Genetic Research

Who Is At Risk for Alcoholism?

Tatiana Foroud, Ph.D.; Howard J. Edenberg, Ph.D.; and John C. Crabbe, Ph.D.

The National Institute on Alcohol Abuse and Alcoholism (NIAAA) was founded 40 years ago to help elucidate the biological underpinnings of alcohol dependence, including the potential contribution of genetic factors. Twin, adoption, and family studies conclusively demonstrated that genetic factors account for 50 to 60 percent of the variance in risk for developing alcoholism. Case–control studies and linkage analyses have helped identify DNA variants that contribute to increased risk, and the NIAAA­sponsored Collaborative Studies on Genetics of Alcoholism (COGA) has the expressed goal of identifying contributing genes using state­of­the­art genetic technologies. These efforts have ascertained several genes that may contribute to an increased risk of alcoholism, including certain variants encoding alcohol­metabolizing enzymes and neurotransmitter receptors. Genome­wide association studies allowing the analysis of millions of genetic markers located throughout the genome will enable discovery of further candidate genes. In addition to these human studies, genetic animal models of alcohol’s effects and alcohol use have greatly advanced our understanding of the genetic basis of alcoholism, resulting in the identification of quantitative trait loci and allowing for targeted manipulation of candidate genes. Novel research approaches—for example, into epigenetic mechanisms of gene regulation—also are under way and undoubtedly will further clarify the genetic basis of alcoholism. KEY WORDS: Alcohol dependence; alcoholism; genetics and heredity; genetic theory of alcohol and other drug (AOD) use; genetic causes of AOD use, abuse and dependence (genetic AOD); genetic risk and protective factors; hereditary versus environmental factors; genetic mapping; Collaborative Studies on Genetics of Alcoholism; human studies; animal studies

vidence from archeological artifacts The National Institute on Alcohol TATIANA FOROUD, PH.D., is a indicates that fermented beverages Abuse and Alcoholism (NIAAA) Chancellor’s Professor in the Department was founded 40 years ago to further Eexisted as early as 10,000 B.C. of Medical and Molecular Genetics, The excessive consumption of alcohol, understanding of the biological underpinnings of alcohol dependence. Indiana University School of Medicine, however, results in dangers to the Indianapolis, Indiana. health and well being of the drinker Early genetic studies were focused and those around him or her. Today, on delineating whether environmental factors, genetic factors, or both con­ HOWARD J. EDENBERG, PH.D., is a the World Health Organization estimates Distinguished Professor in the Department that alcohol causes 1.8 million deaths tributed to the risk for alcohol depen­ dence. Once it was apparent that of Biochemistry and Molecular Biology (3.2 percent of all deaths) worldwide genetics did indeed play a role in alcohol and the Department of Medical and and 58.3 million (4 percent of total) Molecular Genetics, both at the Indiana 1 dependence, NIAAA began to fund disability­adjusted life­years (DALYs) studies seeking to identify relevant University School of Medicine, lost to disease (http://www.who.int/ Indianapolis, Indiana. substance_ abuse/facts/alcohol/en/ genes. Since then, studies in humans and animals have used complementary index.html). In the United States, alco­ JOHN C. CRABBE, PH.D., is a professor approaches to understand the genetics hol dependence (i.e., alcoholism) is a in the Department of Behavioral of alcohol use and dependence. This major health problem, affecting 4 to 5 Neuroscience, Oregon Health & Science percent of the population at any given overview summarizes the evidence University, and a senior research career time, with a lifetime prevalence of 12.5 1DALYs are a measure of burden of disease. One DALY is equal scientist at the VA Medical Center, percent (Hasin et al. 2007). to 1 healthy year of life lost. Portland, Oregon.

64 Alcohol Research & Health Genetic Research and Risk for Alcoholism supporting a role for genetic factors Strategies for Identifying possible to scan the genome using in alcoholism and describes how new Genes Contributing to a type of genetic variation called genetic findings could affect our Alcohol Dependence microsatellites. In this approach, understanding of the causes and factors called linkage analysis, the pattern contributing to this debilitating disease Researchers have developed several of transmission of a disease (e.g., and could potentially guide the devel­ strategies to identify genes that contribute alcoholism) in families with multiple opment of improved treatments. to differences in the risk for alcohol affected members is compared with dependence, including case–control the pattern of transmission of certain studies and linkage analyses. These microsatellites (see figure 1B). The strategies depend on the premise that Evidence of a Genetic underlying hypothesis is that alcoholics for a particular position in the DNA within a family share many risk alleles; Contribution to Alcohol of these genes, more than one possible Dependence therefore, genes containing alleles form exists. Each of these forms is that increase the risk for alcoholism termed an allele. The study methods Several study designs, including twin, reside within chromosomal regions that used to identify genes that affect the are inherited by most or all alcoholic family, and adoption studies, are used risk for alcohol dependence assume that to determine whether relatively common family members. Unfortunately, how­ the presence of certain alleles increases ever, the chromosomal regions that diseases, such as alcohol dependence, the risk of alcoholism. These variants are caused at least in part by genetic were identified using this approach often that affect risk can be located either factors and to estimate the magnitude contained hundreds or even thousands directly within a gene or near a gene. of genes, making it very challenging of the overall genetic contribution. Case–control studies compare allele to determine which specific gene(s) Twin studies compare the similarity in frequencies in a sample of alcoholic contribute to the risk for alcoholism. disease status (i.e., concordance2) and control subjects. Because DNA between identical (i.e., monozygotic) is inherited from both parents, every The Collaborative Studies on and fraternal (i.e., dizygotic) twins. If person carries two copies of the DNA Genetics of Alcoholism Study risk for a disease (e.g., alcohol depen­ at a given position in the genome— dence) is determined at least in part one allele that was inherited from the Another major advancement in the by genetic factors, monozygotic twins, father and one allele that was inherited search for genes contributing to the who have identical genetic material from the mother. The genotype risk for alcoholism was the initiation (i.e., genomes), would be expected to describes the variation at a particular in 1989 of the NIAAA­funded have a higher concordance rate for position within the genome and is Collaborative Studies on Genetics of alcohol dependence than dizygotic defined by the allele inherited from Alcoholism (COGA), a family study twins, who on average share only half the father and the allele inherited from with the expressed goal of identifying their genome. Studies by several groups the mother. If a given allele contributed contributing genes using newly available have indeed shown higher concordance to the risk for alcohol dependence, genetic technologies (Begleiter et al. 1995; rates for alcohol dependence among one would expect the allele and/or Bierut et al. 2002; Edenberg 2002). The study was groundbreaking in several monozygotic than among dizygotic genotype frequencies to differ between ways, including its size, emphasis on the case and the control subjects (see twins (Agrawal and Lynskey 2008). families, and extensive characterization figure 1A). Family studies, which evaluate the of subjects. In the process, COGA members of a family (both alcoholic Initially, case–control studies often researchers developed a novel assess­ and nonalcoholic members) for the were performed using small numbers of alcoholic and control subjects and ment instrument, the Semi­Structured presence of the disease, also have pro­ examined the role of a single gene, Assessment of the Genetics of Alcoholism vided convincing evidence that the risk frequently testing only for a single (SSAGA), which since has been trans­ for alcohol dependence is determined variation. This approach has limited lated into nine languages and is used partly by genetic influences (Gelernter power, and many results could not be by over 237 investigators worldwide in and Kranzler 2009). Overall, family, studies of alcohol use and dependence. 3 replicated. The most robust result from adoption, and twin studies provide these early studies was the demon­ Families were obtained by recruit­ convergent evidence that hereditary stration that the genes encoding two ing alcohol­dependent probands (i.e., factors play a role in alcohol dependence, alcohol­metabolizing enzymes— index cases) who were in treatment with variations in genes estimated to alcohol dehydrogenase (ADH) and and who gave permission to contact account for 50 to 60 percent of the aldehyde dehydrogenase (ALDH)— total variance in risk. These estimates 2 For a definition of this and other technical terms, see the glossary, played an important role in determining pp. 161–164. suggest that although genetic factors alcoholism risk (this will be discussed in are important, nongenetic factors also more detail in the next section). 3 Adoption studies compare the disease status of adoptees with that of their birth parents (with each of whom they share on average half contribute significantly to the risk for With the advances of molecular their genome) and of their adoptive parents (with whom they typically alcohol dependence. genetics technologies, it then became have no genetic relationship and do not share their genome).

Vol. 33, Nos. 1 and 2, 2010 65 their family members. This approach several different chromosomal regions et al. 2005), a family study of both generated a dataset of 1,857 families as possibly containing one or more alcohol dependence and alcohol­related consisting of 16,062 individuals as of genes contributing to alcohol depen­ endophenotypes (including electro­ March 2010. Moreover, the researchers dence; to related clinical characteristics physiological measures, similar to identified a genetically informative (i.e., phenotypes) such as smoking, COGA) (Hill 1998), and a study of subset comprising 262 families with depression, suicidal behavior, conduct Mission Indian families (Ehlers et al. at least three first­degree relatives who disorder, and the largest number of 2004). Twin studies also have remained met lifetime criteria for both Diagnostic drinks within a 24­hour period; and a focus of several NIAAA­funded and Statistical Manual of Mental to neurobiological endophenotypes research projects (Jacob et al. 2001; Disorders, Third Edition, Revised such as event­related potentials and Madden et al. 2000). Moreover, a (DSM–III–R) (American Psychiatric brain oscillations in electrophysiological study of offspring of alcoholic fathers Association 1987) alcohol dependence activity (Edenberg 2002; Edenberg has expanded into a longitudinal, and Feighner definite alcoholism;4 and Foroud 2006). Despite much multigenerational genetic study that this subset became the focus of genetic progress, however, identification of is focused on better understanding analyses. The extensive characteriza­ the specific genes contributing to the factors contributing to the initiation tion of subjects also allowed analysis these phenotypes remains a challenging of alcohol use as well as the long­term of the role of hereditary characteris­ task because they lie within broad risk for alcohol dependence (Schuckit tics (i.e., endophenotypes) that often linkage regions that often encom­ 1991). Finally, studies also have are associated with alcoholism but are passed 10 to 30 million base pairs. examined African­American alcohol­ not direct symptoms of alcoholism, In addition to COGA, NIAAA has dependent families ascertained on the such as certain electrophysiological supported several other large family basis of cocaine or opioid dependence traits, drug dependence, other related studies designed to identify genes (Gelernter and Kranzler 2009). psychiatric conditions, and personality contributing to the risk for alcohol measures (Edenberg 2002). dependence. These include a large 4 These criteria, which were the accepted diagnostic criteria at the time of COGA’s initiation, were based on the definitions estab­ Genetic analyses in this subsample study in Ireland that is recruiting lished in the DSM–III–R (American Psychiatric Association 1987) of the COGA dataset have implicated siblings (Kendler et al. 1996; Prescott and by Feighner and colleagues (1972).

A B

• Recruit the entire family, including both • Recruit a group of unrelated cases and unrelated controls affected and unaffected individuals • Compare the frequency of SNP alleles in the two groups to detect • Use markers to identify chromosomal allelic or genotypic association regions inherited by affected and not • Associated regions typically are small (thousands of base pairs) inherited by unaffected family members • Linked regions typically are large (tens of millions of base pairs)

Figure 1 Approaches to identifying genes contributing to the risk of alcoholism. A) Case–control association study design. Each circle represents a person who is either an alcoholic (case subject) or not an alcoholic (control subject). The study assesses the role of a single­nucleotide polymorphism (SNP)* that exists in two different variants (i.e., alleles)—allele 1 and allele 2. Because each person inherits two copies of the SNP from their parents, the numbers in the circles represent the three possible genotypes (11, 12, and 22). Many more case than control subjects carry at least one copy of allele 1 (i.e., have the 11 and 12 genotypes), suggesting that people with allele 1 may be more likely to develop alcoholism. B) Linkage study design. A three­generation family tree (pedigree) is shown. Squares represent male subjects and circles represent female subjects. Shaded symbols represent alcoholic individuals and unshaded symbols represent nonalcoholic indi­ viduals. In this pedigree, there are alcoholic individuals in each generation, and both men and women are affected.

NOTE: *An SNP is a DNA sequence variation occurring when a single nucleotide in a DNA marker (or other genetic sequence) differs between members of a species or between the chromosome pairs in an individual.

66 Alcohol Research & Health Genetic Research and Risk for Alcoholism

Together, these approaches, although at position 487 of the ALDH protein ADH1B*3 variant is common in by no means completed, already have for the amino acid lysine. This muta­ people from Africa (Edenberg 2007; resulted in the identification of some tion acts in a nearly dominant manner Eng et al. 2007; Li et al. 2007, genes that impact the risk for alcohol to render the enzyme almost inactive: 2009). All of these variations have dependence. Some of these genes and even people who inherit only one copy strikingly strong effects on risk; thus, the proteins they encode are dis­ of ALDH2*2 and one “normal” copy in Asian populations, ALDH2*2 and cussed in the next section. of the gene (i.e., people who are het­ ADH1B*2 each can lower risk by erozygous for this mutation) produce two­ to sevenfold. No other known an ALDH enzyme with extremely low gene variations have such a strong Genes Contributing to enzyme activity (Crabb et al. 1989). As effect on risk for alcoholism. Alcohol Dependence a result, these individuals exhibit highly The influence of ADH variations elevated levels of acetaldehyde, which on risk was further investigated through produces aversive reactions, including linkage studies performed in non­ Genes Encoding Alcohol­ flushing, elevated heart rate (i.e., tachy­ Asian families. These analyses detected Metabolizing Enzymes cardia), and nausea after consuming linkage of alcoholism to a broad region Classic studies, which have been repli­ even a small amount of alcohol (Eng on chromosome 4q that included the cated in many populations, have et al. 2007). Similarly, coding varia­ ADH gene cluster (Long et al. 1998; demonstrated that certain coding varia­ tions in the ADH1B gene (called Prescott et al. 2006; Reich 1996; tions in two genes affecting alcohol ADH1B*2 and ADH1B*3) that encode Reich et al. 1998; Williams et al. 1999). metabolism have a strong protective highly active enzymes which increase Given the strong prior evidence for effect—that is, they both substantially the rate at which acetaldehyde is pro­ the role of the ADH genes in alco­ lower the risk for alcoholism. These duced also are strongly protective and holism susceptibility, the COGA variants affect a gene called ADH1B, reduce the risk for alcohol dependence investigators initially focused on the which encodes a variant of ADH, and (Edenberg 2007; Thomasson et al. 1991). 262 families from the study with a a gene called ALDH2, which encodes These gene variations have been very strong history of alcoholism. In a variant of ALDH (Edenberg 2000, selected for in different populations. these families, they determined the 2007; Hurley et al. 2002) (figure 2). For example, the ALDH2*2 variant genotype for 110 DNA markers The protective variant in the ALDH2 is common only among people from known as single­nucleotide polymor­ gene, known as ALDH2*2, involves a east Asia, the ADH1B*2 variant is phisms (SNPs), which were distribut­ point mutation that results in the common among people from east ed throughout the ADH gene cluster. exchange of the amino acid glutamate Asia and the Middle East, and the These analyses detected significant evidence of association of alcoholism with 12 SNPs located in and around the ADH4 gene (Edenberg et al. 2006) and modest evidence of associ­ ation with noncoding SNPs5 in ADH1A and ADH1B. Moreover, the Higher intrinsic rate More enzyme aversion analyses provided evidence that the Very low activity ADH1B*3 allele was protective among African­American families (Edenberg Alcohol Acetaldehyde Acetate et al. 2006). The association of sever­ al noncoding ADH polymorphisms ADH ALDH with alcohol dependence has been replicated in other studies (Edenberg 2007; Macgregor et al. 2009). Figure 2 The main steps of alcohol metabolism. Alcohol first is metabolized to acetaldehyde by the enzyme alcohol dehydrogenase (ADH), which is encoded by several genes, each of which may exist in several variants (i.e., alleles). Certain alleles encode Genes Encoding γ­Aminobutyric ADH molecules that result in the metabolism of alcohol (denoted by the red arrow Acid Receptors above ADH). As a result, buildup of acetaldehyde occurs (denoted by the upward­ pointing arrow), leading to such aversive effects as nausea, flushing, and acceler­ The brain­signaling molecule (i.e., ated heart beat (i.e., tachycardia). The acetaldehyde then is metabolized to acetate neurotransmitter) γ­aminobutyric acid by the enzyme aldehyde dehydrogenase (ALDH), which also is encoded by several (GABA), by interacting with a molecule genes existing in different alleles. Certain alleles in the ALDH2 gene, which encodes called the GABA­A receptor, mediates a key ALDH enzyme, can result in very low activity of the enzyme (denoted by the several effects of alcohol, including black arrow with a red line through it), again causing acetaldehyde accumulation and alcohol’s sedative and anxiety­reducing the resulting aversive effects. 5 Noncoding SNPs are DNA sequence variations that are located in regions of the ADH gene that do not encode the actual ADH protein.

Vol. 33, Nos. 1 and 2, 2010 67 (i.e., anxiolytic) effects, motor incoor­ risk factor for alcohol dependence. The study identified several SNPs in a region dination, tolerance, and dependence receptor encoded by this gene is a G­ on chromosome 2 that previously had (Kumar et al. 2009). Several genes that protein–coupled receptor6 involved in been linked to alcohol dependence, as encode subunits of the GABA­A recep­ many functions. In the COGA study, well as SNPs in a gene called CDH13 tor are associated with an increased risk SNPs in CHRM2 were associated with that is located on chromosome 16 for alcoholism. For example, significant alcohol dependence, a finding that was and the ADH gene ADH1C on chro­ evidence suggests that a gene called replicated in an independent study mosome 4. GABRA2, which with other GABA­A (Edenberg and Foroud 2006). Recently, COGA reported results receptor genes is located in a cluster Extensive research also has examined of a GWAS that included 847 alcohol­ on chromosome 4, is associated with the neuronal nicotinic acetylcholine dependent case and 552 control sub­ alcoholism (Edenberg et al. 2004). receptors (nAChRs), which are affected jects (Edenberg et al. 2010). The This finding has been replicated in by both nicotine and alcohol. DNA combined evidence from this case– many (but not all) case–control studies variation in the genes that encode the control study, a follow­up in families, in Europeans, Australians, and Plains subunits of these receptors may play and gene expression data provided Indians (Edenberg and Foroud 2006; a role in the susceptibility to alcohol strongest support for the association Gelernter and Kranzler 2009). In several dependence and nicotine addiction. with alcohol dependence of a cluster samples, the association with GABRA2 Similar to the GABA­A receptors, of genes on chromosome 11.7 How­ was greatest among those alcohol­ the genes encoding these receptors ever, the associations detected in the dependent people who also were depen­ are found in clusters on several chro­ COGA GWAS did not reach the dent on nicotine (Philibert et al. 2009) mosomes. Studies have reported an threshold for statistical significance or illicit drugs (Agrawal et al. 2006; association of SNPs in CHRNA5– for this type of analysis, and therefore Philibert et al. 2009); the latter subgroup CHRNA3 (Wang et al. 2009) and additional studies must be conducted is characterized by greater severity of CHRNA6–CHRNB3 (Hoft et al. to further define the associated genes. alcohol problems in general (Dick et 2009) gene clusters with alcohol Several SNPs nominated as candidates al. 2007). In addition, another gene dependence or alcohol consumption. in the earlier German GWAS also within the chromosome 4 GABA­A were replicated in the COGA sample, cluster, GABRG1, also may influence Genome­wide Association Studies including SNPs in or near the genes the risk for alcoholism (Covault et al. In the past few years, it has become CPE, DNASE2B, SLC10A2, ARL6IP5, 2008; Enoch et al. 2009). possible to genotype up to a million ID4, GATA4, SYNE1, and ADCY3. Finally, GABA­A genes on other SNPs throughout the genome in a single Another recent report (Bierut et al. chromosomes, including GABRG3 experiment—an approach called genome­ 2010) described a GWAS using an on chromosome 15 (Dick et al. wide association studies (GWASs). overlapping set of COGA subjects as 2004) and GABRA1 on chromosome This technique, which is based on the well as additional subjects recruited 5 (Dick et al. 2006), also have been assumption that common genetic vari­ as part of other addiction research associated with alcoholism. However, ation contributes to disease risk, allows projects. This sample included both these associations have not yet been a comprehensive test of association African­American and European­ replicated in other samples and there­ across the genome, rather than testing American subjects, and the primary fore must be considered tentative. only one gene at a time. It has been analysis sought to identify association used for many different diseases, with with alcohol dependence using a Genes Encoding Acetylcholine varying success. In particular, the rela­ case–control design. Although none Receptors tively low statistical power of GWASs is of the detected associations met Another neurotransmitter system a significant hurdle. Thus, the analyses genome­wide criteria for statistical involved in the actions of alcohol is require very large samples because most significance, there was some evidence acetylcholine, which can interact with variations only have small effects; to support the previously reported different types of receptors, including moreover, the multiple testing involved association in GABRA2 as well as in muscarinic and nicotinic receptors. As in a GWAS reduces the statistical a gene called ERAP1, which encodes with the GABA­A receptor, the subunits power to detect associations. the enzyme endoplasmic reticulum for each of these receptors are encoded Several studies recently have report­ aminopeptidase 1 (Bierut et al. by different genes that have several dif­ ed GWAS results from case–control 6 G­protein–coupled receptors interact with a signaling molecule ferent alleles (i.e. code for different forms studies comparing alcohol­dependent (e.g., acetylcholine) outside the cell, resulting in the activation of of the receptor subunit), and certain case subjects to nondependent control signaling pathways within the cell and thereby inducing a cellular response. Specifically, binding of the receptor to the signaling alleles have been associated with an subjects. The first published study, molecule alters the structure of the receptor so that it can activate increased risk for alcoholism. For example, conducted in Germany, compared an associated G­protein, which in turn can act on other proteins the gene that encodes the muscarinic 487 men in inpatient treatment for in the cell. acetylcholine receptor subtype 2, called alcohol dependence to 1,358 control 7 The genes located in this cluster are SLC22A18, PHLDA2, CHRM2, appears to be an important subjects (Treutlein et al. 2009). The NAP1L4, snora54, CARS, and OSBPL5.

68 Alcohol Research & Health Genetic Research and Risk for Alcoholism

2010). Finally, a GWAS in a sample biological effects and to individual dif­ mals within a strain are genetically of twins and their families recruited in ferences in risk for alcohol dependence. identical. This reduction in the genetic Australia is currently being analyzed. The main advantage of animal models variation among the animals studied for these genetic analyses is that they could increase the power to identify allow researchers to more tightly control genes contributing to alcohol­related Genetic Animal Models environmental influences, thereby making traits. of Alcohol’s Effects and it easier to identify genetic risk factors. Another commonly used type of Alcohol Use In 1959, inbred mouse strains first animal model involves selectively were shown to differ in their tendency bred lines. Starting in the late 1940s, Since the earliest days of alcohol research, to drink alcohol (McClearn and Rodgers researchers in Chile bred rats that the use of animal models has featured 1959), and studies with inbred strains preferred to drink alcohol­containing strongly in attempts to understand continue to this day. Each inbred solutions as well as rats that avoided genetic contributions to the mecha­ strain possesses a random collection of alcohol (Mardones and Segovia­ nisms through which alcohol exerts its genes (i.e., genotype), but all the ani­ Riquelme 1983). Such selective

Table Selectively Bred Rat and Mouse Lines With Differential Responses to Alcohol*

Lines Abbreviation Selected Trait

Rats University of Chile Alcohol Drinker UChB/UChA High/low drinking, 10 percent ethanol vs. water and nondrinker

ALKO Alcohol and Nonalcohol AA/ANA High/low drinking, 10 percent ethanol vs. water

Alcohol Preferring and Nonpreferring P/NP High/low drinking, 10 percent ethanol vs. water

Sardinian Alcohol Preferring and sP/sNP High/low drinking,10 percent ethanol vs. water Nonpreferring

Marchigian Sardinian Alcohol Preferring msP High drinking, 10 percent ethanol vs. water (derived from 13th generation sP rats)

High/Low Alcohol Drinking HAD­1/LAD­1 High/low drinking,10 percent ethanol vs. water HAD­2/LAD­2

High/Low Addiction Research HARF/LARF High/low drinking, 12 percent ethanol during a 20­minute Foundation period of limited access

High Alcohol Sensitive and HAS­1/LAS­1 Long/short duration of loss­of­righting reflex after high­dose Low Alcohol Sensitive HAS­2/LAS­2 ethanol injection

Mice High/Low Alcohol Preference HAP­1/LAP­1 High/low drinking,10 percent ethanol vs. water HAP­2/LAP­2 HAP­3/LAP­3

High Drinking in the Dark HDID­1 High blood alcohol levels after drinking 20 percent ethanol HDID­2 in a single­bottle, limited access exposure

Long Sleep and Short Sleep LS/SS Long/short duration of loss­of­righting reflex after high­dose ethanol injection

FAST and SLOW FAST­1/SLOW­1 Sensitivity/resistance to low­dose ethanol stimulation FAST­2/SLOW­2 of activity

Withdrawal Seizure Prone and WSP­1/WSR­1 Severe/mild handling­induced convulsions after exposure Withdrawal Seizure Resistant WSP­2/WSR­2 to ethanol vapor inhalation for 72 hours

SOURCE: *In press.

Vol. 33, Nos. 1 and 2, 2010 69 breeding has been repeated numerous major neurotransmitter targets, includ­ be accessed via the Portland Alcohol times with rats and mice, resulting in ing the glutamate/NMDA,8 serotonin, Research Center Web site (http://www. pairs of animal lines that differ with dopamine, norepinephrine, and cannabi­ ohsu.edu/parc/). respect to a particular alcohol­related noid receptor systems (Kelai et al. The greatest success story for alcohol­ trait. A list of currently available 2006; Smith et al. 2008; Vengeliene et related QTL mapping in rodents has rodent selected lines is shown in table al. 2005). By acting on all these signaling been the discovery of a quantitative 1. Studies with the high­ and low­ systems, alcohol ultimately exerts its trait gene (QTG)9 that affects acute drinking selected lines in particular effects through modulation of intracellular withdrawal severity from both alcohol have been a major focus of NIAAA­ signaling cascades (Newton and Messing and pentobarbital in mice. Originally, sponsored research efforts (for a 2006). Without animal models, researchers investigators mapped several QTLs review, see Crabbe et al. 2010; other could not have gained an understanding contributing to this trait to locations reviews were published in a special of these highly complex mechanisms on various mouse chromosomes issue of Addiction Biology, Vol. underlying alcohol’s diverse effects, and (Buck et al. 1997). Subsequent studies 11[3–4], 2006). Animals have been genetic animal models in particular with a variety of specifically created selected for many alcohol­related have aided in understanding individual genetic animal models gradually nar­ traits, including preference for alco­ differences in sensitivity to these effects. rowed down the size of the DNA hol, tolerance or sensitivity to alco­ region (i.e., reduced the confidence hol’s effects, and withdrawal severity. Gene Identification and interval) around one of these QTLs New selection projects also are Quantitative Trait Locus Mapping until only a few genes remained with­ emerging; for example, researchers are in the confidence interval. Functional breeding mice that exhibit binge­like Animal models also have been exploited for many years in attempts to identify studies then demonstrated that the drinking (Crabbe et al. 2009). most likely gene contributing to the Studies with these selected lines specific gene variations associated with increased sensitivity to alcohol’s effects. trait was Mpdz, which encodes a protein have contributed a great deal to containing multiple structural compo­ understanding the neurobiological These gene­mapping studies, which commenced in the early 1990s, have nents known as PDZ­domains bases for alcohol’s myriad effects. For (Shirley et al. 2004). Studies of this example, researchers consistently have used methods similar to those described above for human studies (e.g., linkage gene’s pattern of expression in the observed low levels of the neurotrans­ brain and of the functions of the mitter serotonin in certain brain areas analyses). They primarily have sought to identify quantitative trait loci (QTLs)— MPDZ protein continue, as do stud­ (i.e., the limbic system) and other ies to identify the receptor molecules DNA regions that are associated with indications of dysregulation of the with which MPDZ interacts (e.g., the characteristics (i.e., quantitative traits) serotonin system in animal lines bred serotonin 2C receptor) (Chen et al. for high alcohol drinking (Crabbe which vary in the degree to which they 2008a; Reilly et al. 2008). 2008). Other studies with selected are present (e.g., sensitivity to alcohol Additional mapping studies aim lines have shown dysregulation of or height). Such traits typically are to narrow other QTLs for alcohol the GABA and glutamate systems determined by multiple genes and each in animals bred to exhibit severe QTL may contain one or more of these responses, both in animals (Bennett withdrawal. (Finn et al. 2004). genes. Compared with humans, studies et al. 2007, 2008; Hitzemann et al. with rats and mice have the distinct 2009) and in humans. A recent com­ advantage that researchers can use indi­ parison of data from mouse and human Contributions of Genetic viduals with defined genotypes and QTL mapping identified a promising Animal Model Research control patterns of mating, making it region of human chromosome 1 that much easier to localize the chromosome was linked to alcohol dependence and region of interest (i.e., the “locus” of which overlapped with an area of Enhanced Understanding of the QTL). The most recent systematic mouse chromosome 1 that has been Alcohol’s Pharmacology and linked to an alcohol withdrawal QTL review (Crabbe et al. 1999) of the 10 Neurobiology alcohol­related QTL data for the various (Ehlers et al. 2010). However, as alcohol­related traits being mapped, Animal research has been invaluable for 8 The N­methy­D­aspartate receptor is one of the receptor types discovering how alcohol exerts its bio­ which now is out of date, listed the for the neurotransmitter glutamate. logical effects. For example, numerous likely locations of several genes affecting 9 In contrast to a QTL, which only identifies a DNA region that studies have shown an important role alcohol withdrawal severity, preference is likely to contain a gene contributing to a quantitative trait for GABA neurotransmission in medi­ for drinking, and sensitivity to alcohol’s (but also may contain other, unrelated DNA sequences), a QTG ating alcohol’s acute and chronic effects effects. Researchers at the Oregon Health represents the actual gene. (Finn et al. 2004; Lobo and Harris 2008; & Science University now maintain a 10 Although humans and mice have different numbers of chromo­ Kumar et al. 2009). Additional animal much more recent update of mouse somes and substantial variation in their genome, there are some parallels between the two genomes. Thus, about 80 percent of studies have demonstrated that alco­ alcohol QTL locations for these and genes that are located closely together on a human chromosome hol’s pharmacology involves nearly all other alcohol­related traits, which can also tend to be located in a cluster on a mouse chromosome.

70 Alcohol Research & Health Genetic Research and Risk for Alcoholism described by Ehlers and colleagues or are involved in similar pathways els, researchers first need to demon­ (2010) a detailed comparison of rodent (e.g., McBride et al. 2009). strate that corresponding genes exist and human maps to see whether the in these organisms and that they QTLs from rodent studies identify Candidate Gene Studies and Gene actually have similar functions. One the same chromosomal regions as the Targeting example of such convergence of evi­ linkage studies in humans is very dif­ dence is the finding that a small sig­ Another important development naling molecule called neuropeptide ficult. Nevertheless, some promising enhancing the possibilities of genetic Y (NPY) and its receptors play a role results of cross­species consistency animal models of alcoholism was the in alcohol intoxication in mice, rats, exist, which likely will increase in development of transgenic animals in and Drosophila (Chen et al. 2008b; number as the details of both rodent the late 1980s. These are animals that Gilpin et al. 2004; Thiele et al. 2002). and human genetic maps improve. have been genetically modified so that A meta­analysis of human association Classical QTL analysis has associated the expression of a single candidate data, in contrast, found no clear evi­ individual differences in gene sequence gene has been selectively inactivated or dence that polymorphisms in the gene (or in other genetic markers, such as augmented compared with the parent encoding a precursor of NPY are microsatellites) with differences in the strain. This approach allows researchers associated with alcohol dependence phenotype being mapped. A recent to study the influence of individual (Zhu et al. 2003). However, some development in rodent QTL map­ genes on risk for alcoholism (or many genes encoding NPY receptors may ping has been development of expres­ other diseases or behaviors). By now, play a role in alcohol dependence and sion QTL (eQTL) mapping. eQTLs more than 100 candidate genes have withdrawal (Wetherill et al. 2008). are DNA regions that differ not in been studied for their contribution to Finally, certain signaling proteins their gene sequence, but in the level alcohol’s effects, usually by comparing (e.g., epidermal growth factor receptor to which the gene becomes active mice in which a single gene has been [EGFR], protein kinase C, protein (i.e., is expressed) in individuals dif­ inactivated (i.e., knockout mice) with kinase A, and cyclic AMP [cAMP]) fering with respect to certain alcohol­ control mice in which the gene still is have been implicated in alcohol’s related traits. This information can functional. As reviewed by Crabbe and effects across multiple species, includ­ be gathered from microarray experi­ colleagues (2006), most of the genes ing humans, rats, mice, Drosophila, ments that measure the levels of indi­ thus studied were found to influence and zebrafish (Corl et al. 2009; vidual mRNAs. These additional some aspect of alcohol sensitivity. For Newton and Messing 2006, 2007; eQTLs greatly expand the pool of example, of 84 different transgenic ani­ Peng et al. 2009). potentially informative genes. mals tested for effects on alcohol self­ The eQTL approach has been used administration, one­quarter exhibited to compare gene expression in brain increased drinking, one­third exhibited Studies of Gene– tissue from several rodent lines and decreased drinking, and 40 percent did Environment Interaction strains genetically predisposed to drink not differ from control animals (Crabbe alcohol with control tissue from low­ et al. 2006). This finding clearly Studies clearly have shown that both drinking animals. The chromosomal demonstrates the multiplicity of genetic genetic and environmental factors con­ location of differentially expressed influences on alcohol responses. As tribute to the risk for alcohol depen­ genes then was compared with QTL gene­targeting technologies allow more dence, and it is likely that the interplay data based on genetic sequence varia­ specific experimental regulation of between these factors is critical for tions (i.e., polymorphisms). This genes than simple deactivation or over­ determining the risk for alcohol abuse combination of information suggested expression, these approaches will continue and dependence. Advances in genetic several candidate genes that may to provide important data. For example, technologies already have allowed influence alcohol drinking (Mulligan researchers now can manipulate genes researchers to explore the genome in et al. 2006; Weng et al. 2009). so that they are expressed only in certain ever greater detail, and with the advent An additional refinement to the cell types or during particular develop­ of whole­genome sequencing, com­ gene­finding efforts has been the mental periods. plete delineation of genetic variation study of networks of proteins or the Candidate gene studies also have soon will be available. In contrast, our genes that encode them. The reason­ been valuable in looking for consistency understanding of the critical environ­ ing is that even if different studies (or across species in the impact of certain mental factors influencing alcohol use studies in different species) do not genes or gene variants. Invertebrate disorders remains inadequate and is an identify the same specific gene as models (e.g., the fruit fly Drosophila area of active research. One of the chal­ being involved in a trait, they might or the worm Caenorhabditis elegans) lenges is how to define the environment, identify a network of genes that under­ offer much more powerful tools to which may include family, peer, and lies the genetic “signal” across studies manipulate the genome than do societal influences; other exposures; and datasets and which encodes rodents (Lovinger and Crabbe 2005). personality or psychiatric factors proteins that have similar functions However, to be able to use such mod­ (which also have genetic components);

Vol. 33, Nos. 1 and 2, 2010 71 and many more, most of which change a stressor). Moreover, the differences exhibited greater levels of DNA methy­ over time. Furthermore, the influence resulted, at least in part, from varia­ lation of two different genes than of these factors on the risk of alcohol tions between high­drinking and low­ nonalcoholics and, consequently, greater use disorders varies within the lifespan drinking animals in a gene encoding reduction in the expression of those genes (Sher et al. 2010; van der Zwaluw and a receptor for corticotropin­releasing (Bleich et al. 2006; Bonsch et al. 2005). Engels 2009). hormone (CRH) (which is involved MicroRNAs—short RNA molecules Animal models offer significant in the body’s stress response) and in naturally encoded by the genome that advantages for studies attempting to the expression of that gene (Hansson can bind to certain mRNA molecules, tease apart genetic and environmental et al. 2006). Thus, this study demon­ thereby repressing the further pro­ influences on an individual’s risk for strated an interaction between a specific cessing of these mRNAs—also might alcoholism. Given their methodological genotype and an environmental factor be involved in regulating alcohol’s power, it is surprising how little (i.e., stress). effects (Miranda et al. 2010). These research into this area has been done Analysis of human gene–environment microRNAs also offer a new experi­ using genetic animal models. One interactions also are complicated by mental method for silencing the trait that has been found to be genet­ the fact that these interactions are expression of specifically targeted ically determined is alcohol prefer­ important from adolescent exposure genes. The expression of microRNAs ence of inbred mouse strains. Thus, to alcohol and then throughout life. is sensitive to epigenetic modulation, specific mouse strains have displayed Accordingly, from a developmental and turning microRNAs on or off their tendencies to drink more or less perspective, the critical environmental has become feasible in rodent models. alcohol by choice repeatedly across 50 influences are likely to change over Modification of microRNAs may years of studies. In fact, alcohol pref­ time (e.g., the relative influence of offer a new pathway for identifying erence in these animals is even more family versus peer factors). Studies that critical genes that can then serve as replicable across studies (and there­ follow genetically specified animals target for new therapeutic drugs for fore, across environments) than brain prospectively while extracting biological alcoholism treatment. weight (Wahlsten et al. 2006), sug­ information at different times along In summary, the genetics field has gesting that it is strongly influenced the way are a promising area for future undergone a technological revolution, by genetic effects. Not all alcohol research that has not been sufficiently particularly in the past decade, allowing traits are so stable, however, and the exploited thus far. researchers to process large numbers combined effects of genetic and envi­ of samples for their genetic studies ronmental manipulations could be and to efficiently interrogate the exploited more fully using genetic Future Directions entire genome. Using these strategies, animal models. researchers have been able to identify A recent review has discussed Research into the genetics of alcoholism, a number of genes in which variations several important features of gene– both in humans and in animal models, appear to contribute to the suscepti­ environment interaction research has made great strides over the past four bility to alcohol dependence. It is (Sher et al. 2010). For example, the decades, and even more approaches are important to note, however, that the social environment plays such a crucial beginning to be evaluated. For example, individual role of each of these genes, role in shaping drinking behaviors in there is growing interest in studying and the SNPs within them, is quite humans, but it is difficult to identify epigenetic factors—that is, factors modest. This means that a given allele corresponding rat and mouse behav­ which alter certain phenotypes by or SNP that has been found to be iors and environmental factors. One modifying regulation of gene expression, associated with alcohol dependence example of a study analyzing gene– without, however, changing the gene’s may increase the risk of alcoholism environment interactions in animals DNA sequence. One such factor that only incrementally. As a result, it would (Hansson et al. 2006) compares the can impact gene expression is methylation be a gross overinterpretation of the influence of environmental stress in of the DNA. Other epigenetic changes results obtained in human association a rat line selectively bred for high alter the packaging of DNA into studies to date to suggest that we alcohol preference (i.e., the Marchigian­ chromatin. For example, two enzyme currently have a means to identify Sardinian preferring rats) with their families called histone acetyltransferases people at greatest risk for alcohol nonselected control group. The inves­ and deacetylases can be used to alter dependence. With the exception of tigators found that the genetically chromatin structure experimentally, and the strong protective effects of certain “enriched” rats were more sensitive studies found that when such changes ADH and ALDH variants, each gene than the control animals to the effects accompany chronic drug administration, variant identified to date has a much of environmental stress on reinstate­ they can modify cocaine­related behaviors smaller individual effect on alcoholism ment of previously extinguished in rats (Renthal and Nestler 2009). risk than, for example, a family history alcohol drinking (i.e., the alcohol­ Although similar research on alcohol­ of alcoholism. preferring rats resumed alcohol drink­ related traits still is in its infancy, some Another challenge is to relate the ing more easily after being exposed to studies have found that alcoholic patients complex human behavioral phenotypes

72 Alcohol Research & Health Genetic Research and Risk for Alcoholism

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