Genomewide association analysis of symptoms of alcohol dependence in the molecular genetics of schizophrenia (MGS2) control sample

Chloride intracellular channels modulate acute ethanol behaviors in Drosophila, Caenorhabditis elegans and mice

Identifying genes that influence behavioral responses to alcohol is critical for understanding the molecular basis of alcoholism and ultimately developing therapeutic interventions for the disease. Using an integrated approach that combined the power of the Drosophila, Caenorhabditis elegans and mouse model systems with bioinformatics analyses, we established a novel, conserved role for chloride intracellular channels (CLICs) in alcohol-related behavior. CLIC proteins might have several biochemical functions including intracellular chloride channel activity, modulation of transforming growth factor (TGF)-β signaling, and regulation of ryanodine receptors and A-kinase anchoring proteins. We initially identified vertebrate Clic4 as a candidate ethanol-responsive gene via bioinformatic analysis of data from published microarray studies of mouse and human ethanol-related genes. We confirmed that Clic4 expression was increased by ethanol treatment in mouse prefrontal cortex and also uncovered a correlation between basal expression of Clic4 in prefrontal cortex and the locomotor activating and sedating properties of ethanol across the BXD mouse genetic reference panel. Furthermore, we found that disruption of the sole Clic Drosophila orthologue significantly blunted sensitivity to alcohol in flies, that mutations in two C. elegans Clic orthologues, exc-4 and exl-1, altered behavioral responses to acute ethanol in worms and that viral-mediated overexpression of Clic4 in mouse brain decreased the sedating properties of ethanol. Together, our studies demonstrate key roles for Clic genes in behavioral responses to acute alcohol in Drosophila, C. elegans and mice.

Recent advances in the genetic epidemiology and molecular genetics of substance use disorders

This article reviews current advances in the genetics of substance use disorders (SUDs). Both genetic and environmental sources of risk are required to develop a complete picture of SUD etiology. Genetic sources of risk for SUDs are not highly substance specific in their effects. Genetic and environmental risks for SUDs typically do not only add together but also interact with each other over development. Risk gene identification for SUDs has been difficult, with one recent success in identifying nicotinic receptor variants that affect risk for nicotine dependence. The impact of genetic variants on SUD risk will individually be small. Although genetic epidemiologic methods are giving us an increasingly accurate map of broad causal pathways to SUDs, gene discovery will be needed to identify the specific biological systems. Identifying these risk genes and understanding their action will require large clinical samples, and interaction between these studies and work in model organisms.

Genes encoding enzymes involved in ethanol metabolism

The effects of beverage alcohol (ethanol) on the body are determined largely by the rate at which it and its main breakdown product, acetaldehyde, are metabolized after consumption. The main metabolic pathway for ethanol involves the enzymes alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH). Seven different ADHs and three different ALDHs that metabolize ethanol have been identified. The genes encoding these enzymes exist in different variants (i.e., alleles), many of which differ by a single DNA building block (i.e., single nucleotide polymorphisms [SNPs]). Some of these SNPs result in enzymes with altered kinetic properties. For example, certain ADH1B and ADH1C variants that are commonly found in East Asian populations lead to more rapid ethanol breakdown and acetaldehyde accumulation in the body. Because acetaldehyde has harmful effects on the body, people carrying these alleles are less likely to drink and have a lower risk of alcohol dependence. Likewise, an ALDH2 variant with reduced activity results in acetaldehyde buildup and also has a protective effect against alcoholism. In addition to affecting drinking behaviors and risk for alcoholism, ADH and ALDH alleles impact the risk for esophageal cancer.

Genome-wide association study identifies 5q21 and 9p24.1 (KDM4C) loci associated with alcohol withdrawal symptoms

Several genome-wide association (GWA) studies of alcohol dependence (AD) and alcohol-related phenotypes have been conducted; however, little is known about genetic variants influencing alcohol withdrawal symptoms (AWS). We conducted the first GWA study of AWS using 461 cases of AD with AWS and 408 controls in Caucasian population in the Collaborative Study on the Genetics of Alcoholism (COGA) sample. Logistic regression analysis of AWS as a binary trait, adjusted for age and sex, was performed using PLINK. We identified 51 SNPs associated with AWS with p < 10(-4). The first best signal was rs770182 (p = 3.65 × 10(-6)) at 5q21 near EFNA5 gene which was replicated in the Australian twin-family study of 273 families (p = 0.0172). Furthermore, three SNPs (rs10975990, rs10758821 and rs1407862) within KDM4C gene at 9p24.1 showed p < 10(-4) (p = 7.15 × 10(-6), 2.79 × 10(-5) and 4.93 × 10(-5), respectively) in the COGA sample while one SNP rs12001158 within KDM4C with p = 1.97 × 10(-4) in the COGA sample was replicated in the family sample (p = 0.01). Haplotype analysis further supported the associations of single-marker analyses of KDM4C in the COGA sample. Moreover, two SNPs (rs2046593 and rs10497668) near FSIP2 at 2q32.1 with moderate associations with AWS in the COGA sample (p = 2.66 × 10(-4) and 9.48 × 10(-5), respectively) were replicated in the family sample (p = 0.0013 and 0.0162, respectively). In addition, several SNPs in GABRA1, GABRG1, and GABRG3 were associated with AWS (p < 10(-2)) in the COGA sample. In conclusion, we identified several loci associated with AWS. These findings offer the potential for new insights into the pathogenesis of AD and AWS.

Stable genetic effects on symptoms of alcohol abuse and dependence from adolescence into early adulthood

Relatively little is known about how genetic influences on alcohol abuse and dependence (AAD) change with age. We examined the change in influence of genetic and environmental factors which explain symptoms of AAD from adolescence into early adulthood. Symptoms of AAD were assessed using the four AAD screening questions of the CAGE inventory. Data were obtained up to six times by self-report questionnaires for 8,398 twins from the Netherlands Twin Register aged between 15 and 32 years. Longitudinal genetic simplex modeling was performed with Mx. Results showed that shared environmental influences were present for age 15-17 (57%) and age 18-20 (18%). Unique environmental influences gained importance over time, contributing 15% of the variance at age 15-17 and 48% at age 30-32. At younger ages, unique environmental influences were largely age-specific, while at later ages, age-specific influences became less important. Genetic influences on AAD symptoms over age could be accounted for by one factor, with the relative influence of this factor differing across ages. Genetic influences increased from 28% at age 15-17 to 58% at age 21-23 and remained high in magnitude thereafter. These results are in line with a developmentally stable hypothesis that predicts that a single set of genetic risk factors acts on symptoms of AAD from adolescence into young adulthood.