Brain Network Segregation is Associated with Drug Use Severity in Individuals with Opioid Use Disorder

Abstract Opioid use disorder (OUD) is associated with altered brain network connectivity, particularly in the fronto-parietal (FPN), default mode, and salience (SN) networks. At rest, brain networks that are distinct from each other but are partially connected can optimize neural efficiency and support cognitive performance. Previous research found lower network segregation in people with cognitive impairment, alcohol use disorder, and as people age. Here, we examined “brain network segregation”—a graph theory-based metric of the network integration/segregation balance—in individuals with OUD and hypothesized that recent drug use severity would be linked to reduced network segregation. Forty adults with OUD completed resting-state functional magnetic resonance imaging, the drug use severity subscale of the Addiction Severity Index, and measures of cognition (IQ and working memory), mood, and affect. We grouped 264 brain regions into 10 networks, categorized as “association” (higher-order cognition) or “sensorimotor” (sensory and motor) networks. Regression analyses showed that drug use severity predicted lower brain network segregation in the association networks, with the FPN and SN driving this effect. Age predicted lower brain network segregation in the sensorimotor networks, while an interaction with age showed that drug use severity only predicted lower sensorimotor network segregation in younger adults. Cognition did not relate to brain network segregation, but positive affect related to greater SN segregation. Brain network segregation remained stable across OUD treatment. These findings elucidate alterations in brain network segregation related to drug use severity in people with OUD, which may contribute to cognitive impairment and accelerated brain aging. Competing Interest Statement The authors have declared no competing interest. Footnotes Funding: This work was supported by NIH/NIDA T32DA028874 (Hager); NIH/NIA T32AG076411 (Ramos-Rolón); Commonwealth of Pennsylvania C.U.R.E. Addiction Center of Excellence: Brain Mechanisms of Relapse and Recovery (Childress); NIH AA031088, NIH AA031337, and NIH DA046345-05W1 (Wiers); NIH/NIDA K01DA051709, Brain & Behavior Research Foundation NARSAD Young Investigator Grant #30780 (Shi);