Medication Use is Associated with Distinct Microbial Features in Anxiety and Depression.

This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by DSM-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing and shallow shotgun sequencing were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and NeuroMAP CoBRE cohorts. The results highlight the significant influence of medication use; antidepressant use is associated with significant differences in gut microbiota beta diversity and has a larger effect size than NPD diagnosis. Next, specific microbes were associated with ANXD and MDD, highlighting their potential for non-pharmacological intervention. Finally, the study demonstrated the capability of Random Forest classifiers to predict diagnoses of NPD and medication use from microbial profiles, suggesting a promising direction for the use of gut microbiota as biomarkers for NPD. The findings suggest that future research on the gut microbiota's role in NPD and its interactions with pharmacological treatments are needed.

Exploring the role of neuronal-enriched extracellular vesicle miR-93 and interoception in major depressive disorder.

Major depressive disorder (MDD) is associated with interoceptive processing dysfunctions, but the molecular mechanisms underlying this dysfunction are poorly understood. This study combined brain neuronal-enriched extracellular vesicle (NEEV) technology and serum markers of inflammation and metabolism with Functional Magnetic Resonance Imaging (fMRI) to identify the contribution of gene regulatory pathways, in particular micro-RNA (miR) 93, to interoceptive dysfunction in MDD. Individuals with MDD (n = 41) and healthy comparisons (HC; n = 35) provided blood samples and completed an interoceptive attention task during fMRI. EVs were separated from plasma using a precipitation method. NEEVs were enriched by magnetic streptavidin bead immunocapture utilizing a neural adhesion marker (L1CAM/CD171) biotinylated antibody. The origin of NEEVs was validated with two other neuronal markers - neuronal cell adhesion molecule (NCAM) and ATPase Na+/K+ transporting subunit alpha 3 (ATP1A3). NEEV specificities were confirmed by flow cytometry, western blot, particle size analyzer, and transmission electron microscopy. NEEV small RNAs were purified and sequenced. Results showed that: (1) MDD exhibited lower NEEV miR-93 expression than HC; (2) within MDD but not HC, those individuals with the lowest NEEV miR-93 expression had the highest serum concentrations of interleukin (IL)-1 receptor antagonist, IL-6, tumor necrosis factor, and leptin; and (3) within HC but not MDD, those participants with the highest miR-93 expression showed the strongest bilateral dorsal mid-insula activation during interoceptive versus exteroceptive attention. Since miR-93 is regulated by stress and affects epigenetic modulation by chromatin re-organization, these results suggest that healthy individuals but not MDD participants show an adaptive epigenetic regulation of insular function during interoceptive processing. Future investigations will need to delineate how specific internal and external environmental conditions contribute to miR-93 expression in MDD and what molecular mechanisms alter brain responsivity to body-relevant signals.

Impulsivity in amphetamine use disorder: Examination of sex differences.

AIMS: This study aimed to test whether there are sex differences in the relationship between impulsivity and amphetamine use disorder (AMP). DESIGN: A naturalistic cross-sectional design was used. SETTING: The Tulsa 1000 study was held in Tulsa, OK, USA. PARTICIPANTS: There were two groups in this study: AMP+ (29F, 20M) and AMP- (57F, 33M). MEASUREMENTS: This project focuses on data related to impulsivity: UPPS-P impulsive behavior scale and a stop signal task (SST) during functional magnetic resonance imaging (fMRI) recording. Group, sex and their interaction were compared for UPPS-P ratings and SST fMRI and behavioral responses. FINDINGS: AMP+ reported higher UPPS-P positive and negative urgency scores (Ps < 0.001; r = 0.56 and 0.51) and displayed greater bilateral insula and amygdala responses across correct SST trials (Ps < 0.001, g range = 0.57-0.81) than AMP-. fMRI results indicated that AMP+ exhibited larger right anterior/middle insula, amygdala and nucleus accumbens signals during successful difficult stop trials than AMP- (Ps < 0.01; g = 0.63, 0.54 and 0.44, respectively). Crucially, two group × sex effects emerged: (a) within females, AMP+ reported larger UPPS-P lack of premeditation scores than AMP- (P < 0.001, r = 0.51), and (b) within males, AMP+ showed greater left middle insula signals than AMP- across correct SST trials (P = 0.01, g = 0.78). CONCLUSIONS: Both female and male amphetamine users appear to be characterized by rash action in the presence of positive and negative mood states as well as heightened recruitment of right hemisphere regions during behavioral inhibition. In contrast, planning ahead may be particularly difficult for female amphetamine users, whereas male amphetamine users may need to recruit additional left hemisphere resources during inhibitory processing.

Striatal hypoactivation during monetary loss anticipation in individuals with substance use disorders in a heterogenous urban American Indian sample.

Research suggests that disproportionate exposure to risk factors places American Indian (AI) peoples at higher risk for substance use disorders (SUD). Although SUD is linked to striatal prioritization of drug rewards over other appetitive stimuli, there are gaps in the literature related to the investigation of aversive valuation processing, and inclusion of AI samples. To address these gaps, this study compared striatal anticipatory gain and loss processing between AI-identified with SUD (SUD+; n = 52) and without SUD (SUD-; n = 35) groups from the Tulsa 1000 study who completed a monetary incentive delay (MID) task during functional magnetic resonance imaging. Results indicated that striatal activations in the nucleus accumbens (NAcc), caudate, and putamen were greatest for anticipating gains (ps < 0.001) but showed no group differences. In contrast to gains, the SUD+ exhibited lower NAcc (p = .01, d =0.53) and putamen (p = .04, d =0.40) activation to anticipating large losses than the comparison group. Within SUD+ , lower striatal responses during loss anticipations were associated with slower MID reaction times (NAcc: r = -0.43; putamen: r = -0.35) during loss trials. This is among the first imaging studies to examine underlying neural mechanisms associated with SUD within AIs. Attenuated loss processing provides initial evidence of a potential mechanism wherein blunted prediction of aversive consequences may be a defining feature of SUD that can inform future prevention and intervention targets.

Association between inflammation, reward processing, and ibuprofen-induced increases of miR-23b in astrocyte-enriched extracellular vesicles: A randomized, placebo-controlled, double-blind, exploratory trial in healthy individuals.

Ibuprofen, a non-steroidal, anti-inflammatory drug, modulates inflammation but may also have neuroprotective effects on brain health that are poorly understood. Astrocyte-enriched extracellular vesicles (AEEVs) facilitate cell-to-cell communication and - among other functions - regulate inflammation and metabolism via microribonucleic acids (miRNAs). Dysfunctions in reward-related processing and inflammation have been proposed to be critical pathophysiological pathways in individuals with mood disorders. This investigation examined whether changes in AEEV cargo induced by an anti-inflammatory agent results in inflammatory modulation that is associated with reward-related processing. Data from a double-blind, randomized, repeated-measures study in healthy volunteers were used to examine the effects of AEEV miRNAs on brain activation during reward-related processing. In three separate visits, healthy participants (N = 20) received a single dose of either placebo, 200 mg, or 600 mg of ibuprofen, completed the monetary incentive delay task during functional magnetic resonance imaging, and provided a blood sample for cytokine and AEEV collection. AEEV miRNA content profiling showed that ibuprofen dose-dependently increased AEEV miR-23b-3p expression with greater increase following the 600 mg administration than placebo. Those individuals who received 600 mg and showed the highest miR-23b-3p expression also showed the (a) lowest serum tumor necrosis factor (TNF) and interleukin-17A (IL-17A) concentrations; and had the (b) highest striatal brain activation during reward anticipation. These results support the hypothesis that ibuprofen alters the composition of miRNAs in AEEVs. This opens the possibility that AEEV cargo could be used to modulate brain processes that are important for mental health.

C-Reactive protein and the kynurenic acid to quinolinic acid ratio are independently associated with white matter integrity in major depressive disorder.

Kynurenic acid (KynA) and quinolinic acid (QA) are neuroactive kynurenine pathway (KP) metabolites that have neuroprotective and neurotoxic properties, respectively. At least partly as a result of immune activation, the ratio of KynA to QA in the blood is reduced in major depressive disorder (MDD) and has been reported to be positively correlated with gray matter volume in depression. This study examined whether the inflammatory mediator, C-reactive protein (CRP) and the putative neuroprotective index, KynA/QA, were associated with white matter integrity in MDD, and secondly, whether any such associations were independent of each other or whether the effect of CRP was mediated by KynA/QA. One hundred and sixty-six participants in the Tulsa 1000 study with a DSM-V diagnosis of MDD completed diffusion tensor imaging and provided a serum sample for the quantification of CRP, KynA, and QA. Correlational tractography was performed using DSI Studio to map the specific white matter pathways that correlated with CRP and KynA/QA. CRP was negatively related to KynA/QA (standardized beta coefficient, SBC = -0.35 with standard error, Std.E = 0.13, p < 0.01) after controlling for nine possible confounders, i.e., age, sex, body mass index (BMI), medication status, lifetime alcohol use, severity of depression, severity of anxiety, length of illness, and smoking status. Higher concentrations of CRP were associated with decreased white matter integrity (fractional anisotropy, FA) of the bilateral cingulum and fornix after controlling for the nine potential confounders (SBC = -0.43, Std.E = 0.13, p = 0.002). Greater serum KynA/QA was associated with increased white matter integrity of the bilateral fornix, bilateral superior thalamic radiations, corpus callosum, and bilateral cingulum bundles after controlling for the same possible confounders (SBC = 0.26, Std.E = 0.09, p = 0.005). The relationship between CRP and FA was not mediated by KynA/QA. Exploratory analyses also showed that KynA/QA but not CRP was associated with self-reported positive affect, attentiveness, and fatigue measured with the PANASX (SBCs = 0.17-0.23). Taken together, these results are consistent with the hypothesis that within a subgroup of MDD patients, a higher level of systemic inflammation alters the balance of KP metabolism but also raise the possibility that CRP and neuroactive KP metabolites represent independent molecular mechanisms underlying white matter alterations in MDD.

Individuals with substance use disorders have a distinct oral microbiome pattern.

BACKGROUND: Substance use disorder emerges from a complex interaction between genetic predisposition, life experiences, exposure, and subsequent adaptation of biological systems to the repeated use of drugs. Recently, investigators have proposed that the human microbiota may play a role in brain health and disease. In particular, the human oral microbiome is a distinct and diverse ecological niche with its composition influenced by external factors such as lifestyle, diet, and oral hygiene. This investigation examined whether individuals with substance use disorder (SU) show a different oral microbiome pattern and whether this pattern is sufficient to delineate the SU group from healthy comparison (HC) subjects. METHODS: Participants were a sub-sample (N â€‹= â€‹177) of the Tulsa 1000 (T-1000) project. We analyzed 123 SU and 54 HC subjects using 16S rRNA marker gene sequencing to characterize the oral microbiome. RESULTS: The groups differed significantly based on the UniFrac distance, a phylogenetic-based measure of beta diversity, but did not differ in alpha diversity. Using a machine learning approach, microbiome features combined with socio-demographic variables successfully categorized group membership with 87%-92% accuracy, even after controlling for external factors such as smoking or alcohol consumption. SU individuals with relatively lower diversity also reported higher levels of negative reinforcement experiences associated with their primary substance of abuse. CONCLUSIONS: Oral microbiome features are useful to sufficiently differentiate SU from HC subjects. There is some evidence that subjects whose drug use is driven by negative reinforcement show an impoverished oral microbiome. Taken together, the oral microbiome may help to understand the dysfunctional biological processes that promote substance use or may be pragmatically useful as a risk or severity biological marker.

COVID-19 vaccine willingness and cannabis use histories.

Background: Cannabis use is associated with problematic health-behaviors such as excessive alcohol and tobacco use, and sedentary behavior. Here, we examined the association between cannabis use history and an especially topical health-behavior, willingness to receive a COVID-19 vaccine. Methods: COVID-19 vaccine willingness was surveyed in a subset of participants from the Tulsa 1000 Study, which is a longitudinal study of psychiatric treatment-seeking and healthy control participants. We identified 45 participants who completed a COVID-19 vaccine questionnaire and reported more than 10 lifetime cannabis uses. Those participants were compared to a group of 45 individuals with very light (<10) cannabis use histories who were propensity score-matched on age, sex, income, and race. Two-group t-tests and Bayes factor analysis on vaccine willingness were conducted between groups. Exploratory correlation analyses were conducted on vaccine willingness and lifetime cannabis use levels within the cannabis group only. Results: Vaccine willingness did not differ between the two groups (t88=0.33, p=.74; BF01=4.3). However, a negative correlation was identified within the cannabis group, such that higher lifetime cannabis use histories correlated with less willingness to receive a vaccine (rho43= -.33, p=.03). Conclusions: Although vaccine willingness did not differ between the two matched groups, preliminary evidence suggests that heavy lifetime cannabis use might indicate a reluctance to engage in health-promoting behaviors like receiving a COVID-19 vaccine.

Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom.

Artificial intelligence (AI) is increasingly employed in health care fields such as oncology, radiology, and dermatology. However, the use of AI in mental health care and neurobiological research has been modest. Given the high morbidity and mortality in people with psychiatric disorders, coupled with a worsening shortage of mental health care providers, there is an urgent need for AI to help identify high-risk individuals and provide interventions to prevent and treat mental illnesses. While published research on AI in neuropsychiatry is rather limited, there is a growing number of successful examples of AI's use with electronic health records, brain imaging, sensor-based monitoring systems, and social media platforms to predict, classify, or subgroup mental illnesses as well as problems such as suicidality. This article is the product of a study group held at the American College of Neuropsychopharmacology conference in 2019. It provides an overview of AI approaches in mental health care, seeking to help with clinical diagnosis, prognosis, and treatment, as well as clinical and technological challenges, focusing on multiple illustrative publications. Although AI could help redefine mental illnesses more objectively, identify them at a prodromal stage, personalize treatments, and empower patients in their own care, it must address issues of bias, privacy, transparency, and other ethical concerns. These aspirations reflect human wisdom, which is more strongly associated than intelligence with individual and societal well-being. Thus, the future AI or artificial wisdom could provide technology that enables more compassionate and ethically sound care to diverse groups of people.

Sex differences in circulating inflammatory mediators as a function of substance use disorder.

BACKGROUND: Substance use disorders (SUD) with comorbid depression and anxiety are linked to poor treatment outcome and relapse. Although some depressed individuals exhibit elevated blood-based inflammation (interleukin-6 [IL-6] and C reactive protein [CRP]), few studies have examined whether the presence of SUD exacerbates inflammation. METHODS: Treatment-seeking individuals with major depressive disorder (MDD), anxiety disorders, and/or SUD (N = 160; 80 % with MDD) recruited into the Tulsa 1000 study provided blood samples, participated in clinical interviews, and completed a questionnaire battery querying symptoms of current psychopathology and emotional processing. Analyses followed a multistep process. First, groups were created on the presence versus absence of 1+ lifetime SUD diagnoses: SUD+ (37 F, 43 M) and SUD- (60 F, 20 M). Second, a principal component analysis (PCA) of questionnaire data resulted in two factors, one indexing negative emotionality/withdrawal motivation and one measuring positive emotionality/approach motivation. Third, SUD groups, extracted PCA factors, and nuisance covariates (age, body mass index [BMI], nicotine use, psychotropic medication [and hormone/contraception use in females]) were entered as simultaneous predictors of blood-based inflammation (IL-6, IL-8, IL-10, tumor necrosis factor-α, and CRP). RESULTS: Within females, SUD + exhibited higher IL-8 and IL-10 but lower CRP levels than SUD-. In contrast, SUD was not associated with biomarker levels in males. Across sexes, higher BMI was linked to higher IL-6 and CRP levels, and within the five biomarkers, IL-6 and CRP shared the most variance. CONCLUSION: These findings point to sex-specific inflammatory profiles as a function of SUD that may provide new targets for intervention.

Elevated peripheral inflammation is associated with attenuated striatal reward anticipation in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is the leading cause of years lived with disability worldwide, and up to 40% of individuals with MDD do not respond to current treatments. Studies suggest that peripheral inflammation plays an important role in the striatal mesolimbic dopamine pathway and corticostriatal reward circuitry in MDD. Although MDD patients show blunted striatal responses to reward, the link between degree of inflammation and attenuation of reward processing is unclear. We investigated whether MDD patients with elevated peripheral inflammation exhibit attenuated reward responses to enhance our understanding of MDD pathophysiology and develop more effective treatments for current non-responders. METHODS: MDD subjects varying on serum C-reactive protein (CRP) concentrations (MDD-High CRP, >3 mg/L, n = 44; MDD-Low CRP, <3 mg/L, n = 44) and healthy comparisons (HC, n = 44) completed a monetary incentive delay (MID) task and provided blood samples to measure inflammation-related markers. MDD-High and MDD-Low were propensity score-matched on age, sex, body mass index (BMI), smoking status, exercise and MID task head motion. Percent change in blood oxygen level-dependent (BOLD) signal during anticipation of wins and losses was extracted from bilateral nucleus accumbens, dorsal caudate and dorsolateral putamen regions of interest (ROIs). A linear mixed-effects model was used to test group (MDD-High, MDD-Low and HC), condition (large-win, small-win and no win), and their interaction for these ROIs as well as whole-brain voxelwise data. Analyses also tested group differences in inflammatory mediators. Correlations were used to explore the relationship between inflammatory mediators and brain regions showing differences between MDD-High and MDD-Low. RESULTS: MDD-High exhibited: (a) lower BOLD signal change in dorsal caudate, thalamus, left insula and left precuneus during anticipation of small wins than MDD-Low; and (b) higher serum soluble intercellular adhesion molecule 1 (sICAM-1) and interleukin 6 (IL-6) concentrations than MDD-Low and HC. MDD as a whole, regardless of CRP-based inflammation, exhibited: (a) lower precuneus BOLD signal change to large wins than HC; and (b) higher Interleukin 1 receptor antagonist (IL-1ra), macrophage-derived chemokine (MDC) and macrophage inflammatory protein-1 alpha (MIP-1α) concentrations than HC. Higher serum sICAM-1 concentrations were associated with lower caudate BOLD signal change to small wins only within the MDD-High group. CONCLUSION: Within MDD patients, high inflammation (CRP, sICAM-1) was linked to reduced striatal activation recruited to discriminate intermediate reward magnitudes. These findings support an association between levels of peripheral inflammation and the degree of reward-related activation in individuals with MDD. REGISTRATION OF CLINICAL TRIALS: The ClinicalTrials.gov identifier for the clinical protocol associated with data published in this current paper is NCT02450240, "Latent Structure of Multi-level Assessments and Predictors of Outcomes in Psychiatric Disorders."

Mapping cortical and subcortical asymmetries in substance dependence: Findings from the ENIGMA Addiction Working Group.

Brain asymmetry reflects left-right hemispheric differentiation, which is a quantitative brain phenotype that develops with age and can vary with psychiatric diagnoses. Previous studies have shown that substance dependence is associated with altered brain structure and function. However, it is unknown whether structural brain asymmetries are different in individuals with substance dependence compared with nondependent participants. Here, a mega-analysis was performed using a collection of 22 structural brain MRI datasets from the ENIGMA Addiction Working Group. Structural asymmetries of cortical and subcortical regions were compared between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis (n = 1,796) and nondependent participants (n = 996). Substance-general and substance-specific effects on structural asymmetry were examined using separate models. We found that substance dependence was significantly associated with differences in volume asymmetry of the nucleus accumbens (NAcc; less rightward; Cohen's d = 0.15). This effect was driven by differences from controls in individuals with alcohol dependence (less rightward; Cohen's d = 0.10) and nicotine dependence (less rightward; Cohen's d = 0.11). These findings suggest that disrupted structural asymmetry in the NAcc may be a characteristic of substance dependence.

Machine Learning Analysis of Electronic Nose in a Transdiagnostic Community Sample With a Streamlined Data Collection Approach: No Links Between Volatile Organic Compounds and Psychiatric Symptoms.

Non-intrusive, easy-to-use and pragmatic collection of biological processes is warranted to evaluate potential biomarkers of psychiatric symptoms. Prior work with relatively modest sample sizes suggests that under highly-controlled sampling conditions, volatile organic compounds extracted from the human breath (exhalome), often measured by an electronic nose ("e-nose"), may be related to physical and mental health. The present study utilized a streamlined data collection approach and attempted to replicate and extend prior e-nose links to mental health in a standard research setting within large transdiagnostic community dataset (N = 1207; 746 females; 18-61 years) who completed a screening visit at the Laureate Institute for Brain Research between 07/2016 and 05/2018. Factor analysis was used to obtain latent exhalome variables, and machine learning approaches were employed using these latent variables to predict three types of symptoms independent of each other (depression, anxiety, and substance use disorder) within separate training and a test sets. After adjusting for age, gender, body mass index, and smoking status, the best fitting algorithm produced by the training set accounted for nearly 0% of the test set's variance. In each case the standard error included the zero line, indicating that models were not predictive of clinical symptoms. Although some sample variance was predicted, findings did not generalize to out-of-sample data. Based on these findings, we conclude that the exhalome, as measured by the e-nose within a less-controlled environment than previously reported, is not able to provide clinically useful assessments of current depression, anxiety or substance use severity.

Subcortical surface morphometry in substance dependence: An ENIGMA addiction working group study.

While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics-the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD)-that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures.

Bouncing back: Brain rehabilitation amid opioid and stimulant epidemics.

Recent methamphetamine and opioid use epidemics are a major public health concern. Chronic stimulant and opioid use are characterized by significant psychosocial, physical and mental health costs, repeated relapse, and heightened risk of early death. Neuroimaging research highlights deficits in brain processes and circuitry that are linked to responsivity to drug cues over natural rewards as well as suboptimal goal-directed decision-making. Despite the need for interventions, little is known about (1) how the brain changes with prolonged abstinence or as a function of various treatments; and (2) how symptoms change as a result of neuromodulation. This review focuses on the question: What do we know about changes in brain function during recovery from opioids and stimulants such as methamphetamine and cocaine? We provide a detailed overview and critique of published research employing a wide array of neuroimaging methods - functional and structural magnetic resonance imaging, electroencephalography, event-related potentials, diffusion tensor imaging, and multiple brain stimulation technologies along with neurofeedback - to track or induce changes in drug craving, abstinence, and treatment success in stimulant and opioid users. Despite the surge of methamphetamine and opioid use in recent years, most of the research on neuroimaging techniques for recovery focuses on cocaine use. This review highlights two main findings: (1) interventions can lead to improvements in brain function, particularly in frontal regions implicated in goal-directed behavior and cognitive control, paired with reduced drug urges/craving; and (2) the targeting of striatal mechanisms implicated in drug reward may not be as cost-effective as prefrontal mechanisms, given that deep brain stimulation methods require surgery and months of intervention to produce effects. Overall, more studies are needed to replicate and confirm findings, particularly for individuals with opioid and methamphetamine use disorders.

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects.

OBJECTIVE: Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes. METHOD: Brain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings. RESULTS: Lower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects. CONCLUSIONS: The results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine.

Blunted Frontostriatal Blood Oxygen Level-Dependent Signals Predict Stimulant and Marijuana Use.

BACKGROUND: Occasional recreational stimulant (amphetamine and cocaine) use is an important public health problem among young adults because 16% of those who experiment develop stimulant use disorder. This study aimed to determine whether behavioral and/or neural processing measures can forecast the transition from occasional to problematic stimulant use. METHODS: Occasional stimulant users completed a Risky Gains Task during functional magnetic resonance imaging and were followed up 3 years later. Categorical analyses tested whether blood oxygen level-dependent (BOLD) responses differentiated occasional stimulant users who became problem stimulant users (n = 35) from those who desisted from stimulant use (n = 75) at follow-up. Dimensional analyses (regardless of problem stimulant user or desisted stimulant use status; n = 144) tested whether BOLD responses predicted baseline and follow-up stimulant and marijuana use. RESULTS: Categorical results indicated that relative to those who desisted from stimulant use, problem stimulant users 1) made riskier decisions after winning feedback; 2) exhibited lower frontal, insular, and striatal BOLD responses to win/loss feedback after making risky decisions; and 3) displayed lower thalamic but greater temporo-occipital BOLD responses to risky losses than to risky wins. In comparison, dimensional results indicated that lower BOLD signals to risky choices than to safe choices in frontal, striatal, and additional regions predicted greater marijuana use at follow-up. CONCLUSIONS: Taken together, blunted frontostriatal signals during risky choices may quantify vulnerability to future marijuana consumption, whereas blunted frontostriatal signals to risky outcomes mark risk for future stimulant use disorder. These behavioral and neural processing measures may prove to be useful for identifying ultra-high risk individuals prior to onset of problem drug use.

Differences in decision-making as a function of drug of choice.

Poor decision-making is a central feature of all substance use disorders (SUD), but substances vary in the legal and health consequences associated with their use. For example, while the negative health consequences associated with cigarette smoking are often years away, the consequences of heroin abuse can be fatal in mere hours. It remains unclear if users of these substances show decision-making patterns that differ with the relative riskiness of their drug of choice. To address this question, we reviewed studies that compared decision-making of individuals using different substances. We focused on studies assessing two of the most commonly investigated decision-making processes-delay discounting and risk taking-and specifically focused on decision-making that involved selection between options for hypothetical monetary rewards. For delay discounting, we reviewed studies that assessed decisions regarding delayed or immediate monetary rewards, and for risk-taking we reviewed studies using the Iowa Gambling Task. Studies directly comparing different SUD groups were limited in number and tended to compare alcohol or cocaine users to other substance users. Overall, these studies do not support the hypothesis that decision-making differed by drug of choice. Major limitations in the literature include failing to account for comorbid substance use and a lack of prospective longitudinal studies. Due to these limitations, conclusions should be considered provisional. Nonetheless, current findings suggest that these two facets of decision-making are similar across drugs of abuse.

How the Brain Wants What the Body Needs: The Neural Basis of Positive Alliesthesia.

Discontinuing unhealthy behaviors, such as overeating or drug use, depends upon an individual's ability to overcome the influence of environmental reward cues. The strength of that influence, however, varies greatly depending upon the internal state of the body. Characterizing the relationship between interoceptive signaling and shifting drug cue valuation provides an opportunity for understanding the neural bases of how changing internal states alter reward processing more generally. A total of 17 cigarette smokers rated the pleasantness of cigarette pictures when they were nicotine sated or nicotine abstinent. On both occasions, smokers also underwent functional magnetic resonance imaging (fMRI) scanning while performing a visceral interoceptive attention task and a resting-state functional connectivity scan. Hemodynamic, physiological, and behavioral parameters were compared between sated and abstinent scans. The relationships between changes in these parameters across scan sessions were also examined. Smokers rated cigarette pictures as significantly more pleasant while nicotine abstinent than while nicotine sated. Comparing abstinent with sated scans, smokers also exhibited significantly decreased mid-insula, amygdala, and orbitofrontal activity while attending to interoceptive signals from the body. Change in interoceptive activity within the left mid-insula predicted the increase in smoker's pleasantness ratings of cigarette cues. This increase in pleasantness ratings was also correlated with an increase in resting-state functional connectivity between the mid-insula and the ventral striatum and ventral pallidum. These findings support a model wherein interoceptive processing in the mid-insula of withdrawal signals from the body potentiates the motivational salience of reward cues through the recruitment of hedonic 'hot spots' within the brain's reward circuitry.