducted so far have identified gray matter alterations in brain regions such as the striatum and prefrontal cortex. However, a comprehensive model of its neurobiology and the eventual contribution of white matter abnormalities are still unclear. One intriguing hypothesis is that regions ascribed to the Default Mode Network are involved in OCPD, similar to what has been shown for OCD and other anxiety disorders. METHODS: To test this hypothesis, the gray and white matter images of 30 individuals diagnosed with OCPD (73% female, mean age=29.300), and 34 non-OCPD controls (82% female, mean age = 25.599) were analyzed for the first time with a data fusion unsupervised machine learning method known as Parallel Independent Component Analysis (pICA) to detect the joint contribution of these modalities to the OCPD diagnosis. RESULTS: Results indicated that two gray matter networks (GM-05 and GM-23) and one white matter network (WM-25) differed between the OCPD and the control group. GM-05 included brain regions belonging to the Default Mode Network and the Salience Network and was significantly correlated with anxiety; GM-23 included portions of the cerebellum, the precuneus, and the fusiform gyrus; WM-25 included white matter portions adjacent to Default Mode Network regions. DISCUSSION: These findings shed new light on the gray and white matter contributions to OCPD and may pave the way to developing objective markers of this disorder.