The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium

Abstract

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.

A closer look to neural pathways and psychopharmacology of obsessive compulsive disorder

“…In a recent study analyzing the resting-state functional connectome of OCD patients, Bruin et al further strengthen findings of regional involvement in the previous studies using machine learning ( Graybiel and Rauch, 2000 ; Milad and Rauch, 2012 ; van den Heuvel et al, 2016 ; Bruin et al, 2023 ). However, their results show a lesser degree of subcortical involvement in OCD and suggest the most significant hypo-connectivity to be found within the cortico-striato-thalamo-cortical (CSTC) sensorimotor network when measured via resting-state fMRI ( Bruin et al, 2023 ). With these new innovative models incorporating machine learning with fMRI to map the involvement of brain areas in OCD patients, new pathways are open in the field of OCD research to locate key regions and identify specific circuitry to target in the development of novel pharmacological treatments and show potential to provide a stronger understanding of the pathophysiology behind OCD.…”

“…In a recent study analyzing the resting-state functional connectome of OCD patients, Bruin et al further strengthen findings of regional involvement in the previous studies using machine learning (Graybiel and Rauch, 2000;Milad and Rauch, 2012;van den Heuvel et al, 2016;Bruin et al, 2023). However, their results show a lesser degree of subcortical involvement in OCD and suggest the most significant hypo-connectivity to be found within the cortico-striatothalamo-cortical (CSTC) sensorimotor network when measured via resting-state fMRI (Bruin et al, 2023).…”

Deep brain stimulation modulates directional limbic connectivity in major depressive disorder

“…Frontostriatal hyperconnectivity has been considered core part of the pathology of OCD (Pauls et al, 2014), whereas multiple studies have suggested that functional connectivity between NAc and vmPFC is reduced in depressed patients (Furman et al, 2011;Liu et al, 2021a;Satterthwaite et al, 2015;Zhou et al, 2022). However, more recent large-scale multicenter studies showed that restingstate connectivity is reduced throughout the brain in both MDD as well as OCD, with the exception of primarily thalamic hyperconnectivity (Bruin et al, 2023;Gallo et al, 2023;Javaheripour et al, 2021). The pathophysiology of MDD and OCD may therefore be more comparable than previously thought.…”

ENIGMA’s simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury

“…For example, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Brain Injury working group (e.g., Dennis et al, 2021 , Dennis et al, 2022 , Olsen et al, 2021 ) has addressed the inconsistent neuroimaging findings in TBI by aggregating MRI data from TBI patients across multiple sites to obtain sufficient power to reliably conduct analyses on MRI data. As one example, Bruin and colleagues (2023) have recently conducted a mega-analysis of rsfMRI data from 1, 024 obsessive compulsive disorder (OCD) patients and 1, 028 healthy controls from 28 independent samples of the ENIGMA-OCD consortium. Their images were analyzed using HALFpipe (Harmonized AnaLysis of Functional MRI pipeline) ( Waller et al, 2022 ), which is an fMRIPrep-based analytical tool modified for the clinical neurosciences ( Esteban et al, 2019 ).…”