Anne Buu

Effects of alcoholism severity and smoking on executive neurocognitive function.

AIMS Neurocognitive deficits in chronic alcoholic men are well documented. Impairments include memory, visual-spatial processing, problem solving and executive function. The cause of impairment could include direct effects of alcohol toxicity, pre-existing cognitive deficits that predispose towards substance abuse, comorbid psychiatric disorders and abuse of substances other than alcohol. Cigarette smoking occurs at higher rates in alcoholism and has been linked to poor cognitive performance, yet the effects of smoking on cognitive function in alcoholism are often ignored. We examined whether chronic alcoholism and chronic smoking have effects on executive function. METHODS Alcoholism and smoking were examined in a community-recruited sample of alcoholic and non-alcoholic men (n = 240) using standard neuropsychological and reaction-time measures of executive function. Alcoholism was measured as the average level of alcoholism diagnoses across the study duration (12 years). Smoking was measured in pack-years. RESULTS Both alcoholism and smoking were correlated negatively with a composite executive function score. For component measures, alcoholism was correlated negatively with a broad range of measures, whereas smoking was correlated negatively with measures that emphasize response speed. In regression analyses, both smoking and alcoholism were significant predictors of executive function composite. However, when IQ is included in the regression analyses, alcoholism severity is no longer significant. CONCLUSIONS Both smoking and alcoholism were related to executive function. However, the effect of alcoholism was not independent of IQ, suggesting a generalized effect, perhaps affecting a wide range of cognitive abilities of which executive function is a component. On the other hand, the effect of smoking on measures relying on response speed were independent of IQ, suggesting a more specific processing speed deficit associated with chronic smoking.

Trajectories of childhood aggression and inattention/hyperactivity: Differential effects on substance abuse in adolescence

OBJECTIVE Aggression and hyperactivity/inattention each are linked to risk of alcohol use disorder (AUD), but their unique contributions remain ambiguous. The present study disaggregated these two domains developmentally and examined the relation between childhood behavior trajectories and adolescent substance use. METHOD A total of 335 children of alcoholic and nonalcoholic fathers were studied prospectively. Parallel process latent trajectory class analysis was developed with behavioral ratings by parents and teachers of aggression and inattention/hyperactivity across ages 7 to 16. Membership in the four latent classes was used as a predictor for problem adolescence alcohol use and substance onset. RESULTS Youths in the four latent trajectory classes differed in number of alcohol problems at age 16: healthy class (39% of sample, mean 2.1 alcohol-related problems), inattentive/hyperactive but not aggressive (33%; mean 2.7 problems), aggressive but not inattentive/hyperactive (4%, mean 5.0 problems), and comorbid (24%; mean 4.0 problems). Survival analysis revealed that the aggressive, comorbid, and inattentive/hyperactive classes had significantly earlier onsets of drinking, drunkenness, and marijuana use than the healthy class. Illicit drug use was also significantly increased in the comorbid, aggressive, and inattentive/hyperactive classes compared to the healthy class. CONCLUSIONS Three levels of behavioral risk of substance abuse exist, the highest having trajectories of increased aggressive and inattentive/hyperactive problems throughout childhood, the next involving only an increased inattentive/hyperactive behavioral trajectory, and the lowest involving those with neither type of problem. Children with both inattention/hyperactivity and aggression have the greatest need for childhood intervention to prevent substance abuse in adolescence.

New variable selection methods for zero-inflated count data with applications to the substance abuse field

Zero-inflated count data are very common in health surveys. This study develops new variable selection methods for the zero-inflated Poisson regression model. Our simulations demonstrate the negative consequences which arise from the ignorance of zero-inflation. Among the competing methods, the one-step SCAD method is recommended because it has the highest specificity, sensitivity, exact fit, and lowest estimation error. The design of the simulations is based on the special features of two large national databases commonly used in the alcoholism and substance abuse field so that our findings can be easily generalized to the real settings. Applications of the methodology are demonstrated by empirical analyses on the data from a well-known alcohol study.

Statistical models for longitudinal zero‐inflated count data with applications to the substance abuse field

This study fills in the current knowledge gaps in statistical analysis of longitudinal zero-inflated count data by providing a comprehensive review and comparison of the hurdle and zero-inflated Poisson models in terms of the conceptual framework, computational advantage, and performance under different real data situations. The design of simulations represents the special features of a well-known longitudinal study of alcoholism so that the results can be generalizable to the substance abuse field. When the hurdle model is more natural under the conceptual framework of the data, the zero-inflated Poisson model tends to produce inaccurate estimates. Model performance improves with larger sample sizes, lower proportions of missing data, and lower correlations between covariates. The simulation also shows that the computational strength of the hurdle model disappears when random effects are included.

Alcohol expectancies in childhood: change with the onset of drinking and ability to predict adolescent drunkenness and binge drinking

AIMS We examined the relationship between alcohol expectancies in childhood and onset of drinking, binge drinking and drunkenness in adolescence and the influence of drinking onset on expectancy development. DESIGN A prospective, longitudinal study of children assessed for alcohol expectancies and drinking at four time-points between ages 6 and 17 years. SETTING Community study of families at high risk for alcoholism conducted in a four-county area in the Midwestern United States. PARTICIPANTS The study involved 614 children; 460 were children of alcoholics and 70% were male. MEASUREMENTS Expectancies about alcohol effects were measured using the Beverage Opinion Questionnaire and childs drinking by the Drinking and Drug History-Youth Form. FINDINGS Partial factor invariance was found for expectancy factors from ages 6 to 17 years. Survival analysis showed that social/relaxation expectancies in childhood predicted time to onset of binge drinking and first time drunk (Wald χ(2) , 1 d.f. = 3.8, P = 0.05 and 5.0, P < 0.05, respectively). The reciprocal effect was also present; when adolescents began drinking, there was an increase in social/relaxation expectancy and a concomitant increase in slope of the expectancy changes lasting throughout adolescence. CONCLUSIONS A reciprocal relationship exists between childhood alcohol expectancies and the development of alcohol involvement. Higher expectancies for positive effects predict earlier onset of problem drinking. Onset of use, in turn, predicts an increase in rate of development of positive expectancies.

Developmental emergence of alcohol use disorder symptoms and their potential as early indicators for progression to alcohol dependence in a high risk sample: A longitudinal study from childhood to early adulthood

This study characterized developmental emergence of individual alcohol use disorder (AUD) symptoms, and evaluated their ability as early indicators of progression into alcohol dependence (AD), conditional upon gender, parental alcohol dependence, early onset of drinking, and level of delinquent behavior at onset. The two parameters of interest were (a) likelihood of specific AUD symptom appearance once drinking has begun, and (b) primacy of symptom appearance as an indicator of likelihood for eventual move into diagnosis. We analyzed prospective data from a community sample of high risk youth from childhood to early adulthood. Symptoms that were at higher probability of being experienced at drinking onset and that could serve as good indicators for the early stage of disease progression were: persistent desire or unsuccessful efforts to control alcohol use (AD4), and continued use despite having persistent or recurrent interpersonal problems (AA4). Tolerance (AD1) may serve as an indicator for the intermediate stage of progression. Young people tended to be at an elevated risk for developing AD6 (activities given up), AD7 (physical/psychological problems), and AA3 (legal problems) in later years so these symptoms may be good indicators for later stages of progression. In addition to being male, an early onset drinker, or high in delinquent behavior, drinkers who experienced AA4 or AD1 as first symptoms were at higher risk for progression to AD. We also identified two high risk clusters: late onset drinkers with AA4 as first symptom, and children of alcoholics with AD1 as first symptom.

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function

BackgroundIn genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data.ResultsOur simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct.ConclusionsThe proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

Efficient Inference of Local Ancestry

MOTIVATION The inference of local ancestry of admixed individuals at every locus provides the basis for admixture mapping. Local ancestry information has been used to identify genetic susceptibility loci. RESULTS In this study, we developed a statistical method, efficient inference of local ancestry (EILA), which uses fused quantile regression and k-means classifier to infer the local ancestry for admixed individuals. We also conducted a simulation study using HapMap data to evaluate the performance of EILA in comparison with two competing methods, HAPMIX and LAMP. In general, the performance declined as the ancestral distance decreased and the time since admixture increased. EILA performed as well as the other two methods in terms of computational efficiency. In the case of closely related ancestral populations, all the three methods performed poorly. Most importantly, when the ancestral distance was large or moderate, EILA had higher accuracy and lower variation in comparison with the other two methods. AVAILABILITY AND IMPLEMENTATION EILA is implemented as an R package, which is freely available from the Comprehensive R Archive Network (http://cran.r-project.org/). CONTACT jyangstat@gmail.com.

Time‐varying effect models for ordinal responses with applications in substance abuse research

Ordinal responses are very common in longitudinal data collected from substance abuse research or other behavioral research. This study develops a new statistical model with free SAS macros that can be applied to characterize time-varying effects on ordinal responses. Our simulation study shows that the ordinal-scale time-varying effects model has very low estimation bias and sometimes offers considerably better performance when fitting data with ordinal responses than a model that treats the response as continuous. Contrary to a common assumption that an ordinal scale with several levels can be treated as continuous, our results indicate that it is not so much the number of levels on the ordinal scale but rather the skewness of the distribution that makes a difference on relative performance of linear versus ordinal models. We use longitudinal data from a well-known study on youth at high risk for substance abuse as a motivating example to demonstrate that the proposed model can characterize the time-varying effect of negative peer influences on alcohol use in a way that is more consistent with the developmental theory and existing literature, in comparison with the linear time-varying effect model.

Longitudinal phenotypes for alcoholism: Heterogeneity of course, early identifiers, and life course correlates.

Alcoholism is a heterogeneous disorder; however, characterization of life-course variations in symptomatology is almost nonexistent, and developmentally early predictors of variations are very poorly characterized. In this study, the course of alcoholic symptomatology over 32 years is differentiated, and predictors and covariates of trajectory class membership are identified. A community sample of alcoholic and neighborhood matched control families, 332 men and 336 women, was recruited based on alcoholism in the men. Symptoms were assessed retrospectively at baseline (mean age = 32) back to age 15 and prospectively from baseline every 3 years for 15 years. Trajectory classes were established using growth mixture modeling. Men and women had very similarly shaped trajectory classes: developmentally limited (men: 29%, women: 42%), developmentally cumulative (men: 26%, women: 38%), young adult onset (men: 31%, women: 21%), and early onset severe (men: 13%). Three factors at age 15 predicted class membership: family history of alcoholism, age 15 symptoms, and level of childhood antisocial behavior. Numerous measures of drinking and other psychopathology were also associated with class membership. The findings suggest that clinical assessments can be crafted where the profile of current and historical information can predict not only severity of prognosis but also future moderation of symptoms and/or remission over intervals as long as decades.