Neuroimaging of Alcohol Addiction

National Institute On Alcohol Abuse And Alcoholism

Investigators

Linked publications & trials

Abstract

1. Cerebellar recovery of alcohol dependent patients during short term abstinence We are continuing our work that started as a collaboration with Dr. George Fein of Neurobehavioral Research (NRI) in a funded U01 grant to develop and apply a 30-parcel active appearance model of the cerebellum on prospective motion tracking and corrected structural MRIs. The data from this study is still in pipeline for our analyses of structural and functional recovery during short-term abstinence. 2. Omnibus Alcohol Neuroimaging Assessments The purpose of this study is to obtain a standard set of assessments, including brain behavioral, structural, functional, and connectivity (structural and functional) information, on all NIAAA research participants to a) to determine how individual differences in brain structure and evoked responses relate to generalized trait personality and behavior differences (as assessed by psychometric questionnaire instruments and behavioral measures); and b) to determine whether these individual differences relate specifically to genetic polymorphisms in genes governing neurotransmitter activity. We have been analyzing some of this data independently or in collaborative work with other NIAAA investigators in further understanding the pathology of alcohol use disorder (AUD). This in turn might enable us to have identified and established an Addictions Neuroimaging Assessment (ANiA) (Voon et al. 2020). Create a standardized neuroimaging assessment to provide AUD subtyping phenotypes using information from: o Resting state and task driven functional connectivity; o Neurocircuitries associated with AD domains; o Gray and white matter structural integrity of the human brain in various stages of this heterogeneous disease. o Develop a big data system that enables the use of ANA and ANiA assessments and phenotypic data. o Determine the neural correlates (i.e. networks) associated with the domains and neuroclinical measures of AUD. o Utilize innovative approaches such as machine learning to assist in individualized patient treatment, treatment efficacy, and relapse prediction. 1. Structural Data Analysis a. Addiction ENIGMA - Jointly, with our counterparts at the National Institute on Drug Abuse's Neuroimaging Research Branch of Dr. Elliot Stein, we initiated the NIH Addiction Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA). This initiative is part of the Addiction-ENIGMA consortium, a large, multi-site, data-pooling initiative focused on genetics and the brain that has analyzed tens of thousands of study participants at more than 100 labs in over 30 countries. We continued our collaboration with this big data consortium. As a result, two additional manuscripts were published. As part of this collaborations four studies were completed and published. These studies investigated gender related neuroanatomical differences in AUD (Rossetti et al. 2021), relationship between the asymmetry in the brain nucleus accumbens and alcohol or nicotine dependence (Cao et al., 2021), sex differences in the amygdala and hippocampal subregions of 966 with and without AUD (Grace et al. 2020), and a machine learning study predicting alcohol dependence from brain structural measures (Hahn et al., 2020). b. Brain Age In collaboration with Dr. Elliot Stein's Neuroimaging Research Branch (NIDA), we conducted a large scale brain age study to determine the effect of alcohol use on biological brain age. According to this study, there was an association between accelerated brain aging and the estimated lifetime alcohol use based on the previous 90-day alcohol consumption in two large cohorts (submitted for publication to Neurobiology of Aging). 2. Functional Data Analysis a. Emotional Processing - Individuals with AUD can present comorbid anxiety symptoms and often have deficits in emotional processing. Previous research suggests brain response is altered during facial affect recognition tasks, especially in limbic areas, due to either AUD or anxiety symptomology; In this study we wanted to examine the impact of both AUD and clinically significant anxiety symptoms during these tasks invoking emotional (particularly fearful) processing. To do so, we investigated neural activation differences during an emotional face matching task. Participants (N = 232) underwent fMRI scanning. Our results illustrate that individuals with comorbid anxiety symptomology have blunted emotional face processing while those with singular AUD are hyperresponsive. This outcome indicates that AUD with anxiety symptomology may have a unique neurobiological underpinning, and treatment and intervention should be tailored to individual constellations of symptoms (MacIlvane et al., 2021). b. Metabolic Biomarkers of Reward - Metabolic factors, such as triglycerides, glucose, and HbA1c levels, have been shown to be associated with increased risk for heavy alcohol consumption and AUD. The changes in these factors may also play a role in reward seeking behaviors and pathways, which are also implicated in AUD. In collaboration with Dr. Leggio's postdoctoral fellow, Monica Faulkner, we conducted a study to explore the role of peripheral metabolism, alcohol use, and reward processing in individuals that use alcohol. Partial correlations were conducted on peripheral metabolic biomarkers, AUDIT score, and neural activity during reward anticipation and outcome using the monetary incentive delayed (MID). Mediation models revealed that triglycerides and high-density cholesterol have a significant effect on left anterior insula activation during anticipation of potential monetary loss (Faulkner et al., 2021). Treatment - In collaboration with Dr. Leggio's CPN investigators, we continued analyzing the effects of pexacerfront, to evaluate a selective brain penetrant CRH1 antagonist for its ability to modulate emotional and motivational processes in anxious, recently detoxified AUD patients, we conducted an fMRI study of the Trier portion of this study. The analysis for this portion of the study was performed on 20 subjects on placebo and 19 subjects on active compound. In particular, random alternating blocks, consisting of SELF- and OTHER-video perfuming the Trier task were presented. We have completed this analysis and the manuscript is being drafted for presenting the results.