This study investigated the architecture and neural activity of white matter functional networks (WMFNs) in individuals with opioid use disorder (OUD) after prolonged abstinence, compared with healthy controls (HCs).

Blood oxygen level-dependent signals in white matter were analyzed using a data-driven k-means clustering approach across individuals with OUD at baseline (OUD1), the same individuals after prolonged abstinence at follow-up (OUD2), and HCs.

In OUD1, the deep frontoparietal network was fragmented into the superior longitudinal fasciculus network and anterior corona radiata network; this organization partially recovered in OUD2, becoming more similar to HCs. OUD1 also showed hyperactivation in the deep frontal network and hypoactivation in the frontotemporal-parietal network, with frontotemporal-parietal activity negatively correlated with years of opioid use.

OUD is associated with disrupted architecture of WMFNs and altered neural activity, whereas prolonged abstinence may promote partial network restoration. These findings highlight the neuroplastic potential of WMFNs during recovery and provide insights into the neural mechanisms underlying OUD and abstinence-related rehabilitation.

Estimating the prevalence of use of substances such as heroin remains a challenge. The aim of this study is to identify the scientific publications in Spain that have used surveys to investigate heroin use, to describe their methodology and to contrast the formulation of the questions with users’ input on key aspects associated with use.

A scoping review was conducted until November 2024 in MEDLINE (Ovid), EMBASE and Web of Science. The review included questionnaire-based research studies assessing heroin use in Spain. Information on study, population, data collection and consumption characteristics was compiled from each included study. In addition, in-depth interviews were conducted with Spanish heroin current users and ex-users.

Twenty-nine questionnaire-based research studies assessing heroin use in Spain were identified; none of them were specifically oriented to estimate and characterise heroin use at the population level. Most of the studies focused on specific population groups, mainly drug users, students, or inmates. The majority addressed lifetime, past-year, and past-month use, although users found the past 3 or 6 months more relevant. Few studies explored other use characteristics; however, interviews with heroin ex-users highlighted the importance of factors like route of administration and age of first use.

The studies identified in this review vary in terms of target population, geographic scope, reference time frame, and data collection methods. Moreover, questionnaires rarely address additional characteristics of use that are considered relevant by former users. This review identifies areas for improvement to guide future studies and refine methodological approaches.

Opioid use disorder (OUD) is a major global-scale social issue affecting public health. The high potential for addiction and dependence makes opioid use a significant concern, contributing to substance-related disorders. Both genetic and environmental factors contribute to the predisposition to OUD, with the opioidergic, dopaminergic, and GABAergic systems playing primary roles in itsonset.

This narrative review documents the association between genes and their variants related to these three systems, along with current evidence on epigenetic interventions in OUD. Relevant studies investigating candidate-gene associations and molecular mechanisms were synthesized to highlight genetic variants and epigenetic processes linked to OUD.

Genetic associations play a prominent role in OUD, with several single-nucleotide variants identified in affected populations. Key genes implicated include OPRM1, OPRD1, OPRK1, PDYN, OPRL1, and POMC from the opioidergic system; DRD1, DRD2, DRD3, DRD4, ANKK1, and COMT from the dopaminergic system; and GABRA2, GABRB3, GABRG2, GAD1, and GAD2 from the GABAergic system. Evidence also indicates that chronic opioid use is associated with epigenetic changes through posttranslational histone modifications and DNA methylation. However, limitations in existing studies include small sample sizes, limited replication, and potential stratification biases.

Although many candidate-gene associations have been proposed for OUD, robust evidence remains limited. Large, ancestrally diverse genome-wide association studies (GWAS) and systematic replication studies are urgently needed. A deeper understanding of the genetic, epigenetic, and neurobiological bases of addiction will be essential for the development of precisely targeted medications to improve prevention and treatment outcomes for OUD.

Methadone maintenance treatment (MMT) and protracted abstinence (PA) effectively reduce the craving for heroin among individuals with heroin use disorder (HUD). However, the difference in their effects on brain function, especially the coupling among the large-scale brain networks (default mode [DMN], salience [SN], and executive control [ECN] networks), remains unclear. This study analyzed the effects of the MMT and PA on these networks and the predictive value of the bilateral resource allocation index (RAI) for craving for heroin.

Twenty-five individuals undergoing the MMT, 22 undergoing the PA, and 51 healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI). Independent component analysis identified the ECN, DMN, and SN. The SN-ECN and SN-DMN connectivity and the bilateral RAI were evaluated. The relationships between network coupling and clinical and psychological characteristics were analyzed. The multiple linear regression model identified significant variables for predicting craving scores.

The MMT group showed significantly stronger SN-left ECN (lECN) coupling and left RAI than the PA group. In the MMT group, SN-lECN connectivity and bilateral RAI were positively correlated with the total methadone dose. In both treatment groups, SN-right ECN (rECN) connectivity and right RAI were negatively correlated with craving. The models revealed that the bilateral RAI and the MMT and PA were associated with the craving.

The MMT enhances SN-lECN coupling and the left RAI more than the PA, possibly due to higher control modulation. The RAI could help predict heroin craving in individuals with HUD undergoing either treatment program.

Many studies aggregate prescription opioid misuse (POM) and heroin use into a single phenotype, but emerging evidence suggests that their genetic and environmental influences may be partially distinct.

In total, 7164 individual twins (84.12% complete pairs; 59.81% female; mean age = 30.58 years) from the Australian Twin Registry reported their lifetime misuse of prescription opioids, stimulants, and sedatives, and lifetime use of heroin, cannabis, cocaine/crack, illicit stimulants, hallucinogens, inhalants, solvents, and dissociatives via telephone interview. Independent pathway models (IPMs) and common pathway models (CPMs) partitioned the variance of drug use phenotypes into general and drug-specific genetic (a), common environmental (c), and unique environmental factors (e).

An IPM with one general a and one general e factor and a one-factor CPM provided comparable fit to the data. General factors accounted for 55% (a = 14%, e = 41%) and 79% (a = 64%, e = 15%) of the respective variation in POM and heroin use in the IPM, and 25% (a = 12%, c = 8%, e = 5%) and 80% (a = 38%, c = 27%, e = 15%) of the respective variation in POM and heroin use in the CPM. Across both models, POM emerged with substantial drug-specific genetic influence (26–39% of total phenotypic variance; 69–74% of genetic variance); heroin use did not (0% of total phenotypic variance; 0% of genetic variance in both models). Prescription sedative misuse also demonstrated significant drug-specific genetic variance.

Genetic variation in POM, but not heroin use, is predominantly drug-specific. Misuse of prescription medications that reduce experiences of subjective distress may be partially influenced by sources of genetic variation separate from illicit drug use.

Based on hubs of neural circuits associated with addiction and their degree centrality (DC), this study aimed to construct the addiction-related brain networks for patients diagnosed with heroin dependence undertaking stable methadone maintenance treatment (MMT) and further prospectively identify the ones at high risk for relapse with cluster analysis.

Sixty-two male MMT patients and 30 matched healthy controls (HC) underwent brain resting-state functional MRI data acquisition. The patients received 26-month follow-up for the monthly illegal-drug-use information. Ten addiction-related hubs were chosen to construct a user-defined network for the patients. Then the networks were discriminated with K-means-clustering-algorithm into different groups and followed by comparative analysis to the groups and HC. Regression analysis was used to investigate the brain regions significantly contributed to relapse.

Sixty MMT patients were classified into two groups according to their brain-network patterns calculated by the best clustering-number-K. The two groups had no difference in the demographic, psychological indicators and clinical information except relapse rate and total heroin consumption. The group with high-relapse had a wider range of DC changes in the cortical−striatal−thalamic circuit relative to HC and a reduced DC in the mesocorticolimbic circuit relative to the low-relapse group. DC activity in NAc, vACC, hippocampus and amygdala were closely related with relapse.

MMT patients can be identified and classified into two subgroups with significantly different relapse rates by defining distinct brain-network patterns even if we are blind to their relapse outcomes in advance. This may provide a new strategy to optimize MMT.

This study was carried out on 149 of Heroin dependent patient that admission for detoxification.

This study is a 10 days double blind placebo-controlled trial.

This study is a 10 days double blind placebo-controlled trial which was carried out on 149 of Heroin dependent patient that admission for detoxification in Mashhad Ebne-sina hospital in 1385-1386 Subjects were randomly divided into topiramate and placebo detoxification groups.

Topiramate group receive topiramate (max 200 mg) for 10 days. The placebo group received usual regimen and placebo. Withdrawal symptoms were assessed by Subjective and Objective Opiate Withdrawal Scale in days 1, 3, 5, 7, 10.information s analyzed by chi-square test for qualities variables and T-test & Mann-Whitney for quantities variables in SPSS software.

22 subjects were excluded from the study. Both groups had no significant differences in age, sex, education, number of previous withdrawal and past history of other drug use. Result indicates decrease in objective withdrawal symptom significant in 3(p=0.000), 5 (p=0.004) and 7(p=0.026) day and subjective withdrawal symptom significant in 3 (p=0.000) day in topiramate groups.

Topiramate can use for control of withdrawal symptom in patient with Heroin dependency.

Chronic opioid exposure is common world-wide, but behavioural performance remains under-investigated. This study aimed to investigate visuospatial memory performance in opioid-exposed and dependent clinical populations and its associations with measures of intelligence and cognitive impulsivity.

We recruited 109 participants: (i) patients with a history of opioid dependence due to chronic heroin use (n = 24), (ii) heroin users stabilised on methadone maintenance treatment (n = 29), (iii) participants with a history of chronic pain and prescribed tramadol and codeine (n = 28) and (iv) healthy controls (n = 28). The neuropsychological tasks from the Cambridge Neuropsychological Test Automated Battery included the Delayed Matching to Sample (DMS), Pattern Recognition Memory, Spatial Recognition Memory, Paired Associate Learning, Spatial Span Task, Spatial Working Memory and Cambridge Gambling Task. Pre-morbid general intelligence was assessed using the National Adult Reading Test.

As hypothesised, this study identified the differential effects of chronic heroin and methadone exposures on neuropsychological measures of visuospatial memory (p < 0.01) that were independent of injecting behaviour and dependence status. The study also identified an improvement in DMS performance (specifically at longer delays) when the methadone group was compared with the heroin group and also when the heroin group was stabilised onto methadone. Results identified differential effects of chronic heroin and methadone exposures on various neuropsychological measures of visuospatial memory independently from addiction severity measures, such as injecting behaviour and dependence status.