A genetically informed longitudinal study of early-life temperament and childhood aggression.

The present study examined the longitudinal associations between three dimensions of temperament - activity, affect-extraversion, and task orientation - and childhood aggression. Using 131 monozygotic and 173 dizygotic (86 same-sex) twin pairs from the Louisville Twin Study, we elucidated the ages, from 6 to 36 months, at which each temperament dimension began to correlate with aggression at age 7. We employed latent growth modeling to show that developmental increases (i.e., slopes) in activity were positively associated with aggression, whereas increases in affect-extraversion and task orientation were negatively associated with aggression. Genetically informed models revealed that correlations between temperament and aggression were primarily explained by common genetic variance, with nonshared environmental variance accounting for a small proportion of each correlation by 36 months. Genetic variance explained the correlations of the slopes of activity and task orientation with aggression. Nonshared environmental variance accounted for almost half of the correlation between the slopes of affect-extraversion and aggression. Exploratory analyses revealed quantitative sex differences in each temperament-aggression association. By establishing which dimensions of temperament correlate with aggression, as well as when and how they do so, our work informs the development of future child and family interventions for children at highest risk of aggression.

Remember This: Age Moderation of Genetic and Environmental Contributions to Verbal Episodic Memory from Midlife through Late Adulthood.

It is well documented that memory is heritable and that older adults tend to have poorer memory performance than younger adults. However, whether the magnitudes of genetic and environmental contributions to late-life verbal episodic memory ability differ from those at earlier ages remains unresolved. Twins from 12 studies participating in the Interplay of Genes and Environment in Multiple Studies (IGEMS) consortium constituted the analytic sample. Verbal episodic memory was assessed with immediate word list recall (N = 35,204 individuals; 21,792 twin pairs) and prose recall (N = 3,805 individuals; 2,028 twin pairs), with scores harmonized across studies. Average test performance was lower in successively older age groups for both measures. Twin models found significant age moderation for both measures, with total inter-individual variance increasing significantly with age, although it was not possible definitively to attribute the increase specifically to either genetic or environmental sources. Pooled results across all 12 studies were compared to results where we successively dropped each study (leave-one-out) to assure results were not due to an outlier. We conclude the models indicated an overall increase in variance for verbal episodic memory that was driven by a combination of increases in the genetic and nonshared environmental parameters that were not independently statistically significant. In contrast to reported results for other cognitive domains, differences in environmental exposures are comparatively important for verbal episodic memory, especially word list learning.

Tracking and blind deconvolution of blood alcohol concentration from transdermal alcohol biosensor data: A population model-based LQG approach in Hilbert space.

LQG control in Hilbert space, a novel approach for random abstract parabolic systems, and new transdermal alcohol biosensor technology are combined to yield tracking controllers that can be used to automate inpatient management of alcohol withdrawal syndrome and human subject intravenous alcohol infusion studies, and to blindly deconvolve blood or breath alcohol concentration from biosensor measured transdermal alcohol level. The approach taken is based on a full-body alcohol population model in the form of a random, nonlinear, hybrid system of ordinary and partial differential equations and its abstract formulation in a Gelfand triple of Bochner spaces. The efficacy of the approach is demonstrated through simulation studies based on laboratory collected drinking data.

Blood and Breath Alcohol Concentration from Transdermal Alcohol Biosensor Data: Estimation and Uncertainty Quantification via Forward and Inverse Filtering for a Covariate-Dependent, Physics-Informed, Hidden Markov Model.

Transdermal alcohol biosensors that do not require active participation of the subject and yield near continuous measurements have the potential to significantly enhance the data collection abilities of alcohol researchers and clinicians who currently rely exclusively on breathalyzers and drinking diaries. Making these devices accessible and practical requires that transdermal alcohol concentration (TAC) be accurately and consistently transformable into the well-accepted measures of intoxication, blood/breath alcohol concentration (BAC/BrAC). A novel approach to estimating BrAC from TAC based on covariate-dependent physics-informed hidden Markov models with two emissions is developed. The hidden Markov chain serves as a forward full-body alcohol model with BrAC and TAC, the two emissions, assumed to be described by a bivariate normal which depends on the hidden Markovian states and person-level and session-level covariates via built-in regression models. An innovative extension of hidden Markov modeling is developed wherein the hidden Markov model framework is regularized by a first-principles PDE model to yield a hybrid that combines prior knowledge of the physics of transdermal ethanol transport with data-based learning. Training, or inverse filtering, is effected via the Baum-Welch algorithm and 256 sets of BrAC and TAC signals and covariate measurements collected in the laboratory. Forward filtering of TAC to obtain estimated BrAC is achieved via a new physics-informed regularized Viterbi algorithm which determines the most likely path through the hidden Markov chain using TAC alone. The Markovian states are decoded and used to yield estimates of BrAC and to quantify the uncertainty in the estimates. Numerical studies are presented and discussed. Overall good agreement between BrAC data and estimates was observed with a median relative peak error of 22% and a median relative area under the curve error of 25% on the test set. We also demonstrate that the physics-informed Viterbi algorithm eliminates non-physical artifacts in the BrAC estimates.

Alcohol Consumption, Cardiovascular-Related Conditions, and ALDH2*2 Ethnic Group Prevalence in Asian Americans.

BACKGROUND: Little is known about the relationships between alcohol consumption and cardiovascular disease (CVD) and related chronic conditions in Asian Americans and how such risk relationships vary among their subgroups. We examine these relationships in Asian Americans and their moderation by ethnic prevalence of a variant the aldehyde dehydrogenase gene: ALDH2*2. METHODS: Multiple logistic regression modeling was performed using a nationally representative sample of Asian-American adults aged 30 to 70 (n = 1,720) from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Waves 2 (2004 to 2005) and 3 (2012 to 2013). Outcomes considered were diabetes, hypertension, high cholesterol, CVD, any of the 3 conditions (i.e., diabetes, high cholesterol, and CVD) documented to have a J-shaped relationship with drinking (CVDRC3), and any of the CVD-related conditions (ANYCVD). Demographic and socioeconomic characteristics, health insurance coverage, and other lifestyle risk factors (smoking and obesity/overweight) were adjusted. Analyses were stratified by gender. RESULTS: Alcohol consumption level was positively associated only with hypertension in Asian males, with consuming 7 to 14 drinks per week associated with more than double the risk of lifetime abstinence. For females, alcohol consumption had a dose-response relationship with high cholesterol and CVDRC3. Membership in the higher ALDH2*2 ethnic group overall was associated with lower risk of CVD-related conditions. However, compared to abstainers in lower ALDH2*2 group, females in the higher ALDH2*2 group who consumed more than 7 drinks per week had a higher risk of diabetes, hypertension, CVDRC3, and ANYCVD. CONCLUSIONS: Asian Americans may have increased risk of CVD-related conditions at relatively low alcohol consumption levels. Among Asian-American females, in particular, any amount of drinking may increase risk for high cholesterol or any of the CVD-related conditions previously documented to have a curvilinear relationship with drinking. These risks may be particularly elevated for those in ethnic groups with a high prevalence of ALDH2*2.

Estimating the Distribution of Random Parameters in a Diffusion Equation Forward Model for a Transdermal Alcohol Biosensor.

We estimate the distribution of random parameters in a distributed parameter model with unbounded input and output for the transdermal transport of ethanol in humans. The model takes the form of a diffusion equation with the input being the blood alcohol concentration and the output being the transdermal alcohol concentration. Our approach is based on the idea of reformulating the underlying dynamical system in such a way that the random parameters are now treated as additional space variables. When the distribution to be estimated is assumed to be defined in terms of a joint density, estimating the distribution is equivalent to estimating the diffusivity in a multi-dimensional diffusion equation and thus well-established finite dimensional approximation schemes, functional analytic based convergence arguments, optimization techniques, and computational methods may all be employed. We use our technique to estimate a bivariate normal distribution based on data for multiple drinking episodes from a single subject.

Estimation of the Distribution of Random Parameters in Discrete Time Abstract Parabolic Systems with Unbounded Input and Output: Approximation and Convergence.

A finite dimensional abstract approximation and convergence theory is developed for estimation of the distribution of random parameters in infinite dimensional discrete time linear systems with dynamics described by regularly dissipative operators and involving, in general, unbounded input and output operators. By taking expectations, the system is re-cast as an equivalent abstract parabolic system in a Gelfand triple of Bochner spaces wherein the random parameters become new space-like variables. Estimating their distribution is now analogous to estimating a spatially varying coefficient in a standard deterministic parabolic system. The estimation problems are approximated by a sequence of finite dimensional problems. Convergence is established using a state space-varying version of the Trotter-Kato semigroup approximation theorem. Numerical results for a number of examples involving the estimation of exponential families of densities for random parameters in a diffusion equation with boundary input and output are presented and discussed.

Deconvolving the input to random abstract parabolic systems: a population model-based approach to estimating blood/breath alcohol concentration from transdermal alcohol biosensor data.

The distribution of random parameters in, and the input signal to, a distributed parameter model with unbounded input and output operators for the transdermal transport of ethanol are estimated. The model takes the form of a diffusion equation with the input, which is on the boundary of the domain, being the blood or breath alcohol concentration (BAC/BrAC), and the output, also on the boundary, being the transdermal alcohol concentration (TAC). Our approach is based on the reformulation of the underlying dynamical system in such a way that the random parameters are treated as additional spatial variables. When the distribution to be estimated is assumed to be defined in terms of a joint density, estimating the distribution is equivalent to estimating a functional diffusivity in a multi-dimensional diffusion equation. The resulting system is referred to as a population model, and well-established finite dimensional approximation schemes, functional analytic based convergence arguments, optimization techniques, and computational methods can be used to fit it to population data and to analyze the resulting fit. Once the forward population model has been identified or trained based on a sample from the population, the resulting distribution can then be used to deconvolve the BAC/BrAC input signal from the biosensor observed TAC output signal formulated as either a quadratic programming or linear quadratic tracking problem. In addition, our approach allows for the direct computation of corresponding credible bands without simulation. We use our technique to estimate bivariate normal distributions and deconvolve BAC/BrAC from TAC based on data from a population that consists of multiple drinking episodes from a single subject and a population consisting of single drinking episodes from multiple subjects.

Age of Drinking Initiation as a Risk Factor for Alcohol Use Disorder Symptoms is Moderated by ALDH2*2 and Ethnicity.

BACKGROUND: An early age of drinking initiation (ADI) has been associated with increased risk for alcohol use disorders (AUDs), but the consistency of this risk across diverse samples has not been well studied. The purpose of this study was to examine whether the pathway from ADI to AUD symptoms by early adulthood is moderated by ethnicity and possessing an alcohol-metabolizing gene ALDH2*2 variant allele. METHODS: We used multigroup structural equation modeling, including 5 groups split by ethnicity and ALDH2*2, to examine the consistency of the path from ADI to AUD symptoms in 604 Chinese-, Korean-, and White-American college students. We further examined the effects of ALDH2*2, ethnicity, and their interaction in Asians to better understand their unique contributions to the moderation. RESULTS: The association between ADI and AUD symptoms was moderated, with ADI negatively associated with AUD symptoms among Koreans without ALDH2*2 and Whites, but not among Koreans with ALDH2*2 or Chinese regardless of ALDH2*2. Both ALDH2*2 and ethnicity within Asians contributed unique variability in the effect. CONCLUSIONS: Ethnicity and ALDH2*2 altered the relationship of ADI as a risk factor for AUD symptoms. Being Chinese and possessing an ALDH2*2 allele within Koreans both buffered against the risk for AUD symptoms associated with earlier ADI, indicating that this relationship can be attenuated by protective factors.

Review: Prevalence and co-occurrence of addictions in US ethnic/racial groups: Implications for genetic research.

BACKGROUND AND OBJECTIVES: We conducted a review of the prevalence and co-occurrence of 12 types of addictions in US ethnic/racial groups and discuss the implications of the results for genetic research on addictions. METHODS: We utilized MEDLINE and PsycINFO databases to review the literature on alcohol, tobacco, marijuana, illicit drugs, gambling, eating/food, internet, sex, love, exercise, work, and shopping. We present results for each addiction based on total US prevalence, prevalence within ethnic groups, and co-occurrence of addictions among ethnic groups when available. RESULTS: This review indicates very little research has examined the interrelationships of addictive behaviors among US ethnic groups. The studies that exist have focused nearly exclusively on comorbidity of substances and gambling behaviors. Overall findings suggest differences among US ethnic groups in prevalence of addictions and in prevalence of addiction among those who use substances or engage in gambling. Almost no ethnic group comparisons of other addictive behaviors including eating/food, internet, love, sex, exercise, work, and shopping were identified in the literature. CONCLUSIONS: Despite large-scale research efforts to examine alcohol and substance use disorders in the United States, few studies have been published that examine these addictive behaviors among ethnic groups, and even fewer examine co-occurrence and comorbidity with other addictions. SCIENTIFIC SIGNIFICANCE: Even with the limited studies, these findings have implications for genetic research on addictive behaviors. We include a discussion of these implications, including issues of population stratification, disaggregation, admixture, and the interplay between genetic and environmental factors in understanding the etiology and treatment of addictions. (Am J Addict 2017;26:424-436).

Gambling problems and comorbidity with alcohol use disorders in Chinese-, Korean-, and White-American college students.

BACKGROUND AND OBJECTIVES: This study examined gambling behaviors and the relationship between gambling problems and alcohol use disorders (AUDs) among Chinese-, Korean-, and White-American college students. METHODS: Participants were 678 (179 Chinese, 194 Korean, and 305 White; 50% female) 21-26 year-old (M = 22.0 ± 1.36) students attending one university in California. The South Oaks Gambling Screen was administered to assess gambling behavior and the Semi-Structured Assessment for the Genetics of Alcoholism was administered to diagnose lifetime AUDs. Chi-squares and multinomial logistic regressions were conducted to test our hypotheses. RESULTS: Rates of lifetime ever gambling and weekly gambling were similar across the three ethnic groups, but participation in five types of gambling behavior differed. Chinese had the highest rates of gambling problems followed by Koreans and then Whites. Univariate odds ratios determined being Chinese or Korean, being male, and having an AUD were risk factors for gambling problems. When stratified by gender and ethnicity, having an AUD was not related to gambling problems in women, but was strongly associated with gambling problems in Chinese and White men and modestly associated in Korean men. This was true despite low rates of AUDs in Chinese men. DISCUSSION AND CONCLUSIONS: Gambling problems were strongly comorbid with AUDs in Chinese- and White-American men, and moderately comorbid in Korean-American men. No relationship of AUD with gambling problems was found in women. SCIENTIFIC SIGNIFICANCE: The results highlight the importance of assessing disaggregated Asian-American subgroups with respect to addictive behaviors and their comorbidity.

The FKBP5 Gene Affects Alcohol Drinking in Knockout Mice and Is Implicated in Alcohol Drinking in Humans.

FKBP5 encodes FK506-binding protein 5, a glucocorticoid receptor (GR)-binding protein implicated in various psychiatric disorders and alcohol withdrawal severity. The purpose of this study is to characterize alcohol preference and related phenotypes in Fkbp5 knockout (KO) mice and to examine the role of FKBP5 in human alcohol consumption. The following experiments were performed to characterize Fkpb5 KO mice. (1) Fkbp5 KO and wild-type (WT) EtOH consumption was tested using a two-bottle choice paradigm; (2) The EtOH elimination rate was measured after intraperitoneal (IP) injection of 2.0 g/kg EtOH; (3) Blood alcohol concentration (BAC) was measured after 3 h limited access of alcohol; (4) Brain region expression of Fkbp5 was identified using LacZ staining; (5) Baseline corticosterone (CORT) was assessed. Additionally, two SNPs, rs1360780 (C/T) and rs3800373 (T/G), were selected to study the association of FKBP5 with alcohol consumption in humans. Participants were college students (n = 1162) from 21-26 years of age with Chinese, Korean or Caucasian ethnicity. The results, compared to WT mice, for KO mice exhibited an increase in alcohol consumption that was not due to differences in taste sensitivity or alcohol metabolism. Higher BAC was found in KO mice after 3 h of EtOH access. Fkbp5 was highly expressed in brain regions involved in the regulation of the stress response, such as the hippocampus, amygdala, dorsal raphe and locus coeruleus. Both genotypes exhibited similar basal levels of plasma corticosterone (CORT). Finally, single nucleotide polymorphisms (SNPs) in FKBP5 were found to be associated with alcohol drinking in humans. These results suggest that the association between FKBP5 and alcohol consumption is conserved in both mice and humans.

Development of a real-time repeated-measures assessment protocol to capture change over the course of a drinking episode.

AIMS: We report on the development of a real-time assessment protocol that allows researchers to assess change in BrAC, alcohol responses, behaviors, and contexts over the course of a drinking event. METHOD: We designed a web application that uses timed text messages (adjusted based on consumption pattern) containing links to our website to obtain real-time participant reports; camera and location features were also incorporated into the protocol. We used a transdermal alcohol sensor device along with software we designed to convert transdermal data into estimated BrAC. Thirty-two college students completed a laboratory session followed by a 2-week field trial. RESULTS: Results for the web application indicated we were able to create an effective tool for obtaining repeated measures real-time drinking data. Participants were willing to monitor their drinking behavior with the web application, and this did not appear to strongly affect drinking behavior during, or 6 weeks following, the field trial. Results for the transdermal device highlighted the willingness of participants to wear the device despite some discomfort, but technical difficulties resulted in limited valid data. CONCLUSION: The development of this protocol makes it possible to capture detailed assessment of change over the course of naturalistic drinking episodes.

Estimating BrAC from transdermal alcohol concentration data using the BrAC estimator software program.

BACKGROUND: Transdermal alcohol sensor (TAS) devices have the potential to allow researchers and clinicians to unobtrusively collect naturalistic drinking data for weeks at a time, but the transdermal alcohol concentration (TAC) data these devices produce do not consistently correspond with breath alcohol concentration (BrAC) data. We present and test the BrAC Estimator software, a program designed to produce individualized estimates of BrAC from TAC data by fitting mathematical models to a specific person wearing a specific TAS device. METHODS: Two TAS devices were worn simultaneously by 1 participant for 18 days. The trial began with a laboratory alcohol session to calibrate the model and was followed by a field trial with 10 drinking episodes. Model parameter estimates and fit indices were compared across drinking episodes to examine the calibration phase of the software. Software-generated estimates of peak BrAC, time of peak BrAC, and area under the BrAC curve were compared with breath analyzer data to examine the estimation phase of the software. RESULTS: In this single-subject design with breath analyzer peak BrAC scores ranging from 0.013 to 0.057, the software created consistent models for the 2 TAS devices, despite differences in raw TAC data, and was able to compensate for the attenuation of peak BrAC and latency of the time of peak BrAC that are typically observed in TAC data. CONCLUSIONS: This software program represents an important initial step for making it possible for non mathematician researchers and clinicians to obtain estimates of BrAC from TAC data in naturalistic drinking environments. Future research with more participants and greater variation in alcohol consumption levels and patterns, as well as examination of gain scheduling calibration procedures and nonlinear models of diffusion, will help to determine how precise these software models can become.

Framing ethnic variations in alcohol outcomes from biological pathways to neighborhood context.

BACKGROUND: Health disparities research seeks to eliminate disproportionate negative health outcomes experienced in some racial/ethnic minority groups. This brief review presents findings on factors associated with drinking and alcohol-related problems in racial/ethnic groups. METHODS: Those discussed are as follows: (i) biological pathways to alcohol problems, (ii) gene × stress interactions, (iii) neighborhood disadvantage, stress, and access to alcohol, and (iv) drinking cultures and contexts. RESULTS: These factors and their interrelationships are complex, requiring a multilevel perspective. CONCLUSIONS: The use of interdisciplinary teams and an epigenetic focus are suggested to move the research forward. The application of multilevel research to policy, prevention, and intervention programs may help prioritize combinations of the most promising intervention targets.

Blind Deconvolution for Distributed Parameter Systems with Unbounded Input and Output and Determining Blood Alcohol Concentration from Transdermal Biosensor Data.

We develop a blind deconvolution scheme for input-output systems described by distributed parameter systems with boundary input and output. An abstract functional analytic theory based on results for the linear quadratic control of infinite dimensional systems with unbounded input and output operators is presented. The blind deconvolution problem is then reformulated as a series of constrained linear and nonlinear optimization problems involving infinite dimensional dynamical systems. A finite dimensional approximation and convergence theory is developed. The theory is applied to the problem of estimating blood or breath alcohol concentration (respectively, BAC or BrAC) from biosensor-measured transdermal alcohol concentration (TAC) in the field. A distributed parameter model with boundary input and output is proposed for the transdermal transport of ethanol from the blood through the skin to the sensor. The problem of estimating BAC or BrAC from the TAC data is formulated as a blind deconvolution problem. A scheme to identify distinct drinking episodes in TAC data based on a Hodrick Prescott filter is discussed. Numerical results involving actual patient data are presented.

A population model-based linear-quadratic Gaussian compensator for the control of intravenously infused alcohol studies and withdrawal symptom prophylaxis using transdermal sensing.

An output feedback LQG compensator (combined controller and state estimator) for the regulation of intravenous-infused alcohol studies and treatment using a noninvasive transdermal alcohol biosensor is developed. The design is based on a population model involving an abstract semi-linear parabolic hybrid reaction-diffusion system involving coupled partial and ordinary differential equations with random parameters known only up to their distributions. The scheme developed is based on a weak formulation of the model equations in an appropriately constructed Gelfand triple of Bochner spaces wherein the unknown random parameters are treated as additional spatial variables. Implementation relies on a Galerkin-based approximation and convergence theory and an abstract formulation involving linear semigroups of operators. The model is fit and validated using laboratory collected human subject data and the method of moments. The results of numerical simulations of controlled intravenous alcohol infusion are presented and discussed.

Uncertainty Quantification in Estimating Blood Alcohol Concentration From Transdermal Alcohol Level With Physics-Informed Neural Networks.

We develop an approach to estimate a blood alcohol signal from a transdermal alcohol signal using physics-informed neural networks (PINNs). Specifically, we use a generative adversarial network (GAN) with a residual-augmented loss function to estimate the distribution of unknown parameters in a diffusion equation model for transdermal transport of alcohol in the human body. We design another PINN for the deconvolution of the blood alcohol signal from the transdermal alcohol signal. Based on the distribution of the unknown parameters, this network is able to estimate the blood alcohol signal and quantify the uncertainty in the form of conservative error bands. Finally, we show how a posterior latent variable can be used to sharpen these conservative error bands. We apply the techniques to an extensive dataset of drinking episodes and demonstrate the advantages and shortcomings of this approach.

Computation of nonparametric, mixed effects, maximum likelihood, biosensor data based-estimators for the distributions of random parameters in an abstract parabolic model for the transdermal transport of alcohol.

The existence and consistency of a maximum likelihood estimator for the joint probability distribution of random parameters in discrete-time abstract parabolic systems was established by taking a nonparametric approach in the context of a mixed effects statistical model using a Prohorov metric framework on a set of feasible measures. A theoretical convergence result for a finite dimensional approximation scheme for computing the maximum likelihood estimator was also established and the efficacy of the approach was demonstrated by applying the scheme to the transdermal transport of alcohol modeled by a random parabolic partial differential equation (PDE). Numerical studies included show that the maximum likelihood estimator is statistically consistent, demonstrated by the convergence of the estimated distribution to the "true" distribution in an example involving simulated data. The algorithm developed was then applied to two datasets collected using two different transdermal alcohol biosensors. Using the leave-one-out cross-validation (LOOCV) method, we found an estimate for the distribution of the random parameters based on a training set. The input from a test drinking episode was then used to quantify the uncertainty propagated from the random parameters to the output of the model in the form of a 95 error band surrounding the estimated output signal.

Social anxiety and alcohol consumption: The role of social context.

Research has identified social anxiety as a risk factor for the development of alcohol use disorder. However, studies have produced equivocal findings regarding the relationship between social anxiety and drinking behaviors in authentic drinking environments. This study examined how social-contextual features of real-world drinking contexts might influence the relationship between social anxiety and alcohol consumption in everyday settings. At an initial laboratory visit, heavy social drinkers (N = 48) completed the Liebowitz Social Anxiety Scale. Participants were then outfitted with a transdermal alcohol monitor individually-calibrated for each participant via laboratory alcohol-administration. Over the next seven days, participants wore this transdermal alcohol monitor and responded to random survey prompts (6x/day), during which they provided photographs of their surroundings. Participants then reported on their levels of social familiarity with individuals visible in photographs. Multilevel models indicated a significant interaction between social anxiety and social familiarity in predicting drinking, b = -0.004, p =.003 Specifically, among participants higher in social anxiety, drinking increased as social familiarity decreased b = -0.152, p <.001, whereas among those lower in social anxiety, this relationship was non-significant, b = 0.007, p =.867. Considered alongside prior research, findings suggest that the presence of strangers within a given environment may play a role in the drinking behavior of socially anxious individuals.