Brain-volume changes in young and middle-aged smokers: a DARTEL-based voxel-based morphometry study

Relationship between stable smoking behavior and cognitive function in male schizophrenia patients

OBJECTIVE

To explore the relationship between stable smoking behavior and cognitive function in male schizophrenia patients.

METHODS

A simple random sampling method is applied to select 120 patients with schizophrenia admitted to a hospital from August 2020 to December 2022 as the subjects. They are divided into two groups based on whether they smoked or not. Their cognitive function is evaluated using the Stroop test (SWCT), continuous task test (CPT), and Chinese version of the Schizophrenic Cognitive Function Battery Test (MCCB). The Spearman correlation analysis is applied to verify the correlation between smoking behavior and SWCT, CPT, and MCCB in patients. Additionally, the Fagerstrom Nicotine Dependence Scale (FTND) is used to evaluate the nicotine dependence degree in smoking group patients. Pearson correlation analysis verifies the correlation between nicotine dependence and SWCT, CPT, MCCB in smoking group patients.

RESULTS

Among 120 patients include in this study, 3 have symptoms during the trial period, and 1 patient has an error in filling out the questionnaire, all of which are excluded. Finally, 116 valid documents are collected, with an effective recovery rate of 96.67%. According to the SWCT test results, the number of single word errors, single word time, double word errors, and double word time in the smoking group exceed the non-smoking group (P < 0.05). According to the CPT test results, the number of correct reactions in the smoking group is below the non-smoking group. The correct average reaction time, error rate of interference items, and error rate of ineffective items exceed the non-smoking group (P < 0.05). According to the MCCB test results, the scores of connectivity, visual spatial memory, and continuous operation test in the smoking group are below the non-smoking group (P < 0.05). The Spearman correlation analysis results show that stable smoking behavior in male schizophrenia patients is positively correlated with the number of single word errors, double word errors, double word time, correct mean reaction time, interference item error rate, and invalid item error rate (r = 0.216-0.524, P < 0.05). It is also positively correlated with the number of correct reactions, immediate memory, language function, delayed memory, MCCB connectivity, visual spatial memory, and continuous operation (r = -0.212-0.356, P < 0.05). The Pearson correlation analysis results show that the nicotine dependence degree in stable male schizophrenia patients is negatively correlated with monochromatic error count, immediate memory, visual span, attention, and MCCB scores (r = -0.321-0.930, P < 0.05).

CONCLUSION

Smoking in male schizophrenic patients may have impacts on their cognitive function. This impact worsens as the patient's nicotine dependence increases, especially on their memory function. Effective measures should be taken in clinical practice to correct patients' smoking behavior, reduce their nicotine dependence, and improve their cognitive function.

Basic lifestyle habits and volume change in total gray matter among community dwelling middle-aged and older Japanese adults

The brain controls human behavior, and the gray matter is the main resource of neuronal cells. We examined the longitudinal relationship between six basic lifestyle habits (diet, exercise, sleep, alcohol consumption, smoking, and social activity including employment) and total gray matter volume in community-dwelling adults in Japan. This two-year follow-up study with data derived from the National Institute for Longevity Sciences, Longitudinal Study of Aging, Aichi, Japan, included adults aged 40-87 years (n = 1665, men: 51%). Lifestyle habits were assessed at baseline (2008-2010) using self-reported questionnaires and three-day dietary records. Total gray matter volume at baseline and after two years was estimated using T1-weighted brain magnetic resonance imaging and FreeSurfer software. The association between each lifestyle factor, the total number of healthy lifestyle habits, and gray matter volume change was determined via a multiple linear regression analysis adjusting for baseline age, total gray matter volume, and other confounders. The mean ± standard deviation decrease in total gray matter volume during the two-year follow-up period was 0.94 ± 1.86% in men and 0.61 ± 2.27% in women. In the multiple regression analysis, volume loss in total gray matter positively correlated with male smoking, while it was negatively correlated with male social activity and employment, female dietary diversity, and the total number of healthy lifestyle habits (standardized beta coefficient; -0.061 in men [p = 0.07], -0.113 in women [p < 0.05]). Therefore, engaging in social activities, non-smoking, a diverse diet, or adopting one healthy lifestyle habit may help prevent gray matter volume loss.

Right arcuate fasciculus and left uncinate fasciculus abnormalities in young smoker

Previous diffusion tensor imaging (DTI) studies had investigated the white matter (WM) integrity abnormalities in smokers. Exposure to nicotine disrupts neurodevelopment during adolescence, possibly by disrupting the trophic effects of acetylcholine. However, little is known about the diffusion parameters of specific fibre bundles at multiple locations in young smokers. Thirty-seven young smokers and 29 age-, education- and gender-matched healthy non-smokers participated in this study. Automated Fibre Quantification (AFQ) was employed to investigate the WM microstructure in young smokers by integrating multiple indices. Diffusion parameters, that is, fractional anisotropy (FA), axial diffusion (AD), radial diffusion (RD) and mean diffusion (MD), were calculated at 100 points along the length of 18 major brain tracts. The relationships between neuroimaging differences and smoking behaviours were explored, including Fagerström Test of Nicotine Dependence (FTND) and pack-years. Compared with non-smokers, young smokers showed significantly increased FA, AD and decreased RD in the left uncinate fasciculus (UF) and right thalamic radiation (TR), increased AD, RD and decreased FA in the right arcuate fasciculus (Arc). Correlation analyses revealed that FA values of the left UF and RD values of the right Arc were negatively correlated with FTND score in smokers and FA values of the right Arc were positively correlated with FTND scores. Positive correlation was observed between AD values of the left UF and pack-years in smokers. The findings enhanced our understanding of the potential effect of adolescent smoking on WM microstructure.

Shared gray matter alterations in subtypes of addiction: a voxel-wise meta-analysis

BACKGROUND

Numerous studies based on voxel-based morphometry (VBM) have revealed gray matter (GM) alterations in multiple brain regions for addiction. However, findings are poorly replicated, and it remains elusive whether distinct diagnoses of addiction are underpinned by shared abnormalities. Our aim was to conduct a quantitative meta-analysis of structural neuroimaging studies investigating GM abnormalities in two main categories of addiction: substance use disorders (SUD) and behavioral addictions (BA).

METHOD

A systematic database search was conducted in several databases from Jan 1, 2010, to Oct 23, 2020, to identify eligible VBM studies. Meta-analysis was performed with the seed-based d mapping software package to compare alternations between individuals with addiction-related disorders and healthy controls (HC).

RESULTS

A total of 59 VBM studies including 2096 individuals with addiction-related disorders and 2637 HC met the inclusion criteria. Individuals with addiction-related disorders showed shared GM volume decrease in bilateral prefrontal cortex, bilateral insula, bilateral rolandic operculum, left superior temporal gyrus, and right Heschl gyrus and GM increase in right lingual gyrus and right fusiform gyrus comparing with HC (p < 0.005). Subgroup analysis found heterogeneity between SUD and BA mainly in left inferior occipital gyrus and right striatum (p < 0.005). Meta-regression revealed that GM atrophy in right anterior cingulate (r = 0.541, p = 0.03 (uncorrected)) and left inferior frontal gyrus (r = 0.595, p = 0.015) were positively correlated with higher impulsivity.

CONCLUSIONS

This meta-analysis identified a concordance across subtypes of addiction in terms of the brain structural changes in prefrontal and insula areas, which may relate to higher impulsivity observed across addiction diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates in addiction.

Multifactorial Etiology of Adolescent Nicotine Addiction: A Review of the Neurobiology of Nicotine Addiction and Its Implications for Smoking Cessation Pharmacotherapy

Nicotine is the primary pharmacologic component of tobacco, and its highly addictive nature is responsible for its widespread use and significant withdrawal effects that result in challenges to smoking cessation therapeutics. Nicotine addiction often begins in adolescence and this is at least partially attributed to the fact that adolescent brain is most susceptible to the neuro-inflammatory effects of nicotine. There is increasing evidence for the involvement of microglial cells, which are the brain's primary homeostatic sensor, in drug dependence and its associated behavioral manifestations particularly in the adolescent brain. A hallmark of neuro-inflammation is microglial activation and activation of microglia by nicotine during adolescent development, which may result in long-term addiction to nicotine. This non-systematic review examines multifactorial etiology of adolescent nicotine addiction, neurobiology of nicotine addiction and the potential mechanisms that underlie the effects of nicotine on inflammatory signaling in the microglia, understanding how nicotine affects the adolescent brain. We speculate, that modulating homeostatic balance in microglia, could have promising therapeutic potential in withdrawal, tolerance, and abstinence-related neural adaptations in nicotine addiction, in the adolescent brain. Further, we discuss nicotine addiction in the context of the sensitization-homeostasis model which provides a theoretical framework for addressing the potential role of microglial homeostasis in neural adaptations underlying nicotine abuse.

Common abnormality of gray matter integrity in substance use disorder and obsessive-compulsive disorder: A comparative voxel-based meta-analysis

The objective of the current study is to determine robust transdiagnostic brain structural markers for compulsivity by capitalizing on the increasing number of case‐control studies examining gray matter volume (GMV) alterations in substance use disorders (SUD) and obsessive‐compulsive disorder (OCD). Voxel‐based meta‐analysis within the individual disorders and conjunction analysis were employed to reveal common GMV alterations between SUDs and OCD. Meta‐analytic coordinates and signed brain volumetric maps determining directed (reduced/increased) GMV alterations between the disorder groups and controls served as the primary outcome. The separate meta‐analysis demonstrated that SUD and OCD patients exhibited widespread GMV reductions in frontocortical regions including prefrontal, cingulate, and insular. Conjunction analysis revealed that the left inferior frontal gyrus (IFG) consistently exhibited decreased GMV across all disorders. Functional characterization suggests that the IFG represents a core hub in the cognitive control network and exhibits bidirectional (Granger) causal interactions with the striatum. Only OCD showed increased GMV in the dorsal striatum with higher changes being associated with more severe OCD symptomatology. Together the findings demonstrate robustly decreased GMV across the disorders in the left IFG, suggesting a transdiagnostic brain structural marker. The functional characterization as a key hub in the cognitive control network and casual interactions with the striatum suggest that deficits in inhibitory control mechanisms may promote compulsivity and loss of control that characterize both disorders.

Metabolic Dynamics in the Prefrontal Cortex during a Working Memory Task in Young Adult Smokers

INTRODUCTION

Cigarette smoking is known to modulate brain metabolism and brain function. How the dynamics of these metabolic alterations influence the active performance of higher order cognitive tasks in smokers, compared to non-smokers, is still unclear. The present exploratory study sought to examine the impact of smoking on the "complete" metabolic profile while the participants performed a working memory (N-back) task.

METHODS

The study sample consisted of 40 young male healthy participants (smokers [n = 20] and non-smokers [n = 20]). Functional magnetic resonance spectroscopy data were acquired using a 3 T whole-body MR system. Data analysis was performed using Java-based Magnetic Resonance User Interface software, and metabolite ratios with respect to creatine (Cr) were calculated.

RESULTS

On a behavioural level, smokers showed worse performance (measured by d') than non-smokers. However, we observed significant differences in the metabolite concentrations in smokers compared to non-smokers, which also changed over the course of the N-back task. A significant effect of the group was observed with smokers showing lower glutamate/Cr (Glx/Cr) and choline/Cr (Cho/Cr) ratios than non-smokers. Further, N-acetyl aspartate (NAA/Cr) and Cho/Cr ratios were significantly different during the rest and the task conditions. In addition, our results demonstrated the metabolite interactions (NAA and Cho, Glx and myo-inositol [mI], and Cho and mI).

CONCLUSION

Further studies are necessary to shed more light on the association between smoking behaviours and metabolic alterations. However, our preliminary findings would assist in this future research to have a complete understanding of the metabolite interactions not only in smoking but also in addiction research.

Meta-analysis of brain gray matter changes in chronic smokers

BACKGROUND

Previous studies based on voxel-based morphometry (VBM) had revealed brain gray matter (GM) changes in chronic smokers relative to nonsmokers. However, not all studies reported entirely consistent findings, or even opposite. The aim of this study was to conduct a quantitative meta-analysis of VBM studies of chronic smokers.

METHOD

A systematic database search was conducted in PubMed and Web of Knowledge from January 1, 2000 to January 31, 2020 to identify eligible VBM studies. Meta-analysis was performed with the Seed-based d Mapping software package to compare alternations between chronic cigarette smokers and nonsmokers. In addition, meta-regression analysis were performed to examine the influences of cigarette per day, smoking history and FTND.

RESULTS

A total of 17 VBM studies including 905 smokers and 1344 nonsmokers met the inclusion criteria. The results of this meta-analysis showed that the chronic smokers showed a robust GM volume decrease in bilateral prefrontal cortex and left insular and a GM increase in the right lingual cortex and left occipital cortex. Moreover, meta-regression analysis showed that cigarette per day, smoking history and FTND were partly associated with GM changes in chronic smokers.

CONCLUSIONS

This meta-analysis indicated that chronic cigarette smokers had significant and robust brain GM alternations compared with nonsmokers. Longitudinal studies should be performed in the future to explore whether these brain regions could be used as potential therapeutic neuro-target for nicotine dependence.

Brain Gray Matter Volume and Functional Connectivity Are Associated With Smoking Cessation Outcomes

Smoking cessation is critical for reducing the risk of respiratory, cardiovascular diseases and cancers. However, most cessation attempts resulted in failure. In the present study, we aim to explore whether alterations of brain gray matter (GM) volume and functional connectivity (FC) are related to cessation outcomes, in hope of providing evidence for improving smoking cessation outcomes. Seventy-three smokers and 41 non-smokers were enrolled in the present study. All smokers participated in a 12-week smoking cessation treatment during which Varenicline was used to aid cessation. At the end of treatment, the smokers were divided into quitters and relapsers based on their abstinence performance. Structural magnetic resonance imaging (MRI) and voxel-based morphometry were applied to quantify the differences of regional brain volumes among the three groups at baseline. In addition, resting-state FC was used to investigate the related functional changes. In comparison with non-smokers, the smokers showed smaller GM volume in the left dorsal medial thalamus. Among the 73 smokers, 29 subjects successfully quitted smoking. The quitters showed greater GM volume than the relapsers in the right postcentral gyrus, right putamen\caudate nucleus and left orbitofrontal cortex (OFC). The GM volume in the left OFC was found to be negatively correlated with the pack years and daily smoking amount in the quitters. Furthermore, we found significantly reduced FC between left thalamus and left cerebellum in the relapsers. These findings extended our knowledge of the neural mechanism of smoking cessation, and suggested that brain structural and functional changes were related to smoking cessation outcomes.

Lifestyle Risk Factors and Findings on Brain Magnetic Resonance Imaging of Older Adult American Indians: The Strong Heart Study

BACKGROUND

Clinical stroke is prevalent in American Indians, but the lifestyle risk factors for vascular brain injury have not been well-studied in this population. The purpose of this study was to correlate brain magnetic resonance imaging (MRI) findings with obesity, alcohol use, and smoking behaviors in elderly American Indians from the Strong Heart Study.

METHODS

Cranial MRI scans (n = 789) were analyzed for dichotomous measures of infarcts, hemorrhages, white matter hyperintensities (WMH), and cerebral atrophy and continuous measures of total brain, WMH, and hippocampal volume. Poisson regression was used to estimate prevalence ratios, and linear regression was used to estimate measures of association for continuous outcomes. Models were adjusted for the risk factors of interest as well as age, sex, study site, income, education, hypertension, diabetes, and low-density lipoprotein cholesterol.

RESULTS

Smoking was associated with increased hippocampal atrophy (p = 0.002) and increased prevalence of sulcal widening (p < 0.001). Relative to nonsmokers, smokers with more than 25 pack-years of smoking had a 27% (95% CI 7-47%) increased prevalence of high-grade sulci, p = 0.005. Body mass index was inversely associated with prevalence of nonlacunar infarcts and sulcal widening (all p = 0.004). Alcohol use was not significantly associated with any of the measured MRI findings.

CONCLUSIONS

This study found similar associations between smoking and vascular brain injury among American Indians, as seen in other populations. In particular, these findings support the role of smoking as a key correlate for cerebral atrophy.

Cigarette smoking and gray matter brain volumes in middle age adults: the CARDIA Brain MRI sub-study

Cigarette smoking has been associated with dementia and dementia-related brain changes, notably gray matter (GM) volume atrophy. These associations are thought to reflect the co-morbidity of smoking and vascular, respiratory, and substance use/psychological conditions. However, the extent and localization of the smoking-GM relationship and the degree to which vascular, respiratory, and substance use/psychological factors influence this relationship remain unclear. In the Coronary Artery Risk Development in Young Adults CARDIA cohort (n = 698; 52% women; 40% black participants; age = 50.3 (SD = 3.5)), we examined the associations of smoking status with total GM volume and GM volume of brain regions linked to neurocognitive and addiction disorders. Linear regression models were used to adjust for vascular, respiratory, and substance use/psychological factors and to examine whether they modify the smoking-GM relationship. Compared to never-smokers, current smokers had smaller total GM volume (-8.86 cm³ (95%CI = -13.44, -4.29). Adjustment for substance use/psychological - but not vascular or respiratory - factors substantially attenuated this association (coefficients = -5.54 (95% CI = -10.32, -0.76); -8.33 (95% CI = -12.94, -3.72); -7.69 (95% CI = -6.95, -4.21), respectively). There was an interaction between smoking and alcohol use such that among alcohol non-users, smoking was not related to GM volumes and among alcohol users, those who currently smoked had -12 cm³ smaller total GM, specifically in the frontal and temporal lobes, amygdala, cingulate, and insula. Results suggest a large-magnitude association between smoking and smaller GM volume at middle age, accounting for vascular, respiratory, and substance use/psychological factors, and that the association was strongest in alcohol users. Regions suggested to be most vulnerable are those where cognition and addiction processes overlap.

The thalamus in drug addiction: from rodents to humans

Impairments in response inhibition and salience attribution (iRISA) have been proposed to underlie the clinical symptoms of drug addiction as mediated by cortico-striatal-thalamo-cortical networks. The bulk of evidence supporting the iRISA model comes from neuroimaging research that has focused on cortical and striatal influences with less emphasis on the role of the thalamus. Here, we highlight the importance of the thalamus in drug addiction, focusing on animal literature findings on thalamic nuclei in the context of drug-seeking, structural and functional changes of the thalamus as measured by imaging studies in human drug addiction, particularly during drug cue and non-drug reward processing, and response inhibition tasks. Findings from the animal literature suggest that the paraventricular nucleus of the thalamus, the lateral habenula and the mediodorsal nucleus may be involved in the reinstatement, extinction and expression of drug-seeking behaviours. In support of the iRISA model, the human addiction imaging literature demonstrates enhanced thalamus activation when reacting to drug cues and reduced thalamus activation during response inhibition. This pattern of response was further associated with the severity of, and relapse in, drug addiction. Future animal studies could widen their field of focus by investigating the specific role(s) of different thalamic nuclei in different phases of the addiction cycle. Similarly, future human imaging studies should aim to specifically delineate the structure and function of different thalamic nuclei, for example, through the application of advanced imaging protocols at higher magnetic fields (7 Tesla).This article is part of a discussion meeting issue 'Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists'.

Discrimination of smoking status by MRI based on deep learning method

Background

This study aimed to assess the feasibility of deep learning-based magnetic resonance imaging (MRI) in the prediction of smoking status.

Methods

The head MRI 3D-T1WI images of 127 subjects (61 smokers and 66 non-smokers) were collected, and 176 image slices obtained for each subject. These subjects were 23-45 years old, and the smokers had at least 5 years of smoking experience. Approximate 25% of the subjects were randomly selected as the test set (15 smokers and 16 non-smokers), and the remaining subjects as the training set. Two deep learning models were developed: deep 3D convolutional neural network (Conv3D) and convolution neural network plus a recurrent neural network (RNN) with long short-term memory architecture (ConvLSTM).

Results

In the prediction of smoking status, Conv3D model achieved an accuracy of 80.6% (25/31), a sensitivity of 80.0% and a specificity of 81.3%, and ConvLSTM model achieved an accuracy of 93.5% (29/31), a sensitivity of 93.33% and a specificity of 93.75%. The accuracy obtained by these methods was significantly higher than that (<70%) obtained with support vector machine (SVM) methods.

Conclusions

The deep learning-based MRI can accurately predict smoking status. Studies with large sample size are needed to improve the accuracy and to predict the level of nicotine dependence.

The relation between gray matter volume and the use of alcohol, tobacco, cocaine and cannabis in male polysubstance users

BACKGROUND

Neuroimaging studies have demonstrated gray matter (GM) volume abnormalities in substance users. While the majority of substance users are polysubstance users, very little is known about the relation between GM volume abnormalities and polysubstance use.

METHODS

In this study we assessed the relation between GM volume, and the use of alcohol, tobacco, cocaine and cannabis as well as the total number of substances used, in a sample of 169 males: 15 non-substance users, 89 moderate drinkers, 27 moderate drinkers who also smoke tobacco, 13 moderate drinkers who also smoke tobacco and use cocaine, 10 heavy drinkers who smoke tobacco and use cocaine and 15 heavy drinkers who smoke tobacco, cannabis and use cocaine.

RESULTS

Regression analyses showed that there was a negative relation between the number of substances used and volume of the dorsal medial prefrontal cortex (mPFC) and the ventral mPFC. Without controlling for the use of other substances, the volume of the dorsal mPFC was negatively associated with the use of alcohol, tobacco, and cocaine. After controlling for the use of other substances, a negative relation was found between tobacco and cocaine and volume of the thalami and ventrolateral PFC, respectively.

CONCLUSION

These findings indicate that mPFC alterations may not be substance-specific, but rather related to the number of substances used, whereas, thalamic and ventrolateral PFC pathology is specifically associated with tobacco and cocaine use, respectively. These findings are important, as the differential alterations in GM volume may underlie different cognitive deficits associated with substance use disorders.

Brain Structure Alterations in Respect to Tobacco Consumption and Nicotine Dependence: A Comparative Voxel-Based Morphometry Study

The main purpose of this study is to examine the lifetime tobacco consumption and the degree of nicotine dependence related gray matter (GM) and white matter (WM) volume alterations in young adult-male smokers. Fifty-three long-term male smokers and 53 well-matched male healthy non-smokers participated in the study, and the smokers were respectively categorized into light and heavy tobacco consumption subgroups by pack-years and into moderate and severe nicotine dependence subgroups using the Fagerström Test for Nicotine Dependence (FTND). Voxel-based morphometry analysis was then performed, and ANCOVA analysis combined with subsequent post hoc test were used to explore the between-group brain volume abnormalities related to the smoking amount and nicotine dependence. Light and heavy smokers displayed smaller GM and WM volumes than non-smokers, while heavy smokers were found with more significant brain atrophy than light smokers in GM areas of precuneus, inferior and middle frontal gyrus, superior temporal gyrus, cerebellum anterior lobe and insula, and in WM areas of cerebellum anterior lobe. However, the contrary trend was observed regarding alterations associated with severity of nicotine dependence. Severe nicotine dependence smokers rather demonstrated less atrophy levels compared to moderate nicotine dependence smokers, especially in GM areas of precuneus, superior and middle temporal gyrus, middle occipital gyrus, posterior cingulate and insula, and in WM areas of precuneus, posterior cingulate, cerebellum anterior lobe and midbrain. The results reveal that the nicotine dependence displays a dissimilar effect on the brain volume in comparison to the cigarette consumption. Our study could provide new evidences to understand the adverse effects of smoking on the brain structure, which is helpful for further treatment of smokers.

Lower total and regional grey matter brain volumes in youth with perinatally-acquired HIV infection: Associations with HIV disease severity, substance use, and cognition

Despite improved survival due to combination antiretroviral therapy (cART), youth with perinatally-acquired HIV (PHIV) show cognitive deficits and developmental delay at increased rates. HIV affects the brain during critical periods of development, and the brain may be a persistent reservoir for HIV due to suboptimal blood brain barrier penetration of cART. We conducted structural magnetic resonance imaging (sMRI) and cognitive testing in 40 PHIV youth (mean age=16.7years) recruited from the NIH Pediatric HIV/AIDS Cohort Study (PHACS) who are part of the first generation of PHIV youth surviving into adulthood. Historical and current HIV disease severity and substance use measures were also collected. Total and regional cortical grey matter brain volumes were compared to a group of 334 typically-developing, HIV-unexposed and uninfected youth (frequency-matched for age and sex) from the Pediatric Imaging, Neurocognition, and Genetics (PING) study (mean age=16.1years). PHIV youth had smaller (2.8-5.1%) total and regional grey matter volumes than HIV-unexposed and uninfected youth, with smallest volumes seen among PHIV youth with higher past peak viral load (VL) and recent unsuppressed VL. In PHIV youth, worse cognitive performance correlated with smaller volumes. This pattern of smaller grey matter volumes suggests that PHIV infection may influence brain development and underlie cognitive dysfunction seen in this population. Among PHIV youth, smaller volumes were also linked to substance use (alcohol use: 9.0-13.4%; marijuana use: 10.1-16.0%). In this study, collection of substance use information was limited to the PHIV cohort; future studies should also collect substance use information in controls to further address interactions between HIV and substance use on brain volume.

Behavioral impulsivity mediates the relationship between decreased frontal gray matter volume and harmful alcohol drinking: A voxel-based morphometry study

Alcohol use disorder (AUD) with harmful drinking patterns is on the one hand characterized by impulsive behavior and is on the other hand known to involve structural brain alterations with lower gray matter volume (GMV), especially in the prefrontal cortex (PFC). So far it is unclear whether frontal brain volumes are associated to harmful alcohol drinking and impulsivity, while controlling simultaneously for a wide array of important confounding factors, which are related to alcohol consumption. We used voxel-based morphometry in 99 adults ranging within a continuum of normal to harmful drinking behavior and alcohol dependence, measured by the 'Alcohol Use Disorders Identification Test', to examine whether the severity of harmful drinking is correlated with structural markers, in particular in the PFC and whether such markers are linked to self-reported impulsivity. We included alcohol and nicotine lifetime exposure, age, education, and BMI as covariates to control that GMV decreases were not related to those factors. Harmful drinking was associated with lower GMV in the right frontal pole, left inferior frontal gyrus, and bilateral inferior parietal lobe. GMV loss in the PFC regions was correlated with increased impulsivity. Follow-up mediation analyses showed that the relationship between GMV in the frontal pole and harmful drinking was mediated by impulsivity. Our findings show that PFC reductions are associated with harmful drinking and impulsivity. Our data suggest that reduced frontal pole GM, independent of a number of alcohol drinking associated covariates, e.g. lifetime alcohol consumption, is related to impaired top-down control of alcohol drinking behavior.