Substance-Specific and Shared Gray Matter Signatures in Alcohol, Opioid, and Polysubstance Use Disorder

Central Executive Network drives delta-9-tetrahydrocannabinol (THC)-induced nonlinear changes in large-scale functional connectivity in adolescent nonhuman primates

Adolescent cannabinoid exposure has been implicated in enduring modifications to adult brain circuitry; however, well-controlled, systematic analyses investigating dose-dependent effects of chronic delta-9-tetrahydrocannabinol (THC) exposure on brain connectivity are lacking. It is hypothesized that large-scale intrinsic networks, such as default mode (DMN), central executive (CEN), and salience networks (SN), are critically involved in vulnerability to deficits in cognitive processing often associated with adolescent cannabis use. The present study aimed to elucidate the effects of chronic THC exposure on functional connectivity (FC) of these putative large-scale networks in nonhuman primates. Separate groups of adolescent squirrel monkeys (aged 2.0-yrs [female] and 2.5-yrs [male]) were administered intramuscular injections of vehicle or THC daily (0.32 or 3.2mg/kg) for 6-months during adolescence. Resting state functional connectivity from scans conducted in awake subjects was measured before dosing, at 6-months of chronic dosing, and 60-days following discontinuation of daily THC exposure. Utilizing two distinct analytical methodologies, we observed a non-linear, dosage-dependent alteration in DMN-CEN FC across scan intervals. Specifically, exposure to a low THC dosage increased FC during chronic exposure compared to both the pre-dosing and discontinuation periods. This pattern, however, was not observed in either the vehicle or high THC dosage groups. Dual-regression unveiled a similar non-linear effect within the CEN, but not DMN, suggesting the effect on DMN-CEN FC may be driven by modifications within the CEN. Taken together, these results suggest adolescent THC exposure differentially affects large-scale brain networks and contributes to a nuanced understanding of CEN's role in disrupting brain connectivity following chronic THC exposure.

Cortical thickness of the inferior parietal lobule as a potential predictor of relapse in men with alcohol dependence

Alcohol dependence is a disorder with a high recurrence rate that leads to a considerable public health burden. The risk of relapse appears to be related to a complex interplay of multiple factors. Herein, we aimed to explore the potential neural predictors of relapse in Chinese male patients with alcohol dependence. This study enrolled 58 male patients with alcohol dependence who had undergone acute detoxification. General demographic information and clinical features were collected. Magnetic resonance imaging data were used to measure cortical thickness across 34 regions of the brain. Patients were followed up at six months, and 51 patients completed the follow-up visit. These patients were divided into a relapser and an abstainer group. A binary logistic regression analysis was performed to investigate the potential risk factors of relapse. Compared to abstainers, relapsers showed higher inattention and non-planning impulsivity on the 11th version of the Barratt Impulsive Scale. The cortical thicknesses of the inferior-parietal lobules were significantly higher in abstainers compared with those in relapsers. Furthermore, binary logistic regression analysis showed that the thickness of the inferior parietal lobule predicted relapse, and lower non-planning impulse was a protective factor against relapse. Relapsers show poorer impulse control than abstainers, and structural magnetic resonance imaging revealed a decreased thickness of the inferior parietal lobule in relapsers. Our results indicate the thickness of the inferior parietal lobule as a potential relapse predictor in male patients with alcohol dependence.

Disrupted brain state dynamics in opioid and alcohol use disorder: attenuation by nicotine use

Substance use disorder (SUD) is a chronic relapsing disorder with long-lasting changes in brain intrinsic networks. While most research to date has focused on static functional connectivity, less is known about the effect of chronic drug use on dynamics of brain networks. Here we investigated brain state dynamics in individuals with opioid use (OUD) and alcohol use disorder (AUD) and assessed how concomitant nicotine use, which is frequent among individuals with OUD and AUD, affects brain dynamics. Resting-state functional magnetic resonance imaging data of 27 OUD, 107 AUD, and 137 healthy participants were included in the analyses. To identify recurrent brain states and their dynamics, we applied a data-driven clustering approach that determines brain states at a single time frame. We found that OUD and AUD non-smokers displayed similar changes in brain state dynamics including decreased fractional occupancy or dwell time in default mode network (DMN)-dominated brain states and increased appearance rate in visual network (VIS)-dominated brain states, which were also reflected in transition probabilities of related brain states. Interestingly, co-use of nicotine affected brain states in an opposite manner by lowering VIS-dominated and enhancing DMN-dominated brain states in both OUD and AUD participants. Our finding revealed a similar pattern of brain state dynamics in OUD and AUD participants that differed from controls, with an opposite effect for nicotine use suggesting distinct effects of various drugs on brain state dynamics. Different strategies for treating SUD may need to be implemented based on patterns of co-morbid drug use.

Common and distinct fronto-striatal volumetric changes in heroin and cocaine use disorders

Different drugs of abuse impact the morphology of fronto-striatal dopaminergic targets in both common and unique ways. While dorsal striatal volume tracks with addiction severity across drug classes, opiates impact ventromedial prefrontal cortex (vmPFC) and nucleus accumbens (NAcc) neuroplasticity in preclinical models, and psychostimulants alter inhibitory control, rooted in cortical regions such as the inferior frontal gyrus (IFG). We hypothesized parallel grey matter volume changes associated with human heroin or cocaine use disorder: lower grey matter volume of vmPFC/NAcc in heroin use disorder and IFG in cocaine use disorder, and putamen grey matter volume to be associated with addiction severity measures (including craving) across both. In this cross-sectional study, we quantified grey matter volume (P < 0.05-corrected) in age/sex/IQ-matched individuals with heroin use disorder (n = 32, seven females), cocaine use disorder (n = 32, six females) and healthy controls (n = 32, six females) and compared fronto-striatal volume between groups using voxel-wise general linear models and non-parametric permutation-based tests. Overall, individuals with heroin use disorder had smaller vmPFC and NAcc/putamen volumes than healthy controls. Bilateral lower IFG grey matter volume patterns were specifically evident in cocaine versus heroin use disorders. Correlations between addiction severity measures and putamen grey matter volume did not reach nominal significance level in this sample. These results indicate alterations in dopamine-innervated regions (in the vmPFC and NAcc) in heroin addiction. For the first time we demonstrate lower IFG grey matter volume specifically in cocaine compared with heroin use disorder, suggesting a signature of reduced inhibitory control, which remains to be tested directly using select behavioural measures. Overall, results suggest substance-specific volumetric changes in human psychostimulant or opiate addiction, with implications for fine-tuning biomarker and treatment identification by primary drug of abuse.