The potential of neuroimaging for identifying predictors of adolescent alcohol use initiation and misuse

RASGRF2 as a potential pathogenic gene mediating the progression of alcoholic hepatitis to alcohol-related cirrhosis and hepatocellular carcinoma

BACKGROUND AND AIMS

Alcoholic hepatitis (AH) and hepatocellular carcinoma (HCC) are common liver diseases. Chronic inflammation caused by AH can progress to alcoholic cirrhosis (AC) and eventually HCC.

METHODS

This study sought to ascertain potential shared genes between AH and HCC through the utilization of multiple transcriptome databases. Employing an immune infiltration analysis, and calculating the correlation between shared genes and immune infiltration results, in conjunction with independent bulk transcriptome validation sets, led to the identification of core shared genes. Subsequently, single-cell transcriptome data, clinical sample immunohistochemistry experiments, and overexpressed core shared genes in HepG2 cells were employed to validate the core shared genes of AH and HCC.

RESULTS

Through the bulk transcriptome discovery sets of AH and HCC, 206 potential shared genes were identified. After screening with two machine learning algorithms, five shared genes remained. Combining the results of the immune infiltration and bulk transcriptome results from an independent validation cohort, the core shared gene was determined to be RASGRF2. Single-cell data further demonstrated that RASGRF2 and its downstream genes were highly expressed in AH, AC, and HCC tissues. Spatial transcriptome data indicated that RASGRF2 was highly expressed in HCC tumor tissues. Compared with the paracancerous tissues, the RASGRF2 gene was significantly overexpressed in HCC tissues. Overexpression of RASGRF2 in HepG2 cells resulted in significantly enhanced migration, invasion, and proliferation abilities.

CONCLUSION

RASGRF2 serve as a pathogenic gene that mediates the progression of AH to AC and potentially to HCC.

Neural correlates associated with a family history of alcohol use disorder: A narrative review of recent findings

A family history of alcohol use disorder (AUD) is associated with a significantly increased risk of developing AUD in one's lifetime. The previously reviewed literature suggests there are structural and functional neurobiological markers associated with familial AUD, but to our knowledge, no recent review has synthesized the latest findings across neuroimaging studies in this at-risk population. For this narrative review, we conducted keyword searches in electronic databases to find cross-sectional and longitudinal studies (2015-present) that used magnetic resonance imaging (MRI), diffusion tensor imaging, task-based functional MRI (fMRI), and/or resting state functional connectivity MRI. These studies were used to identify gray matter, white matter, and brain activity markers of risk and resilience in family history positive (FHP) individuals with a family history of AUD. FHP individuals have greater early adolescent thinning of executive functioning (frontal lobe) regions; however, some studies have reported null effects or greater gray matter volume and thickness relative to family history negative (FHN) peers without familial AUD. FHP individuals also have white matter microstructure alterations, such as reduced integrity of fronto-striatal pathways. Recent fMRI studies have found greater inhibitory control activity in FHP individuals, while reward-related findings are mixed. A growing interest in identifying intrinsic connectivity differences between FHP and FHN individuals has emerged in recent years. Familial AUD is related to both structural and functional brain alterations. Research should continue to focus on (1) longitudinal analyses with larger samples, (2) assessment of personal substance use and prenatal exposure to alcohol, (3) the effects of comorbid familial psychopathology, (4) examination of sex-specific markers of risk and resilience, (5) neural predictors of alcohol use initiation, and (6) brain-behavior relationships. These efforts would aid the design of neurobiologically informed prevention and intervention efforts focused on this at-risk population.

Early onset adolescent binge drinking is associated with reduced white matter integrity in post-9/11 adult veterans

Adolescence represents a critical period of neural development during which binge drinking (BD) is prevalent. Though prior work has shown that white matter (WM) integrity is susceptible to damage from excessive alcohol intake in adults, the effect of early adolescent BD on WM health in adulthood remains unknown. Veterans with a history of BD onset before age 15 [n = 49; mean age = 31.8 years; early-onset adolescent binge drinkers (EBD)] and after age 15 [n = 290; mean age = 32.2 years; late-onset adolescent binge drinkers (LBD)] were studied with diffusion tensor imaging. Group differences in fractional anisotropy (FA; movement of water molecules along the WM) and mean diffusivity (MD; average movement of water molecules) were examined as indices of WM integrity using FreeSurfer and FMRIB Software Library (FSL) processing streams. Lower FA and higher MD are thought to represent degradations in WM integrity. A reference group (RG) of social drinkers with no history of BD (n = 31) was used to provide comparative normative data. We observed widespread decreased FA and increased MD in EBDs, compared to LBDs, as well as decreased FA in the pars triangularis, lateral orbitofrontal cortex, superior frontal cortex, isthmus cingulate, and genu and splenium of the corpus callosum EBDs also had lower WM integrity compared to the RG. Adults who initiated BD during early adolescence demonstrated decreased FA and increased MD throughout the frontostriatal circuits that mediate inhibitory control and thus may result in impulsive behavior and a predisposition for developing alcohol use disorder during adulthood.

Predictors of problematic adult alcohol, cannabis, and other substance use: A longitudinal study of two samples

This study examined whether a key set of adolescent and early adulthood risk factors predicts problematic alcohol, cannabis, and other substance use in established adulthood. Two independent samples from the Child Development Project (CDP; n = 585; 48% girls; 81% White, 17% Black, 2% other race/ethnicity) and Fast Track (FT; n = 463; 45% girls; 52% White, 43% Black, 5% other race/ethnicity) were recruited in childhood and followed through age 34 (CDP) or 32 (FT). Predictors of substance use were assessed in adolescence based on adolescent and parent reports and in early adulthood based on adult self-reports. Adults reported their own problematic substance use in established adulthood. In both samples, more risk factors from adolescence and early adulthood predicted problematic alcohol use in established adulthood (compared to problematic cannabis use and other substance use). Externalizing behaviors and prior substance use in early adulthood were consistent predictors of problematic alcohol and cannabis misuse in established adulthood across samples; other predictors were specific to the sample and type of substance misuse. Prevention efforts might benefit from tailoring to address risk factors for specific substances, but prioritizing prevention of externalizing behaviors holds promise for preventing both alcohol and cannabis misuse in established adulthood.

Uncontrolled eating and sensation-seeking partially explain the prediction of future binge drinking from adolescent brain structure

Binge drinking behavior in early adulthood can be predicted from brain structure during early adolescence with an accuracy of above 70%. We investigated whether this accurate prospective prediction of alcohol misuse behavior can be explained by psychometric variables such as personality traits or mental health comorbidities in a data-driven approach. We analyzed a subset of adolescents who did not have any prior binge drinking experience at age 14 (IMAGEN dataset, n = 555, 52.61% female). Participants underwent structural magnetic resonance imaging at age 14, binge drinking assessments at ages 14 and 22, and psychometric questionnaire assessments at ages 14 and 22. We derived structural brain features from T1-weighted magnetic resonance and diffusion tensor imaging. Using Machine Learning (ML), we predicted binge drinking (age 22) from brain structure (age 14) and used counterbalancing with oversampling to systematically control for 110 + variables from a wide range of social, personality, and other psychometric characteristics potentially associated with binge drinking. We evaluated if controlling for any variable resulted in a significant reduction in ML prediction accuracy. Sensation-seeking (-13.98 ± 1.68%), assessed via the Substance Use Risk Profile Scale at age 14, and uncontrolled eating (-13.98 ± 3.28%), assessed via the Three-Factor-Eating-Questionnaire at age 22, led to significant reductions in mean balanced prediction accuracy upon controlling for them. Thus, sensation-seeking and binge eating could partially explain the prediction of future binge drinking from adolescent brain structure. Our findings suggest that binge drinking and binge eating at age 22 share common neurobiological precursors discovered by the ML model. These neurobiological precursors seem to be associated with sensation-seeking at age 14. Our results facilitate early detection of increased risk for binge drinking and inform future clinical research in trans-diagnostic prevention approaches for adolescent alcohol misuse.

Neuroanatomical predictors of problematic alcohol consumption in adolescents: a systematic review of longitudinal studies

AIMS

This study aimed to systematically review the literature on neuroanatomical predictors of future problematic drinking in adolescents.

METHODS

Using PRISMA guidelines, a systematic review was conducted to evaluate neuroanatomical predictors of problematic alcohol consumption in adolescents. EMBASE, MEDLINE, and PsycINFO databases were searched from inception to 6 January 2023. Studies were included if they were original, had a prospective design, had a sample size of at least 12, had a follow-up period of at least 1 year, had at least one structural neuroimaging scan before 18 with no prior alcohol use, and had alcohol use as the primary outcome. Studies were excluded if they had animals only and were not in English. Risk of bias was conducted using the CASP tool.

RESULTS

Out of 1412 studies identified, 19 studies met the criteria, consisting of 11 gray matter (n = 4040), 5 white matter (n = 319), and 3 assessing both (n = 3608). Neuroanatomical predictors of future problematic drinking in adolescents were reported to be distributed across various brain regions such as the orbitofrontal cortex and paralimbic regions. However, the findings were largely heterogeneous.

CONCLUSIONS

This is the first systematic review to map out the existing literature on neuroanatomical predictors of problematic drinking in adolescents. Future research should focus on the aforementioned regions to determine their role in predicting future problematic drinking with more certainty.

Adolescent Neurodevelopment Within the Context of Impulsivity and Substance Use

Purpose of Review

The aim of the present review is to provide an update on recent studies examining adolescent neurodevelopment in the context of impulsivity and substance use. We provide a review of the neurodevelopmental changes in brain structure and function related to impulsivity, substance use, and their intersection.

Recent Findings

When examining brain structure, smaller gray matter volume coupled with lower white matter integrity is associated with greater impulsivity across three components: trait impulsivity, choice impulsivity, and response inhibition. Altered functional connectivity in networks including the inhibitory control network and reward processing network confers risk for greater impulsivity and substance use.

Summary

Across brain structure and function, there is evidence to suggest that overlapping areas involved in the rise in impulsivity during adolescence contribute to early substance use initiation and escalation. These overlapping neurodevelopmental correlates have promising implications for prevention and early intervention efforts for adolescent substance use.

Randomized Controlled Trial of an Alcohol-related Sexual Risk Reduction Intervention with Adolescents: The Role of Neurocognitive Activation During Risky Decision-Making

Justice-involved youth are at a higher risk of negative outcomes from sexual activity and alcohol use relative to their non-justice involved peers. In the current study, we tested the extent to which variability in neurocognitive response (i.e., activation in the right superior parietal lobule; rSPL) during a risky decision-making task moderated the success of a sexual risk reduction intervention. In a cluster randomized trial blocked by gender, justice-involved adolescents (N = 269) first completed a risky decision-making task during a magnetic resonance imaging (MRI) session, then were assigned to an information-only control (GINFO) or sexual risk reduction intervention incorporating alcohol risk reduction content (GPI + GMET) and then re-contacted every three months for one year. Youth in the GPI + GMET intervention reported less sexual risk behavior 12 months after intervention than those in the control. Although neurocognitive activation was associated with sexual risk behavior, it did not moderate intervention outcomes. This risk-reduction intervention appears to work equally well across a range of neurocognitive responses.

Ventral striatal resting-state functional connectivity in adolescents is associated with earlier onset of binge drinking

BACKGROUND

Earlier engagement in heavy drinking during adolescence is a risk factor for the development of alcohol use disorders later in life. Longitudinal studies in adolescents have linked brain structure and task-evoked function to future alcohol use; however, less is known about how intrinsic network-level interactions relate to future substance use during this developmental period.

METHODS

In this prospective longitudinal study, resting-state functional connectivity of the ventral striatum, risky decision making, and sensation seeking were measured in 73 adolescents at baseline. Participants were between the ages of 14 and 15 and had no substantial history of substance use upon study entry. Follow-up interviews were conducted approximately every 3 months to assess the initiation of binge drinking (≥ 5 or ≥ 4 drinks per occasion for males or females, respectively).

RESULTS

Adolescents who began binge drinking sooner exhibited greater connectivity of the ventral striatum to the left precuneus, left angular gyrus, and the left superior frontal gyrus. Greater connectivity of the ventral striatum to the right insula/putamen was associated with longer duration to the onset of binge drinking. Resting-state functional connectivity in these regions was not associated with baseline assessments of risky decision making or sensation seeking.

CONCLUSIONS

Findings provide novel information about potential risk factors for early initiation of heavy alcohol use. Interventions that target relevant resting-state networks may enhance prevention efforts to decrease adolescent substance use by prolonging onset to heavier levels of alcohol consumption.

Cerebral microstructural abnormalities in impulsivity: a magnetic resonance study

Studies that investigated neurobiological parameters subtended to impulsivity trait found their relationship with structural and functional brain alterations. No studies investigated the white matter microstructural attributes of impulsivity in a large sample of healthy subjects. In the present study 1007 subjects from Human Connectome Project public dataset were divided in two groups, impulsive and not impulsive, basing on Delay Discounting task score. For both groups brain morphometric and microstructural characteristics were investigated. A t-test (correct for multiple comparisons) was performed for each brain parcel and impulsivity measure. Magnetic resonance diffusion images were pre-processed and selected to perform a voxelwise analysis on the fractional anisotropy (FA) maps between impulsive and not impulsive groups. Group analysis showed significant differences in morphometric brain data mainly for temporal and frontal lobes. The impulsive group presented higher FA values in four regions: bilateral medial lemniscus and midbrain reticular formation, right superior longitudinal fasciculus, left forceps major, right corticospinal tract. Not impulsive group showed higher FA values in two significant regions: right and left anterior thalamus radiation. Concluding, macroscopic and microstructural brain alterations were assessed, identifying new neuroanatomical substrates for multidimensional impulsivity construct in a large sample of healthy subjects.

Toward Addiction Prediction: An Overview of Cross-Validated Predictive Modeling Findings and Considerations for Future Neuroimaging Research

Substance use is a leading cause of disability and death worldwide. Despite the existence of evidence-based treatments, clinical outcomes are highly variable across individuals, and relapse rates following treatment remain high. Within this context, methods to identify individuals at particular risk for unsuccessful treatment (i.e., limited within-treatment abstinence), or for relapse following treatment, are needed to improve outcomes. Cumulatively, the literature generally supports the hypothesis that individual differences in brain function and structure are linked to differences in treatment outcomes, although anatomical loci and directions of associations have differed across studies. However, this work has almost entirely used methods that may overfit the data, leading to inflated effect size estimates and reduced likelihood of reproducibility in novel clinical samples. In contrast, cross-validated predictive modeling (i.e., machine learning) approaches are designed to overcome limitations of traditional approaches by focusing on individual differences and generalization to novel subjects (i.e., cross-validation), thereby increasing the likelihood of replication and potential translation to novel clinical settings. Here, we review recent studies using these approaches to generate brain-behavior models of treatment outcomes in addictions and provide recommendations for further work using these methods.

Inhibitory-control event-related potentials correlate with individual differences in alcohol use

Impulsivity is a multidimensional construct that is related to different aspects of alcohol use, abuse, and dependence. Inhibitory control, one facet of impulsivity, can be assayed using the stop-signal task (SST) and quantified behaviorally via the stop-signal reaction time (SSRT) and electrophysiologically using event-related potentials (ERPs). Research on the relationship between alcohol use and SSRTs, and between alcohol use and inhibitory-control ERPs, is mixed. Here, adult alcohol users (n = 79), with a wide range of scores on the Alcohol Use Disorders Identification Test (AUDIT), completed the SST under electroencephalography (EEG) (70% of participants had AUDIT total scores greater than or equal to 8). Other measures, including demographic, self-report, and task-based measures of impulsivity, personality, and psychological factors, were also recorded. A machine-learning method with penalized linear regression was used to correlate individual differences in alcohol use with impulsivity measures. Four separate models were tested, with out-of-sample validation used to quantify performance. ERPs alone statistically predicted alcohol use (cross-validated r = 0.28), with both early and late ERP components contributing to the model (larger N2, but smaller P3, amplitude). Behavioral data from a wide range of impulsivity measures were also associated with alcohol use (r = 0.37). SSRT was a relatively weak statistical predictor, whereas the Stroop interference effect was relatively strong. The addition of nonimpulsivity behavioral measures did not improve the correlation (r = 0.34) and was similar when ERPs were combined with non-ERP data (r = 0.29). These findings show that inhibitory control ERPs are robustly correlated individual differences in alcohol use.

EEG spectral power, but not theta/beta ratio, is a neuromarker for adult ADHD

Adults with attention-deficit/hyperactivity disorder (ADHD) have been described as having altered resting-state electroencephalographic (EEG) spectral power and theta/beta ratio (TBR). However, a recent review (Pulini et al. 2018) identified methodological errors in neuroimaging, including EEG, ADHD classification studies. Therefore, the specific EEG neuromarkers of adult ADHD remain to be identified, as do the EEG characteristics that mediate between genes and behaviour (mediational endophenotypes). Resting-state eyes-open and eyes-closed EEG was measured from 38 adults with ADHD, 45 first-degree relatives of people with ADHD and 51 unrelated controls. A machine learning classification analysis using penalized logistic regression (Elastic Net) examined if EEG spectral power (1-45 Hz) and TBR could classify participants into ADHD, first-degree relatives and/or control groups. Random-label permutation was used to quantify any bias in the analysis. Eyes-open absolute and relative EEG power distinguished ADHD from control participants (area under receiver operating characteristic = 0.71-0.77). The best predictors of ADHD status were increased power in delta, theta and low-alpha over centro-parietal regions, and in frontal low-beta and parietal mid-beta. TBR did not successfully classify ADHD status. Elevated eyes-open power in delta, theta, low-alpha and low-beta distinguished first-degree relatives from controls (area under receiver operating characteristic = 0.68-0.72), suggesting that these features may be a mediational endophenotype for adult ADHD. Resting-state EEG spectral power may be a neuromarker and mediational endophenotype of adult ADHD. These results did not support TBR as a diagnostic neuromarker for ADHD. It is possible that TBR is a characteristic of childhood ADHD.

Response Inhibition and Binge Drinking During Transition to University: An fMRI Study

BACKGROUND

Binge Drinking (BD), a highly prevalent drinking pattern among youth, has been linked with anomalies in inhibitory control. However, it is still not well characterized whether the neural mechanisms involved in this process are compromised in binge drinkers (BDs). Furthermore, recent findings suggest that exerting inhibitory control to alcohol-related stimuli requires an increased effort in BDs, relative to controls, but the brain regions subserving these effects have also been scarcely investigated. Here we explored the impact of BD on the pattern of neural activity mediating response inhibition and its modulation by the motivational salience of stimuli (alcohol-related content).

METHODS

Sixty-seven (36 females) first-year university students, classified as BDs (n = 32) or controls (n = 35), underwent fMRI as they performed an alcohol-cued Go/NoGo task in which pictures of alcoholic or non-alcoholic beverages were presented as Go or NoGo stimuli.

RESULTS

During successful inhibition trials, BDs relative to controls showed greater activity in the bilateral inferior frontal gyrus (IFG), extending to the anterior insula, a brain region usually involved in response inhibition tasks, despite the lack of behavioral differences between groups. Moreover, BDs displayed increased activity in this region restricted to the right hemisphere when inhibiting a prepotent response to alcohol-related stimuli.

CONCLUSIONS

The increased neural activity in the IFG/insula during response inhibition in BDs, in the absence of behavioral impairments, could reflect a compensatory mechanism. The findings suggest that response inhibition-related activity in the right IFG/insula is modulated by the motivational salience of stimuli and highlight the role of this brain region in suppressing responses to substance-associated cues.

Biotechnical development of genetic addiction risk score (GARS) and selective evidence for inclusion of polymorphic allelic risk in substance use disorder (SUD)

Research into the neurogenetic basis of addiction identified and characterized by Reward Deficiency Syndrome (RDS) includes all drug and non-drug addictive, obsessive and compulsive behaviors. We are proposing herein that a new model for the prevention and treatment of Substance Use Disorder (SUD) a subset of RDS behaviors, based on objective biologic evidence, should be given serious consideration in the face of a drug epidemic. The development of the Genetic Addiction Risk Score (GARS) followed seminal research in 1990, whereby, Blum’s group identified the first genetic association with severe alcoholism published in JAMA. While it is true that no one to date has provided adequate RDS free controls there have been many studies using case –controls whereby SUD has been eliminated. We argue that this deficiency needs to be addressed in the field and if adopted appropriately many spurious results would be eliminated reducing confusion regarding the role of genetics in addiction. However, an estimation, based on these previous literature results provided herein, while not representative of all association studies known to date, this sampling of case- control studies displays significant associations between alcohol and drug risk. In fact, we present a total of 110,241 cases and 122,525 controls derived from the current literature. We strongly suggest that while we may take argument concerning many of these so-called controls (e.g. blood donors) it is quite remarkable that there are a plethora of case –control studies indicating selective association of these risk alleles ( measured in GARS) for the most part indicating a hypodopaminergia. The paper presents the detailed methodology of the GARS. Data collection procedures, instrumentation, and the analytical approach used to obtain GARS and subsequent research objectives are described. Can we combat SUD through early genetic risk screening in the addiction field enabling early intervention by the induction of dopamine homeostasis? It is envisaged that GARS type of screening will provide a novel opportunity to help identify causal pathways and associated mechanisms of genetic factors, psychological characteristics, and addictions awaiting additional scientific evidence including a future meta- analysis of all available data –a work in progress.

Nucleus accumbens connectivity at rest is associated with alcohol consumption in young male adults

Alcohol consumption during adolescence might impede normal brain development, while more excessive drinking during this period poses a risk for developing alcohol use disorder. Here it was tested whether nucleus accumbens (NAcc) resting-state functional connectivity could be associated with lifetime drinking behavior in young adults, and whether it could predict their alcohol consumption during a one-year follow-up period. The current investigation was part of the bicentric Learning and Alcohol Dependence (LeAD) population-based prospective cohort study. One hundred and eighty-four 18-year-old male social drinking volunteers without a lifetime diagnosis of psychotic, bipolar, or alcohol use disorder were recruited from the general population. Seed-based resting-state functional connectivity was calculated for the bilateral NAcc in each participant. Across the group, the association between NAcc functional connectivity and lifetime alcohol consumption was assessed (p < .05, whole-brain FWE-corrected). Individual connectivity values were then extracted from regions that demonstrated a significant association to predict drinking behavior during a one-year follow-up period (n = 143), correcting for lifetime alcohol consumption. Weaker connectivity between the left NAcc and bilateral dorsolateral prefrontal cortex, inferior frontal gyrus, left caudate nucleus, left putamen, and left insula was associated with greater lifetime alcohol consumption, as well as with greater alcohol consumption during the one-year follow-up period. Our findings underscore the relevance of fronto-striatal connectivity to the field of alcohol research. Impaired prefrontal cognitive control might mediate excessive drinking behavior and may prove a promising biomarker for risk of future alcohol (ab)use.

Corticostriatal Oscillations Predict High vs. Low Drinkers in a Rat Model of Limited Access Alcohol Consumption

Individuals differ in their vulnerability to develop alcohol dependence, which is determined by innate and environmental factors. The corticostriatal circuit is heavily involved in the development of alcohol dependence and may contain neural information regarding vulnerability to drink excessively. In the current experiment, we hypothesized that we could characterize high and low alcohol-drinking rats (HD and LD, respectively) based on corticostriatal oscillations and that these subgroups would differentially respond to corticostriatal brain stimulation. Male Sprague–Dawley rats (n = 13) were trained to drink 10% alcohol in a limited access paradigm. In separate sessions, local field potentials (LFPs) were recorded from the nucleus accumbens shell (NAcSh) and medial prefrontal cortex (mPFC). Based on training alcohol consumption levels, we classified rats using a median split as HD or LD. Then, using machine-learning, we built predictive models to classify rats as HD or LD by corticostriatal LFPs and compared the model performance from real data to the performance of models built on data permutations. Additionally, we explored the impact of NAcSh or mPFC stimulation on alcohol consumption in HD vs. LD. Corticostriatal LFPs were able to predict HD vs. LD group classification with greater accuracy than expected by chance (>80% accuracy). Moreover, NAcSh stimulation significantly reduced alcohol consumption in HD, but not LD (p < 0.05), while mPFC stimulation did not alter drinking behavior in either HD or LD (p > 0.05). These data collectively show that the corticostriatal circuit is differentially involved in regulating alcohol intake in HD vs. LD rats, and suggests that corticostriatal activity may have the potential to predict a vulnerability to develop alcohol dependence in a clinical population.

Corticostriatal Oscillations Predict High vs. Low Drinkers in a Rat Model of Limited Access Alcohol Consumption

Individuals differ in their vulnerability to develop alcohol dependence, which is determined by innate and environmental factors. The corticostriatal circuit is heavily involved in the development of alcohol dependence and may contain neural information regarding vulnerability to drink excessively. In the current experiment, we hypothesized that we could characterize high and low alcohol-drinking rats (HD and LD, respectively) based on corticostriatal oscillations and that these subgroups would differentially respond to corticostriatal brain stimulation. Male Sprague-Dawley rats (n = 13) were trained to drink 10% alcohol in a limited access paradigm. In separate sessions, local field potentials (LFPs) were recorded from the nucleus accumbens shell (NAcSh) and medial prefrontal cortex (mPFC). Based on training alcohol consumption levels, we classified rats using a median split as HD or LD. Then, using machine-learning, we built predictive models to classify rats as HD or LD by corticostriatal LFPs and compared the model performance from real data to the performance of models built on data permutations. Additionally, we explored the impact of NAcSh or mPFC stimulation on alcohol consumption in HD vs. LD. Corticostriatal LFPs were able to predict HD vs. LD group classification with greater accuracy than expected by chance (>80% accuracy). Moreover, NAcSh stimulation significantly reduced alcohol consumption in HD, but not LD (p < 0.05), while mPFC stimulation did not alter drinking behavior in either HD or LD (p > 0.05). These data collectively show that the corticostriatal circuit is differentially involved in regulating alcohol intake in HD vs. LD rats, and suggests that corticostriatal activity may have the potential to predict a vulnerability to develop alcohol dependence in a clinical population.

Connectome-Based Prediction of Cocaine Abstinence

OBJECTIVE

The authors sought to identify a brain-based predictor of cocaine abstinence by using connectome-based predictive modeling (CPM), a recently developed machine learning approach. CPM is a predictive tool and a method of identifying networks that underlie specific behaviors ("neural fingerprints").

METHODS

Fifty-three individuals participated in neuroimaging protocols at the start of treatment for cocaine use disorder, and again at the end of 12 weeks of treatment. CPM with leave-one-out cross-validation was conducted to identify pretreatment networks that predicted abstinence (percent cocaine-negative urine samples during treatment). Networks were applied to posttreatment functional MRI data to assess changes over time and ability to predict abstinence during follow-up. The predictive ability of identified networks was then tested in a separate, heterogeneous sample of individuals who underwent scanning before treatment for cocaine use disorder (N=45).

RESULTS

CPM predicted abstinence during treatment, as indicated by a significant correspondence between predicted and actual abstinence values (r=0.42, df=52). Identified networks included connections within and between canonical networks implicated in cognitive/executive control (frontoparietal, medial frontal) and in reward responsiveness (subcortical, salience, motor/sensory). Connectivity strength did not change with treatment, and strength at posttreatment assessment also significantly predicted abstinence during follow-up (r=0.34, df=39). Network strength in the independent sample predicted treatment response with 64% accuracy by itself and 71% accuracy when combined with baseline cocaine use.

CONCLUSIONS

These data demonstrate that individual differences in large-scale neural networks contribute to variability in treatment outcomes for cocaine use disorder, and they identify specific abstinence networks that may be targeted in novel interventions.

Striatal activity correlates with stimulant-like effects of alcohol in healthy volunteers

Individuals who experience greater stimulation and less sedation from alcohol are at increased risk for alcohol-related problems. However, little is known regarding the neurobiological mechanisms underlying subjective response to alcohol. The current study examined the degree to which alcohol-induced brain activation correlates with ratings of stimulation and sedation, using a within-subjects, double-blind, placebo-controlled design. Participants (N = 34 healthy adults with no history of alcohol use disorder) completed three sessions: a calibration session to determine the duration of infusion needed to bring the breath alcohol to 80 mg/dl for each subject, and two counterbalanced fMRI sessions with placebo and alcohol administration. During the fMRI sessions, participants underwent 50 min scans, which included a 10 min baseline period, the IV infusion period needed to bring breath alcohol concentration (BrAC) to a peak 80 mg/dl (on the alcohol session), followed by a post-peak decline period. Participants rated their subjective stimulation and sedation at regular intervals throughout the scan. A priori VOI analyses showed that the time course of stimulation correlated with BOLD signal in the striatum. The time course of sedation did not correlate with BOLD signal in any VOIs. There were no correlations in primary visual cortex, which served as a control. These findings are the first to show that alcohol effects in the striatum are linked to the positive, stimulant-like effects of the drug and advance our understanding of the neurobiological mechanisms underlying individual differences in subjective responses to alcohol, and more broadly, risk for alcohol use disorders.

A Combination of Impulsivity Subdomains Predict Alcohol Intoxication Frequency

BACKGROUND

Impulsivity, broadly characterized as the tendency to act prematurely without foresight, is linked to alcohol misuse in college students. However, impulsivity is a multidimensional construct and different subdomains likely underlie different patterns of alcohol misuse. Here, we quantified the association between alcohol intoxication frequency and alcohol consumption frequency and choice, action, cognitive, and trait domains of impulsivity.

METHODS

University student drinkers (n = 106) completed a battery of demographic and alcohol-related items, as well as self-report and task-based measures indexing different facets of impulsivity. Two orthogonal latent factors, intoxication frequency and alcohol consumption frequency, were generated. Their validity was demonstrated with respect to adverse consequences of alcohol use. Machine learning with penalized regression and feature selection was then utilized to predict intoxication and alcohol consumption frequency using all impulsivity subdomains. Out-of-sample validation was used to quantify model performance.

RESULTS

Impulsivity measures alone were significant predictors of intoxication frequency, but not consumption frequency. Propensity for increased intoxication frequency was characterized by increased trait impulsivity, including the Disinhibition subscale of the Sensation Seeking Scale, Attentional and Non-planning subscales of the Barratt Impulsiveness Scale, increased task-based cognitive impulsivity (response time variability), and increased choice impulsivity (steeper delay discounting on a delay discounting questionnaire). A model combining impulsivity domains with other risk factors (gender; nicotine, cannabis, and other drug use; executive functioning; and learning processes) was also significant but did not outperform the model comprising of impulsivity alone.

CONCLUSIONS

Intoxication frequency, but not consumption frequency, was characterized by a number of impulsivity subdomains.

Alcohol use effects on adolescent brain development revealed by simultaneously removing confounding factors, identifying morphometric patterns, and classifying individuals

Group analysis of brain magnetic resonance imaging (MRI) metrics frequently employs generalized additive models (GAM) to remove contributions of confounding factors before identifying cohort specific characteristics. For example, the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) used such an approach to identify effects of alcohol misuse on the developing brain. Here, we hypothesized that considering confounding factors before group analysis removes information relevant for distinguishing adolescents with drinking history from those without. To test this hypothesis, we introduce a machine-learning model that identifies cohort-specific, neuromorphometric patterns by simultaneously training a GAM and generic classifier on macrostructural MRI and microstructural diffusion tensor imaging (DTI) metrics and compare it to more traditional group analysis and machine-learning approaches. Using a baseline NCANDA MR dataset (N = 705), the proposed machine learning approach identified a pattern of eight brain regions unique to adolescents who misuse alcohol. Classifying high-drinking adolescents was more accurate with that pattern than using regions identified with alternative approaches. The findings of the joint model approach thus were (1) impartial to confounding factors; (2) relevant to drinking behaviors; and (3) in concurrence with the alcohol literature.

Role of the innate immune system in the neuropathological consequences induced by adolescent binge drinking

Adolescence is a critical stage of brain maturation in which important plastic and dynamic processes take place in different brain regions, leading to development of the adult brain. Ethanol drinking in adolescence disrupts brain plasticity and causes structural and functional changes in immature brain areas (prefrontal cortex, limbic system) that result in cognitive and behavioral deficits. These changes, along with secretion of sexual and stress-related hormones in adolescence, may impact self-control, decision making, and risk-taking behaviors that contribute to anxiety and initiation of alcohol consumption. New data support the participation of the neuroimmune system in the effects of ethanol on the developing and adult brain. This article reviews the potential pathological bases that underlie the effects of alcohol on the adolescent brain, such as the contribution of genetic background, the perturbation of epigenetic programming, and the influence of the neuroimmune response. Special emphasis is given to the actions of ethanol in the innate immune receptor toll-like receptor 4 (TLR4), since recent studies have demonstrated that by activating the inflammatory TLR4/NFκB signaling response in glial cells, binge drinking of ethanol triggers the release of cytokines/chemokines and free radicals, which exacerbate the immune response that causes neuroinflammation/neural damage as well as short- and long-term neurophysiological, cognitive, and behavioral dysfunction. Finally, potential treatments that target the neuroimmune response to treat the neuropathological and behavioral consequences of adolescent alcohol abuse are discussed.