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Langleben, D. D.

Publications and source records attributed to Langleben, D. D..

2 recordsLinked to original sources

Long-acting naltrexone restores network connectivity in subjects with co-morbid cannabis and opioid use disorder

Co-morbid substance use disorders (SUDs) are common but difficult to study due to the complex, interacting, and overlapping mechanisms through which they affect brain networks. Many datasets collected to investigate a specific SUD include participants with co-morbid SUDs. While most studies treat comorbid SUDs as covariates of no interest, these covariates also contain untapped information. This is particularly relevant as cannabis use disorder (CanUD) has become increasingly prevalent and co-morbid with other SUDs that have been more thoroughly studied. While treatments have been established for multiple SUDs, none have been approved for CanUD, although naltrexone (NTX) has been associated with reduced use. Here, we conducted a retrospective secondary analysis of functional magnetic resonance imaging (fMRI) data from individuals with primary opioid use disorder (OUD) with co-morbid CanUD, alcohol use disorder (AUD), or cocaine use disorder (CocUD), while controlling for opioid use. All participants underwent imaging prior to receiving a therapeutic dose of long-acting intramuscular NTX (Vivitrol(R)), an approved treatment for OUD and AUD but not for CocUD, and again two weeks post-administration. At baseline, OUD individuals with co-morbid CanUD, AUD, or CocUD exhibited distinct functional connectivity (FC) alterations compared to those with OUD-only. These differences were greater in younger participants and primarily involved the default mode network. Following NTX administration, FC differences between the co-morbid CanUD and OUD-only groups globally diminished. A similar FC response to NTX was observed in the parietal, subcortical, sensory, and cerebellar networks in the co-morbid AUD group. In contrast, little change in FC was observed in co-morbid CocUD. These findings, combined with prior evidence that NTX reduces cannabis use by dampening the experience of reward, suggest NTX may hold promise as a treatment for CanUD.

neuroscience↗

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

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.

neuroscience↗