Addiction Biology

Maternal smoking during pregnancy is associated with adverse effects on offspring health through impaired placental structure and function. Nicotine and other tobacco-related compounds readily cross the placental barrier, disrupt metabolic pathways, and increase the risk of long-term developmental disorders in newborn. Here, placental metabolic alterations associated with maternal smoking exposure were examined with metabolomics. We used placental samples from the Kuopio Birth Cohort study from 23 nonsmoking controls pregnancies, 19 pregnancies with early smoking exposure (cotinine detected in first-trimester but not in at-term samples), and 13 pregnancies with continuous smoking-exposure (cotinine detected in both first-trimester and at-term samples). Differences in placental metabolomic profiles were seen between controls and both smoking-exposed groups. For example, increased activity of xenobiotic metabolism pathways showed as elevated CYP1A2-related metabolites, e.g., aminoamide local anesthetic metabolite detected in both smoking-exposure groups (p=0.0042 and 0.0019, respectively). Disruptions in amino acid metabolism were observed, e.g., reduced placental tryptophan levels (p=0.0209 and 0.0237). Placentas from women who quit smoking during showed markers of reduced oxidative stress, lower oxidized glutathione (p=0.0119) and higher ergothioneine (p=0.0426) levels. These findings indicate that many smoking-related effects on the placental metabolome persist beyond acute nicotine exposure, showing long-term biological effects of maternal smoking during pregnancy. Plain language summarySmoking during pregnancy can possibly change how the placenta functions, which also affects the newborns long-term health. In this study, we compared placentas from nonsmokers, women who quit during pregnancy, and those who kept smoking. Clear chemical differences were seen in the placentas of smoking exposed pregnant women. The main changes included lowered levels of tryptophan and glutathione, which are important for growth and protection from stress. These results show that smoking-related changes in the placenta can persist beyond active nicotine exposure.

Tobacco use disorder (TUD) remains a leading cause of preventable mortality, and existing pharmacotherapies yield 12-month abstinence rates below 30%. As cannabis legalization expands, approximately 18-22% of people who use tobacco report concurrent cannabis use, yet the impact of co-use on cessation outcomes and the therapeutic potential of endocannabinoid system (ECS) modulation remain unclear. We conducted a translational systematic review and meta-analysis following PRISMA 2020 guidelines, searching Ovid MEDLINE, Embase, APA PsycInfo, and Web of Science through January 2026 (PROSPERO: CRD420250652724). Three study categories were eligible: observational studies of cannabis co-use and cessation outcomes; preclinical studies of cannabinoid modulators on nicotine-related behaviors; and human experimental studies of ECS-targeted interventions. Of 4,869 records screened, 52 studies met inclusion criteria. Meta-analysis of 18 observational studies (N=229,630) revealed that cannabis use was associated with 35% lower odds of achieving tobacco smoking cessation (OR=0.65; 95% CI: 0.55-0.78; p<0.0001; I{superscript 2}=88.1%). Preclinical evidence (15 studies) demonstrated that CB1 receptor antagonists robustly reduced nicotine self-administration and reinstatement, while cannabidiol (CBD) attenuated both nicotine intake and withdrawal without affecting food reinforcement. Clinical translation of CB1 receptor inverse agonists failed due to psychiatric adverse effects, but CBD showed promise by reducing cigarette consumption by 40%, reversing attentional bias to smoking cues, and alleviating withdrawal severity. These findings distinguish naturalistic cannabis exposure from potentially beneficial targeted ECS modulation, and support CBD as a promising candidate for adequately powered tobacco cessation trials.

As the global burden of addiction intensifies, the neurobiological commonalities and distinctions between substance use disorders (SUDs) and behavioral addictions (BAs) remain poorly characterized. This coordinate-based meta-analysis of 59 fMRI articles (n = 2,951) mapped the neural signatures of visual cue-reactivity across the addictive disorders. Our results revealed a universal core network shared by SUDs and BAs centered in the bilateral opercular inferior frontal gyrus, suggesting a shared disruption in inhibitory control. Distinctively, SUDs exhibited a stronger recruitment of a subcortical salience pathway, with greater involvement of the left thalamus ventral anterior nucleus than BAs, potentially reflecting pharmacologically amplified bottom-up salience attribution. Notably, recovery-related patterns diverged in the left medial superior frontal gyrus. Alcohol use disorder was associated with neural restoration, whereas heroin use disorder showed neural decompensation. These neural signatures establish a rigorous neurobiological basis for differentiating substance and behavioral phenotypes, supporting tailored circuit-based precision treatments.

BackgroundFatal insulin intoxication remains difficult to diagnose because insulin undergoes rapid degradation after death, limiting the reliability of direct biochemical measurements. This creates diagnostic uncertainty when objective molecular confirmation of insulin excess are required. We hypothesised that insulin excess induces systemic metabolic alterations that persist beyond insulin degradation and can be captured using postmortem metabolomics in a forensic setting. MethodsHigh-resolution mass spectrometry (HRMS)-based metabolomics was applied to a national cohort comprising 51 fatal insulin intoxications. Orthogonal partial least squares-discriminant analysis (OPLS-DA) models were trained on cases collected between 2017-2022 to identify insulin-associated metabolite features using a shared-and-unique-structures approach. Performance was evaluated using two temporally distinct test sets (2023-2024): a matched validation cohort and a heterogeneous forensic cohort reflecting biological variability. ResultsHere we show that an insulin-associated metabolomic fingerprint comprising 91 features demonstrated reproducible discrimination across independent cohorts. In the matched cohort (n=59, including 14 insulin cases), insulin intoxication classification achieved 100% sensitivity and 73% specificity within the applicability domain. In the heterogeneous cohort (n=154, including 14 insulin cases), 100% sensitivity was maintained with a 72% specificity despite increased biological variability. Univariate analyses demonstrated significant alterations across multiple metabolite classes, including acylcarnitines, fatty acids/lipids, and purine/nucleoside metabolites, with moderate effect sizes, consistent with systemic effects of insulin-induced hypoglycaemia. ConclusionsFatal insulin intoxication is associated with a reproducible metabolomic fingerprint detectable after death. These findings demonstrate that postmortem metabolomics may serve as a complementary decision-support tool when conventional biomarkers are unreliable.

BackgroundEarly low-level alcohol use predicts subsequent alcohol use and problems. Impulsivity and poor inhibitory control also predict later problematic alcohol use. However, few studies prospectively examine early sipping in combination with modeling impulsivity and inhibitory control change over time as predictors of adolescent alcohol use. MethodsData Release 6.0 from the Adolescent Brain Cognitive Development (ABCD) Study was used (n=11,866; 48% Female). A series of linear mixed-effect models examined trajectories of non-religious sipping at baseline (ages 9-10) and self-reported impulsivity (UPPS-P) and task-based inhibitory control (Flanker task) over time as predictors of past year drinks and problematic alcohol use by ages 15-16. Predictors were run as separate models and a full model with all predictors together. Models were nested within the participant and study site. Interactions with age (to measure change over time from Baseline to Year 6) were included. Corrections for multiple comparisons were employed. ResultsIn individual models, four impulsivity interactions were significant: (1) negative urgency*age ({beta}=.04, FDR-p<.001), (2) positive urgency*age ({beta}=.04, FDR-p<.001), (3) lack of planning*age ({beta}=.04, FDR-p<.001), and (4) sensation seeking*age ({beta}=.04, FDR-p<.001), suggesting that as age increases, the relationship between impulsivity and alcohol use strengthens. Sipping*age ({beta}=.02, FDR-p<.001) interactions also predicted standard drinks. Regarding problematic use, there was a significant interaction in the full model: negative urgency*age ({beta}=-.07, p=.05), indicating that this relationship is more pronounced at earlier ages. ConclusionsTrait impulsivity and sipping in late childhood relate to future alcohol use, and the relationship strengthens with age. Our results found a negative interaction between negative urgency and age on problematic use, potentially indicating negative urgency as a phenotype of vulnerability to experiencing alcohol related problems at younger ages. Findings indicate the importance of understanding facets of impulsivity in the context of adolescent alcohol use for prevention and intervention efforts.

Pregnant women with HIV control viral replication with antiretrovirals and give birth to HIV-exposed uninfected infants (HEU). The children, however, exhibit increased morbidity and mortality due to severe infections, as well as cognitive and growth abnormalities. In this study, we performed high-resolution, untargeted metabolomics on 123 HIV-exposed mother-baby pairs and 117 control pairs without HIV. High concentrations of the antiretroviral efavirenz and its metabolites were detected in maternal blood and cord blood. The metabolomic differences between HEU participants and controls reflect perturbed pathways of steroids, tryptophan and bile acids, and they largely consisted of metabolites that were correlated with efavirenz concentrations within the HEU group. The results suggest a major contribution of the drug to the abnormal biochemical profile of HEU infants born to mothers treated with efavirenz.

Alcohol use disorder (AUD) is a chronic, relapsing condition and a major public health problem. However, few medications are approved to treat AUD, and those available show limited efficacy. Drug repurposing is a cost-effective strategy to identify novel therapeutic uses for existing medications. Here, we describe a pipeline that integrates genetic and electronic health record (EHR) data to identify and evaluate drugs to be repurposed for treating AUD. Our approach comprises 1) alcohol-associated gene identification and biological network generation; 2) mapping drugs to target proteins; 3) filtering promising repurposing candidates; and 4) an exemplar pharmacoepidemiologic analysis of the effect of an identified drug (i.e., baclofen) on alcohol consumption. Linking loci to genes from a genome-wide association study (GWAS) of problematic alcohol use identified 94 genes, which we expanded to 327 alcohol-related genes through network-based analyses. Across these analyses, 52 genes were linked to 195 FDA-approved drugs, including four already approved or used off-label to treat AUD. After filtering for safety, relevance, and data availability, 26 candidate drugs, including baclofen, were selected for further evaluation. An evaluation of the real-world effectiveness of baclofen using national EHR data from the United States Department of Veterans Affairs provided evidence that baclofen-exposed patients reduced alcohol consumption more than propensity-score-matched unexposed patients. This approach, which aligns genomic findings with real-world clinical data, provides an efficient method for identifying promising drug repurposing candidates and prioritizing those that merit evaluation in randomized trials to ultimately advance pharmacotherapies for AUD.

Background and AimsSubstance use disorders (SUDs) are heritable and share genetic variance with externalizing and internalizing psychopathology. Although recent gene identification efforts have demonstrated the value of modeling the shared genetic architecture among SUDs and externalizing, most research has thus far failed to account for overlap with internalizing. In this study, we aim to characterize the genetic relationships of both externalizing and internalizing with SUDs. Design and settingWe used genome-wide association study (GWAS) summary statistics derived from previously published studies of externalizing, internalizing, and SUD outcomes to quantify the genetic overlap between these phenotypes. We characterize this overlap using omnibus, partial, and local genetic correlations, estimates of their shared polygenic effects, genetic causality models, polygenic score (PGS) analyses, and estimates of each SUDs residual variance derived from models in Genomic SEM. ParticipantsWe used GWAS summary statistics from individuals whose genomes were most similar to those from reference panels sampled from Europe (Ns ranged from 45,395 to 1,565,618) and Africa (Ns ranged from 30,000 to 122,571). For polygenic scores analyses, we used data from individuals of European and African ancestry groups available in the Collaborative Study on the Genetics of Alcoholism (COGA) sample (NMaximum = 7,394 for European-like genomes and 3,238 for African-like genomes) MeasurementsMeasurements in this study include GWAS summary statistics for externalizing, internalizing, and four substance use disorders: problematic alcohol use (PAU), cannabis use disorder (CUD), opioid use disorder (OUD), and tobacco use disorder (TUD). SUD outcomes in COGA were DSM-IV symptom counts of AUD, CUD, and OUD and scores on the Fagerstrom Test for Nicotine Dependence. FindingsWe found strong genetic relationships of externalizing and, to a lesser extent, internalizing with all SUDs across methods. Despite their more modest associations, internalizing emerged as an important genetic correlate of SUDs. After accounting for variance shared with externalizing, partial genetic correlations between internalizing and SUDs were attenuated but, with the exception of TUD, still significant. Similarly, the PGSINT accounted for a statistically significant increase in variance over and above PGSEXT. Two SUD specific patterns emerged such that TUD was least associated with both psychopathology spectra and OUD was most strongly related to internalizing relative to other SUDs. ConclusionsFrom these findings we conclude that shared genetic influences may explain comorbidity observed between SUDs and internalizing disorders and suggest that genetic risk for internalizing should be incorporated into SUD identification and prevention efforts. Future gene identification efforts should study SUDs in the context of both externalizing and internalizing psychopathology.

Background and AimsThe UK legalised medical cannabis in 2018, yet little is known about people accessing cannabis legally via prescription or those using cannabis for medical purposes without a prescription. This study aimed to estimate: 1) the percentage of people who use cannabis medically with and without a prescription; 2) the sources used to obtain cannabis; 3) the products used; and 4) the associations between monthly or more frequent (MMF) product use and medical cannabis use status. DesignNational repeat cross-sectional surveys conducted in September-November 2023 and 2024. SettingUK. ParticipantsPeople aged 16-65 who used cannabis in the past 12 months (n=4,414). MeasurementsInferential statistics compared outcomes by medical cannabis use status. Multivariable regression analyses estimated associations between MMF product use and medical cannabis use status. FindingsOverall, 13.0% of people reported receiving a medical cannabis prescription, 36.4% reported medical use without a prescription, and 50.6% reported no medical use. Cannabis was sourced through diverse routes; only 10.7% of people with prescriptions obtained all their cannabis from a legal medical prescription. People with a medical prescription had a higher probability of reporting MMF use of oils or liquid drops (aRR=3.51; 95% CI: 2.73-4.52), oil or liquid capsules (aRR=2.63; 1.99-3.47), vape oils (aRR=2.40; 2.03-2.84), edibles (aRR=2.41; 2.01-2.90), cannabis drinks (aRR=3.39; 2.69-4.26), solid concentrates (aRR=3.10; 2.29-4.21), hash or kief (aRR=1.82; 1.44-2.30), and topicals (aRR=3.42; 2.58-4.51) than people who did not report medical use, after adjusting for covariates. People who ever asked for a medical prescription and people with a medical prescription in the past year had a higher probability of screening positive for high-risk use. ConclusionOver one in ten people who use cannabis in the UK report a medical cannabis prescription, yet a third reported medical use without a prescription. With only a minority obtaining all their cannabis legally, many rely on illegal sources, suggesting prescriptions may not meet the needs of those reporting use for medical purposes. People with prescriptions show a higher probability of frequent use of processed, higher-potency products, and meeting a threshold for high-risk use. Healthcare encounters during medical cannabis prescribing should discuss risks related to potency, product type, and adverse effects such as cannabis use disorder.

BackgroundInhaled combusted cannabis and co-use of combusted cannabis and nicotine electronic cigarettes (nECIGs) are on the rise, yet their long-term cardiovascular risk is unclear due to the high prevalence of confounders in observational human studies. Using primary plasma and monocytes and a novel ex vivo mechanistic model of two early steps in atherogenesis, this study examined whether chronic combusted cannabis use is associated with atherogenic changes, as estimated by 1) monocyte transendothelial migration (MTEM), and 2) monocyte-derived foam cell formation (MDFCF), and whether nECIG co-use further amplifies this risk. MethodsA cross-sectional parallel group comparison study was conducted in healthy adults (21-30 years) who chronically 1) used combusted cannabis, 2) co-used both combusted cannabis and nECIGs, and 3) were non-using controls. Using our ex vivo atherogenesis assay, primary outcomes of MTEM, MDFCF, and median fluorescence intensity (MFI) of the lipid-staining fluorochrome BODIPY were determined using primary plasma and autologous primary monocytes from participants. Using flow cytometry and the fluorochrome CELLROX, cellular oxidative stress (COS) in monocytes was determined. ResultsOf the 134 participants, 59 used cannabis, 26 co-used cannabis/nECIG, and 49 were non-using controls. The groups had similar age, sex, and race. Median MTEM was 1.13 fold greater in people who used cannabis compared to non-users 27.8% (IQR 26.1:29.2%) vs 24.5%, (IQR 22.9:27.4%), p<0.0001, and tended to be greater in people who co-used cannabis/nECIG by 1.22-fold 34.1%, (IQR 29.9:38.3%, p=0.17). Median MDFCF and MFI were also increased in people who used cannabis compared to non-users (MDFCF 36.3%, IQR 31.8:35.8%, vs 26.6%, IQR 23.8:25.8%, 1.36-fold and MFI 1163.8, IQR 1042.8:1155.0, vs 940.2 IQR 849.9:1101.4, 1.24-fold) and were further increased in people who co-used cannabis/nECIG (MDFCF 48.7%, IQR 37.3:52.4%, 1.34-fold, MFI 1433.7, IQR 1263.8:1686.4, 1.23-fold; all comparisons p<0.008). Foam cell formation, but not transendothelial migration, was strongly positively correlated with COS. All primary outcomes increased with greater frequency of cannabis and/or nECIG use. ConclusionsIn healthy young adults, exclusive cannabis use is associated with increased atherogenic properties of monocytes and plasma, and this atherogenic effect is further amplified by co-use of nECIGs.

Despite decades of clinical implementation of medications for opioid use disorder (OUD), overdose mortality rates remain high, underscoring a critical gap in treatments that target brain mechanisms driving addiction. Mindfulness-Oriented Recovery Enhancement (MORE) has demonstrated efficacy in reducing opioid use and craving, hypothetically by restructuring the salience of drug and natural rewards. Yet, to date, MOREs neurobiological mechanisms remain unclear. In this first functional magnetic resonance imaging (fMRI) randomized controlled trial (RCT) of MORE for OUD (NCT04112186), we tested whether compared with an active psychoeducational supportive therapy (PST) control group, MORE rebalanced neural responses to drug and natural reward cues in inpatients with OUD receiving standard of care including medications. Compared with PST, eight weeks of MORE significantly reduced drug-biased activity in the dorsolateral prefrontal cortex (dlPFC) and posterior regions of the default mode network including the precuneus during downregulation of responses to drug cues relative to upregulation of responses to natural reward cues (even when controlling for passive cue viewing). The shift from drug to natural reward responses in the lateral and ventromedial PFC was associated with lower cue-induced craving exclusively in the MORE group. MORE also reduced medial PFC synchronization to naturalistic drug-related movie scenes and significantly extended abstinence duration at follow-up ([~]4 months post-treatment) relative to PST. Together, this neuroimaging RCT demonstrates that MORE normalizes function in PFC nodes of the reward, salience, and control systems, positioning MORE as a biologically-grounded adjunct to pharmacotherapy for OUD.

Youth alcohol use is a significant global health concern. Despite the widespread nature of alcohol use-related problems, the longitudinal effects of alcohol on brain structure in youth remain unclear. This review aimed to systematically synthesise the findings from the longitudinal structural magnetic resonance imaging (sMRI) literature on how alcohol use is associated with changes in brain structure in youth. Following PRISMA guidelines, five databases were searched, and studies of youth alcohol use that measured brain structure using sMRI at more than one time-point were included. A label-based meta-analysis (i.e., ratio of number of significant effects for a specific brain region to total number of analyses for that brain region) approach was employed to synthesise the findings. Sixteen studies were included. There was preliminary evidence that youth alcohol use is associated with reduced cortical volume (particularly in temporal regions) and attenuated increases in white matter volume over time. The role of pre-existing structural differences, and other moderating factors remains unclear due to limited research. Future longitudinal studies are needed to clarify the clinical significance of neurodevelopmental changes associated with youth alcohol use. Significance statementThis systematic review synthesises evidence from 16 longitudinal neuroimaging studies on youth alcohol use and brain structure. Preliminary findings suggest adolescent drinking may be associated with reduced grey and white matter volume over time, with heavier consumption amplifying these effects. While methodological limitations prevent definitive conclusions, these potential neurodevelopmental disruptions during a critical brain maturation window could influence cognitive and behavioural outcomes. The review highlights the need for rigorous future research to further clarify the impact of alcohol on developmental brain trajectories, which could support targeted prevention approaches for adolescent brain health.

Substance use disorder (SUD) recovery typically requires transformative change and prioritizing long-term healthy goals. Unfortunately, successful recovery is threatened by relapse rates that often exceed 50% in the first year. We previously reported on an experiential virtual reality (VR) SUD recovery intervention using personalized future self-avatars that produced emotional engagement and positive behavioral change, ie, stronger connection with the future self and future rewards and reduced craving. Here, we used fMRI to identify brain engagement to a future self experience with divergent futures. Twenty adults (14 male, 33 years old) in early SUD recovery (<1 year) interacted with age-progressed versions of themselves in two different VR future realities: an SUD Future Self and a Recovery Future Self. Vivid lifelike visual and audio animation was augmented with a personalized narrative concerning future drug use and recovery. MRI immediately followed. Participants viewed videos of their future selves in the virtual environment and were directed to contemplate what they were seeing. Viewing and contemplating the future selves elicited activation in midline default mode regions (posterior cingulate and ventromedial prefrontal cortices), visual regions including the occipital and fusiform face areas, and left middle frontal gyrus. The Recovery Future Self produced significant left occipital face area activation compared with the SUD Future Self. Midline default mode activation correlated with VR-induced increases in delayed reward preference, and also with greater trait perseverance. Using digital selves as therapeutic agents reveals an entirely novel set of possible interventions and opens exciting new frontiers in behavior change methodology. Future studies targeting decision-making and future behavior could be informed by evaluating increased midline default mode engagement, with uniquely self-focused mechanisms signaled by executive network and face area coactivation. New hope for treatment-resistant mental health conditions is offered by the nearly limitless range of therapeutic experiences enabled by immersive digital therapeutics. Plain Language SummaryHigh relapse rates in early recovery remains a serious challenge. To promote better outcomes, our team recently developed a virtual reality experience where people interacted with future versions of themselves. We used magnetic resonance imaging (MRI) to understand how the brain activated to this experience, and what brain responses were linked to positive outcomes. We worked with 20 adults in early recovery. Each person used virtual reality to interact with two different future selves: one who had returned to substance use, and one who had stayed in recovery. These digital future selves looked and sounded like the participants and were paired with a personalized story about future drug use and recovery. Right after the virtual reality session, participants brains were scanned while they watched videos of these future selves and were asked to think about what they were seeing. When people viewed and reflected on their future selves, brain areas involved in self-reflection and imagining the future became more active, along with regions that process faces. The future selves triggered brain activation in "self-focused" brain networks and in face-processing regions. Activity in key "self-focused" brain regions was linked to choosing larger, delayed rewards over smaller, immediate ones, and to lower impulsivity. These findings suggest that lifelike digital versions of peoples future selves engage brain systems that support thinking ahead, persistence, and valuing long-term outcomes. This creates a promising new avenue for immersive digital therapeutic experiences to encourage lasting behavior change in early recovery from substance use disorder.

Prenatal alcohol exposure (PAE) disrupts embryonic development and gives rise to a variable fetal alcohol spectrum disorder (FASD) phenotype characterized by neurodevelopmental and dysmorphological defects. We investigated the effects of PAE on placental gene regulation by performing genome-wide DNA methylation (DNAm) microarray and gene expression (mRNA sequencing) analyses in 87 PAE, 77 unexposed control, and 11 smoking-exposed-only placentas. Significant alterations were identified in genes involved in synaptic function including both excitatory and inhibitory neurotransmission, and in genes previously associated with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, schizophrenia, and addiction. When placental molecular alterations were compared with neuropsychological and dysmorphological phenotypes of the same children assessed at six years of age, numerous correlations were observed between DNAm and gene expression, as well as head circumference, cognitive performances, ADHD traits, and dysmorphology. These included associations between DAOA methylation and verbal intellectual abilities and language development, GPHN methylation and working memory index, and GLI3 expression and both working memory index and midfacial hypoplasia. As these alterations were observed in the placenta, this tissue not only enables the identification of phenotype-specific FASD candidate genes but also represents a valuable tool for studying complex developmental disorders in human.

BackgroundTheta-band oscillation is integral to fronto-parietal connectivity in the executive control network and its top-down regulation on subcortical areas. External frontoparietal synchronization using theta-frequency transcranial alternating current (tACS) is a technology to potentially engage this network. In this pre-registered, triple-blind, sham-controlled trial (NCT03907644), we tested this intervention targeting the right frontoparietal network in people with opioid use disorder (OUD) to measure network engagement and behavioral outcomes. MethodSixty male participants with OUD were randomized to receive 20 minutes of active or sham 6 Hz tACS (HD electrodes over F4 and P4). Structural, resting-state, task-based fMRI drug cue reactivity, and repeated cue-induced craving assessments were collected immediately before and after stimulation. Pre-registered outcome measures were analyzed using timexgroup interaction models to examine (1) modulation of drug cue-related brain activity, (2) changes in craving, (3) alterations in functional connectivity, and (4) relationship between electric field, neural responses, and craving behavior. Results(1) A significant Time x Group interaction revealed decreased post-stimulation opioid cue-related activity in the active group relative to sham, involving key nodes in reward processing (ventral striatum, amygdala and ventral tegmental area) (FWE corrected =0.05) (2) subjective craving did not differ significantly between groups (3) Group by time generalized psychophysiological interaction analyses showed increased right frontoparietal network engagement ({beta}=2.63, p=0.0308) following stimulation, and increased top-down inhibitory regulation of frontoparietal network on right ventral striatum ({beta}=1.99, p=0.037) and left medial amygdala ({beta}=1.97, p=0.039) (4) Electric field strength in the right frontal/parietal node predicted frontoparietal network engagement in the active group (r=0.43, p=0.02). ConclusionTogether, these findings demonstrate that theta-band frontoparietal tACS can modulate activity and task-dependent coupling within cortical-subcortical circuits in OUD, supporting network-targeted neuromodulation as a potential intervention for addiction. Significance StatementAddiction is linked to imbalances in cortico-subcortical brain circuits that control reward processing and craving. This study tested whether a non-invasive brain stimulation method-- theta-band transcranial alternating current stimulation (tACS)--can rebalance these circuits in people with opioid use disorder. Using advanced brain imaging, we found that tACS strengthened communication within frontoparietal brain regions involved in self-control while reducing their connections with reward and emotion centers. These brain changes were linked to reduced craving responses to drug cues. Our results demonstrate that dual-site, network-targeted tACS modulates neural activity and task-dependent engagement of brain circuits during drug cue reactivity in addiction, supporting its potential as a novel therapeutic approach.

Background and HypothesisAbnormal default mode network (DMN) connectivity was observed in both tobacco use and psychotic spectrum disorders, but it remains unknown how psychosis impacts the relationship between connectivity and tobacco use. Interventions targeting the left lateral parietal DMN node (LLPDMN) have modulated DMN connectivity and nicotine craving in psychosis. We aimed to investigate relationships between DMN connectivity, psychotic illness, and tobacco use. Study Design336 participants (psychosis: n=161, control: n=175) reported their tobacco use history and underwent resting-state functional magnetic resonance imaging. We calculated connectivity within DMN and salience network (SN), between DMN-SN, and from LLPDMN to other DMN and SN nodes. Logistic and LASSO regression with bootstrapping were performed to investigate diagnosis-by-connectivity interactions on lifetime tobacco use. Exploratory brainwide analysis was conducted by regressing brainwide connectivity to LLPDMN against daily cigarette use. Study ResultsWe observed a significant diagnosis-by-DMN connectivity interaction for lifetime tobacco use (p=0.0281, coefficient=0.457, OR=1.579, 95% CI=[1.063, 2.411]); in the psychosis group, higher DMN connectivity was associated with higher odds of lifetime tobacco use. LASSO regression yielded four predictors of lifetime tobacco use: age, diagnosis, LLPDMN connectivity to a prefrontal SN node, and the interaction between diagnosis and LLPDMN connectivity to a right parietal DMN node. Brainwide analysis identified bilateral somatomotor clusters where higher connectivity to LLPDMN correlated with higher daily cigarette use (voxel-wise p<0.001, cluster p<0.05). ConclusionsPsychosis diagnosis modified relationship between DMN connectivity and tobacco use. Modulating DMN connectivity may provide a psychosis-specific treatment target for tobacco dependence.

Opioid use disorder (OUD) is characterized by compulsive drug seeking and impaired executive control arising from maladaptive plasticity within cortico-striatal circuits. While transcriptomic studies have identified coding gene alterations in the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC), the contribution of the noncoding genome remains poorly defined. Here, we performed integrative transcriptomic analysis of postmortem human NAc and DLPFC to systematically identify and characterize long noncoding RNAs (lncRNAs) in OUD. We identified 36,225 lncRNA loci expressed across reward and executive regions, approximately half of which were previously unannotated. OUD was associated with widespread lncRNA dysregulation in NAc and DLPFC, with lncRNA-centered co-expression modules enriched for neuroimmune signaling, phosphorylation-dependent synaptic pathways, and intracellular receptor cascades. Notably, OUD disrupted circadian rhythmicity of lncRNAs to a degree comparable to or exceeding mRNAs, implicating temporal reorganization of noncoding networks in addiction pathology. Integration with single-nucleus transcriptomic data revealed pronounced neuronal and glial cell type specificity among OUD-associated lncRNAs. Together, these findings demonstrate that lncRNAs represent a critical regulatory layer in reward and executive circuits and suggest that spatial, temporal, and cellular remodeling of the noncoding transcriptome contributes to circuit dysfunction in OUD.

BackgroundBipolar disorder (BIP) frequently co-occurs with heightened substance use (SU) and substance use disorders (SUDs). Although the strong co-occurrence of these heritable traits points to shared genetic susceptibility, the extent to which there are differences in how SU and SUD overlap with BIP genetic architecture remains unclear. MethodsWe quantified the polygenic overlap between BIP and SUDs (alcohol, cannabis, opioid, and tobacco), and BIP and SU traits (drinks per week, lifetime cannabis use, prescription_opioid use, and smoking initiation) using GWAS summary statistics and trivariate MiXeR. We then isolated the general and unique genetic contributions of SUD and SU using GWAS-by-subtraction via GenomicSEM. Next, we tested associations between polygenic risk scores (PRSs) derived from these latent factors and diagnostic and behavioral outcomes in the Norwegian Mother, Father and Child Cohort Study. Finally, we applied GSA-MiXeR to explore pleiotropic pathway enrichment shared between the latent factors and BIP. ResultsWe found extensive polygenic overlap between traits, with SUDs being more genetically correlated with BIP than SU traits. The unique SUD factor correlated positively with psychiatric disorders, whereas unique SU correlated negatively. PRSs for BIP, shared SUD/SU, and unique SUD were significantly associated with BIP, SUD, and comorbid SUD-BIP; PRS for unique SU was only associated with self-reported lifetime SU. GSA-MiXeR revealed richer gene-set enrichment for SUD/BIP than SU/BIP implicating dopamine signaling and interneuron function. ConclusionBy dissecting the genetic liability to SUD and SU and investigating their relationship with BIP we find a genetic link driven by substance dependence but not substance use more broadly.

Obesity and metabolic dysfunction are among the strongest risk factors for poor brain and mental health, yet the neural mechanisms linking metabolism, brain, and behaviour remains poorly understood. Here, we provide the first evidence for two distinct large-scale brain network configurations--one associated with metabolic health and another with obesity-- identified using resting-state fMRI data and metabolic phenotypes from a large community cohort (N = 564). While obesity was linked to enhanced coupling between subcortical reward and higher-order cortical networks, metabolic health was characterized by functional integration among default mode, salience, and frontoparietal control regions (metabolic health functional connectivity; MHFC). The MHFC network mediated the relationship between eating restraint and metabolic health, independent on individuals body weight and metabolic status, and it was replicated with data from a different time point. Longitudinal analysis showed that change of MHFC strength predicted metabolic indicators over time, suggesting a role for this network as a potential marker of metabolic resilience. These findings reveal a neurobiological pathway through which executive and interoceptive regulatory systems contribute to metabolic health, offering new insights into the brain mechanisms linking eating behaviour, metabolism, and brain function.

In 2024, approximately 30% of U.S. adolescents reported having consumed alcohol at least once in their lifetime, with about 25% of these individuals engaging in binge drinking. Adolescent alcohol use is associated with neurodevelopmental impairments, elevated risk of later alcohol use, and mental health disorders. These findings underscore the importance of identifying the variables driving adolescent alcohol use and leveraging them for early identification and targeted intervention. Previous studies have typically developed machine-learning classification models that use neuroimaging data in combination with limited clinical measurements. Neuroimaging data are expensive and difficult to obtain at scale, whereas clinical measures are more practical for large-scale screening due to their low cost and widespread accessibility. However, clinical-only approaches for alcohol drinking classification remain largely underexplored. Furthermore, prior studies have often focused on adults, limiting generalizability to the broader adolescent population. Additionally, confounding factors such as age and substance use, which are strongly correlated with alcohol consumption, have often been inadequately addressed, potentially inflating classification performance. Finally, class imbalance remains a persistent challenge, with prior attempts yielding only limited improvements. To address these limitations, we propose FocalTab, a framework that integrates TabPFN with focal loss for robust generalization and effective mitigation of class imbalance. The approach also incorporates an initial preprocessing step to remove confounding factors to account for age and substance-use. We compare FocalTab against state-of-the-art methods across different variable selections and dataset settings. FocalTab achieves the highest accuracy (84.3%) and specificity (80.0%) in the most stringent setting, in which both age and substance use variables were excluded, whereas competing models drop to near-chance specificity (12-24%). We further applied SHapley Additive exPlanations (SHAP) analysis to identify key clinical predictors of drinker classification, supporting enhanced screening and early intervention.