Skip to main content

The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks


Alcoholism is a significant public health problem. A picture of the genetic architecture underlying alcohol-related phenotypes is emerging from genome-wide association studies and work on genetically tractable model organisms.

Alcohol abuse and alcoholism are significant global public health problems. In the USA, alcoholism affects approximately 14 million people at a healthcare cost of $184 billion per year. Excessive alcohol consumption is associated with violent crime, aggression and increased risk of accidents, injury and death. The term 'alcoholism' was first coined by Magnus Huss to describe the persistence of drinking despite adverse health effects. The Diagnostic and Statistical Manual of Mental Disorders classifies alcoholism as an addictive disorder [1]. It is a complex disorder affected by genetic, epigenetic and environmental etiologic factors.

High levels of alcohol intake are associated with impairment of multiple organs, including brain, liver, pancreas and the immune system. The first stage of liver damage following chronic alcohol consumption is the development of fatty liver, which may be followed by inflammation, apoptosis, fibrosis and cirrhosis. Alcohol and its metabolite acetaldehyde are carcinogens, and excessive alcohol consumption is associated with increased risk for mouth and oropharyngeal cancer, breast cancer and liver cancer. The risk of upper gastrointestinal cancer is increased by a missense variant in the gene encoding aldehyde dehydrogenase (ALDH), which is found in some 500 million East Asians [2]. Depression, epilepsy, hypertension and hemorrhagic stroke occur secondary to alcohol consumption [3]. Finally, alcohol consumption during pregnancy can result in birth defects that comprise fetal alcohol syndrome [4]. The diversity of pathologic effects of alcohol indicates that this drug exerts toxicity through multiple mechanisms, each of which can be modulated by different genetic variants.

Twin studies have demonstrated that the amount of alcohol one consumes has a genetic influence [5]. Age at first drink appears to be associated with alcohol-related problem behavior, but progression to alcoholism is under stronger genetic control than initiation, and the effect of early exposure to predict outcome is genetically mediated [6]. Alcohol-related phenotypes are typical quantitative traits, with population variation attributable to multiple segregating loci with effects that are sensitive to environmental exposures. Given that many loci are likely to affect alcohol drinking behavior and the development of dependence, we need to shift our focus from a 'one gene at a time' approach to genetic networks. This can be done by considering the effects of molecular polymorphisms on phenotypes mediated via complex networks of transcriptional, protein, metabolic and neurogenetic endophenotypes. Here, we review genetic risk factors and transcriptional correlates for alcohol consumption in humans, with insights from studies on model genetic organisms.

Human studies

Human genetic studies on alcohol-related phenotypes have used family-based linkage and population-based association analyses to identify quantitative trait loci (QTLs). Linkage studies are based on co-segregation between genetic markers and alcohol dependence in families with several affected members. By contrast, association studies evaluate the strength of association between genetic variants and alcohol phenotypes in samples of unrelated individuals; these can be attributable to a causal effect of the variant or linkage disequilibrium (LD) between the molecular variant and the true causal allele. Association analyses give more precise localization of QTLs than linkage studies; however, false-positive associations can arise from population stratification of cases and controls, and by chance in small samples. In both designs, large numbers of individuals are required to detect QTLs with small effects. Early efforts to dissect the genetic basis of alcohol consumption and addiction in humans were based on candidate genes. The main pathway of ethanol metabolism involves its conversion to acetaldehyde by alcohol dehydrogenase (ADH; Figure 1). Acetaldehyde is oxidized to acetate by aldehyde dehydrogenase (ALDH). The activated form of acetate, acetyl-CoA, can be metabolized into ketone bodies, fatty acids, amino acids and steroids, in addition to oxidation in the Krebs cycle. Cytochrome P450s (for example, those encoded by the gene CYP2E1) and catalase also metabolize a small fraction of ingested ethanol. Multiple ADH and ALDH enzymes are encoded by different genes [7], and different ADH and ALDH alleles can differ in expression levels and in the rate at which their corresponding enzymes metabolize ethanol or acetaldehyde. The ADH1B His48Arg and ALDH2 Lys487 polymorphisms have long been associated with risk of alcoholism, and directly and predictably lead to alcohol-induced flushing through molecular mechanisms that include accumulation of acetaldehyde and release of histamine [8]. ADH1B, ALDH2 and ADH4 influence alcohol consumption and have been implicated as risk factors for developing alcohol abuse or dependence [911].

Figure 1
figure 1

Alcohol metabolism. Ethanol is converted to acetaldehyde by alcohol dehydrogenase (ADH) and subsequently to acetate by aldehyde dehydrogenase (ALDH). Acetate is conjugated to coenzyme A and the resulting acetyl-CoA can be metabolized in the Krebs cycle, or utilized for the synthesis of fatty acids. In addition, a small fraction of ethanol is metabolized by cytochrome P450 2E1 (CYP2E1) and in the brain by catalase. The diagram presents only those members of the ADH and ALDH families referred to in the text. Accumulation of acetaldehyde is responsible for the physiological malaise commonly known as 'hangover'.

The positive reinforcing effects of alcohol are mediated through the corticomesolimbic dopaminergic reward pathway, which extends from the ventral tegmental area to the nucleus accumbens and is modulated by a wide range of neurotransmitters. This pathway is indirectly activated by alcohol through the release of other neurotransmitters, including acetylcholine, dopamine, glutamate, gamma-aminobutyric acid (GABA), opioids and serotonin. Several candidate genes in neurotransmitter pathways associated with the ventral tegmental area and nucleus accumbens have been associated with alcohol dependence, including the genes encoding cholinergic receptor, muscarinic 2 (CHRM2) [12]; cholinergic receptor, nicotinic, alpha 5 (CHRNA5) [13]; catechol-O-methyltransferase (COMT) [9]; GABA A receptor, alpha 2 (GABRA2) [14]; glutamate receptor, metabotropic 8 (GRM8) [15]; solute carrier family 6 (neurotransmitter transporter, serotonin), member 4 (5-HTT) [16]; nuclear factor of kappa light polypeptide gene enhancer in B cells 1 (NFKB1) [17]; monoamine oxidase A (MAOA) [18]; neuropeptide Y receptor Y2 (NPY2R) [19]; opioid receptor, kappa 1 (OPRK1) [20]; opioid receptor, mu 1 (OPRM1) [21]; prodynorphin (PDYN) [20]; and tachykinin receptor 3 (TACR3) [22].

More recently, several genome-wide association studies (GWASs) using 500,000 to 1 million SNPs spanning the entire genome have provided unbiased screens for variants affecting alcohol-related behaviors [2332] (Table 1; Additional file 1). Many of these studies have used samples from large consortia, such as the Collaborative Studies of Genetics of Alcoholism (COGA), the Study of Addiction: Genetics and Environment (SAGE) and the Australian Twin Registry. Consistent with GWAS for other traits [33], many novel loci have been implicated in alcohol dependence and alcohol consumption, but these loci have small effects and are thus difficult to detect with the available sample sizes, especially given the high significance threshold required to control for multiple tests. In one GWAS study, the gene encoding ACN9 homolog (ACN9), which is involved in gluconeogenesis and required for the assimilation of ethanol or acetate into carbohydrate [34], has been associated with susceptibility to alcohol dependence [35]. Two SNPs in the 3' flanking region of the gene encoding peroxisomal trans-2-enoyl-CoA reductase, which is a key enzyme for the peroxisomal fatty acid chain elongation pathway, achieved genome-wide significance for alcohol dependence in a study of German males [31]. A GWAS on pooled DNA samples from individuals with a lifetime history of alcohol dependence, nicotine dependence and co-morbid alcohol/nicotine dependence in an Australian population [28] identified three SNPs that reached genome-wide significance for co-morbid alcohol/nicotine dependence. The implicated genes were: (1) the gene encoding MAP/microtubule affinity-regulating kinase 1 (MARK1), which is a kinase involved in the phosphorylation of microtubule-associated proteins; (2) the gene encoding DEAD box polypeptide 6 (DDX6), which is a putative RNA helicase; and (3) KIAA1409, which encodes a component of the NALCN Na+ channel complex. A family-based association analysis for alcohol dependence that utilized both COGA and the Australian twin-family samples implicated the genes encoding endothelin receptor type B (EDNRB), Usher syndrome 2A (USH2A), TCDD-inducible poly(ADP-ribose) polymerase (TIPARP), monoamine oxidase A, Na+/K+ transporting ATPase interacting 2 (NKAIN2), and Down syndrome cell adhesion molecule like 1 (DSCAML1) [32], with four SNPs in DSCAML1 reaching genome-wide significance. A GWAS for alcohol consumption in Korean male drinkers [23] identified 12 SNPs in six genes (chromosome 12 ORF 51 (C12orf51), and the genes encoding coiled-coil domain containing 63 (CCDC63), myosin, light chain 2 (MYL2), 2'-5'-oligoadenylate synthetase 3 (OAS3), cut-like homeobox 2 (CUX2), and rabphilin 3A homolog (RPH3A)) on chromosome 12q24 associated with alcohol consumption at a genome-wide significance level. In contrast, two studies on alcohol dependence [25, 26], including one of the largest GWASs to date, with over 10,000 individuals from the Australian Twin Registry, failed to identify any SNPs with genome-wide significance. A GWAS meta-analysis of approximately 2.5 million SNPs with alcohol consumption among 12 population-based samples of European ancestry, comprising more than 20,000 individuals [30], identified a single SNP, rs6943555, in the gene for autism susceptibility candidate 2 (AUTS2) associated with alcohol consumption at a genome-wide significance level.

Table 1 Candidate genes for alcohol-related phenotypes replicated in several GWAS and transcriptional profiling studies

Considering only SNPs in genes that achieve genome-wide significance reveals no overlap across the studies, with the exception of the large effects contributed by variation at ADH1B and ALDH2 in Asian populations. Among all SNPs that were significant at a nominal P-value in the studies described above, the gene encoding cadherin 13 (CDH13) was replicated in four independent studies, and eight genes were common across any three studies (Table 1). In addition, five differentially expressed genes in different areas of postmortem human brains of alcoholics were replicated in any of three transcriptional profiling studies (Table 1) [3641].

The lack of concordance across GWASs could be partially due to different measures of alcohol consumption used in different study populations or even across different samples from the same population. Common measures of alcohol consumption are frequency of drinking (weekly and annually), quantity by frequency, maximum drinks in a 24 hour period, frequency of heavy drinking and frequency of intoxication [5]; if these measures are not perfectly correlated, they will be associated with different SNPs. Association studies in humans are limited in resolution by the structure of LD; to the extent that LD varies among populations, different genes may be implicated in different studies. Moreover, rare alleles that contribute to variation in alcohol consumption are essentially blind to detection by association studies using common variants, and many SNPs with small effects may contribute to risk for alcohol dependence.

In summary, GWASs have been limited by difficulties in quantifying alcohol-related phenotypes and in obtaining large sample sizes, together with co-morbidity of alcoholism with other behavioral and neuropsychiatric disorders, gender effects and population admixture. Furthermore, the diversity of mechanisms of vulnerability and resilience to alcohol pose challenges for human genetic studies on alcoholism or alcohol consumption. It has become increasingly clear that, in addition to a few common alleles, many different rare alleles may contribute to vulnerability in different populations.

One strategy that circumvents the limitations of human GWASs relies on comparisons with genes associated with ethanol-related behaviors in genetically amenable model organisms.

Animal models

Given the evolutionary conservation of genes and pathways affecting key biological processes between vertebrates, invertebrates and humans, studies on model organisms (rats, mice, flies and nematodes) have played an important role in identifying potential candidate genes that contribute to alcohol intoxication. Invertebrate and vertebrate models show similar symptoms of alcohol intoxication, including loss of postural control, sedation, immobility and development of tolerance. After alcohol intoxication, mice and rats increase their alcohol consumption, develop tolerance and even alcohol dependence. Drosophila develops tolerance after a single exposure to ethanol [42]. In addition to rapid tolerance, flies develop chronic tolerance after prolonged exposure to a low concentration of ethanol [43]. Caenorhabditis elegans also exhibits tolerance after continuous ethanol exposure [44] and develops ethanol preference as a result of prolonged pre-exposure [45].

In addition to the behavioral similarities between invertebrate and mammalian models, invertebrates use similar neurotransmitter systems, neuropeptides, synaptic proteins, channels and signaling processes to mediate ethanol-induced behaviors [46]. These include genes encoding Ca2+-sensitive adenylate cyclase and protein kinase A [4749], BK channels [5052], Homer [53, 54], genes encoding proteins involved in GABA neurotransmission [55, 56], the gene encoding protein kinase C [57, 58], and genes encoding proteins involved in dopamine and serotonin signaling [45, 59, 60]. In vertebrates, neuropeptide Y (NPY) signaling plays a role in alcohol intake and dependence [61, 62]. Invertebrates have an ortholog to NPY, neuropeptide F (NPF), and signaling via NPF also influences ethanol-related behaviors [44, 63].

Rats meet all the criteria for animal models of alcoholism, including: the ability to orally self-administer ethanol; elevation of blood ethanol concentration after alcohol consumption; willingness to work for ethanol access; development of functional tolerance; and, after a deprivation period, relapse-like behavior [64]. A study on recombinant inbred rat strains identified several genomic regions on chromosomes 1, 6 and 12 that harbor candidate genes for alcohol consumption, including the genes encoding actin filament associated protein, cholecystokinin 2 receptor, melanocortin 4 receptor; protein tyrosine phosphatase receptor type E and tubulin B6 [65]. Furthermore, several microarray studies have identified differential expression of genes between alcohol-preferring and alcohol-non-preferring rat strains, including the genes encoding alpha-adducin (Add1), retinal dehydrogenase 1 (Aldh1a1), adenylate cyclase type 3 (Adcy3), alpha-crystallin B chain (Cryab), glutamate decarboxylase 1 (Gad1) and NPY (Npy) [66, 67]. However, most studies on the genetic underpinnings of alcohol-related phenotypes have focused on mice, because, in contrast to rats, they can be more easily genetically manipulated. Mice are amenable to complete elimination of the gene of interest, gene silencing by RNA interference (RNAi), overexpression and mutagenic technologies [68]. Numerous genetic models have been developed to investigate specific aspects of alcoholism in mice, including tolerance, withdrawal, motivational effects and high-dose sensitivity [68]. Over 90% of the mouse and human genomes can be partitioned into regions of synteny [69].

Among invertebrate models Drosophila is advantageous because large numbers of genetically identical individuals can be reared at relatively low cost and without regulatory restrictions, and many community resources are available for sophisticated genetic manipulations. Drosophila is also readily amenable to neuroanatomical studies.

C. elegans presents a useful model system for examining the effects of ethanol on development [70]. The lineage of each of its 302 neurons and their chemical synapses has been characterized. Nematodes have a short (approximately 3 days) reproductive cycle, enabling large-scale mutagenesis screens within a relatively short time, and they can be cryopreserved.

Mouse models

Studies on mice have identified more than 80 genes that affect alcohol preference drinking [59]. Pioneering work by Buck and colleagues identified three genomic regions on mouse chromosomes 1, 4 and 11 that influence acute alcohol withdrawal [71]. Through a succession of studies involving F2 intercrosses, construction of recombinant inbred lines, and interval-specific congenic strains [7173], the gene encoding multiple PDZ domain protein (Mpdz) was identified as a quantitative trait gene for alcohol withdrawal symptoms. In humans, MPDZ does not demonstrate an association with alcohol-induced withdrawal seizures, but haplotype and single-SNP association analyses suggest a possible association with alcohol dependence [74] and alcohol consumption [65]. Another QTL on chromosome 1 was mapped to a 0.44 Mb interval containing 15 candidate genes, including Kcnj9. Kcnj9 encodes GIRK3, a subunit member of a family of G-protein-dependent inwardly rectifying K+ channels that mediate postsynaptic inhibitory effects of Gi/o-coupled receptors [75]. Kcnj9-null mutant mice show reduced withdrawal from pentobarbital, zolpidem and ethanol [76].

QTLs for alcohol consumption and acute and chronic alcohol withdrawal on distal mouse chromosome 1 [71, 73] are syntenic to a region on human chromosome 1q where several studies have identified QTLs for alcohol-related phenotypes [69, 77, 78]. The gene encoding 5-hydroxytryptamine receptor 1B (Htr1b) is located in this region, and mice in which this gene was knocked out were more aggressive and drank more alcohol, although the effects on alcohol consumption were influenced by unknown environmental factors in different laboratories [79]. In humans, HTR1B was subsequently associated with 'antisocial alcoholism (the dual diagnosis of alcoholism and antisocial personality disorder)' in two populations [80]. A QTL for severity of alcohol dependence and withdrawal on human chromosome 15 was identified in two human studies [77, 81] and is syntenic with a region on mouse chromosome 9, where QTLs for alcohol preference have also been mapped [82, 83]. Significant concordance between allelic variants of human GWASs and orthologous genes associated with alcohol-related phenotypes in mice [84, 85] further demonstrate that mapping genes that underlie alcohol-related behaviors in mice is useful for identifying genes that govern alcohol-related phenotypes in people.

The Drosophilamodel: single gene mutations

Despite differences between the fly brain and the mammalian brain, Drosophila has been a valuable model system for studies on the genetics of alcohol sensitivity. When exposed to alcohol vapors, flies initially become hyperactive, but ultimately lose postural control; alcohol knockdown time provides a measure of sensitivity. Studies on flies have employed two complementary strategies: single mutant analyses and systems genetics approaches. A P-element mutagenesis screen for alcohol sensitivity revealed that a large fraction (approximately 30%) of the genome can contribute to alcohol sensitivity [86]. Indeed, most of the mutations that affect alcohol sensitivity in Drosophila have pleiotropic effects on other complex traits. The first mutants implicated the cyclic AMP signaling pathway, including: the cheapdate allele of amnesiac [49], which encodes a neuropeptide that activates the cyclic AMP signaling pathway [87]; the Ca2+/calmodulin-dependent adenylate cyclase encoded by the rutabaga gene [49]; and PkaR2, which encodes a cyclic AMP-dependent protein kinase [47]. In addition, mutants affecting axonal migration, neural cell adhesion and neurotransmission have also been implicated in alcohol sensitivity, including the gene encoding the axonal migration and cell adhesion receptor fasciclin II [88], the gene encoding GABA-B receptor 1 [56], and genes encoding NPF and its receptor [63]. Others include slowpoke, which encodes a large-conductance Ca2+-activated K+ channel, and arouser, which encodes a predicted adaptor protein homologous to the mammalian epidermal growth factor receptor substrate 8 (Eps8) family. Mutations in slowpoke prevent the development of tolerance [50]. Mutations in the gene encoding arouser (aru) result in increased ethanol sensitivity. The aru gene product interacts with the epidermal growth factor/extracellular signal-regulated kinase and the phospoinositide 3-kinase/Akt pathways to regulate ethanol sensitivity [89].

Several transcription factors have been implicated in alcohol sensitivity and/or induction of tolerance in flies. The hangover gene encodes a transcription factor that contributes to the induction of alcohol tolerance [90]. Similarly, dLmo/Beadex, which encodes a transcriptional regulator, contributes to behavioral responses to ethanol [91]. The mouse ortholog gene encoding LIM domain only 3 (Lmo3) also affects alcohol sensitivity; reduced Lmo3 expression correlates with increased sedation time and reduces voluntary consumption of ethanol [91].

The Drosophilamodel: genetic networks

While single gene approaches have advanced our understanding of how specific genes may influence responses to ethanol, it is becoming increasingly clear that a comprehensive understanding of the genetic architecture of alcohol sensitivity requires studies at the level of genetic networks. Such networks can be constructed based on covariance of transcript levels associated with alcohol sensitivity among different genotypes [92], or computational predictions based on genome-wide co-regulation of transcripts followed by experimental verification [86].

Morozova et al. [92] constructed modules of correlated transcripts associated with alcohol sensitivity and induction of tolerance; these models were validated by transposon-mediated disruption of focal genes. A second approach built computational networks of covariant transcripts around genes that affect sensitivity or resistance to alcohol exposure identified by P-element mutations [86]. Subsequent RNAi-mediated inhibition of genes connected to the focal genes in the networks confirmed their effects on alcohol-related phenotypes. Those genes could, in turn, serve as focal genes to grow the computational networks by iteration, allowing a stepwise expansion of the network with simultaneous functional validation.

From model organisms to human genetics

Evolutionary conservation of pathways offers opportunities for comparative cross-species analyses (Table 2). For example, AUTS2 was identified in human GWASs for alcohol consumption and verified by genotype-specific expression in human prefrontal cortex samples. Differences in expression of Auts2 were also observed in whole-brain extracts of mice selected for differences in voluntary alcohol consumption, and downregulation of an Auts2 homolog was causally associated with reduced alcohol sensitivity in Drosophila. Thus, evidence for the involvement of AUTS2 in alcohol drinking or sensitivity is corroborated across three different species [30].

Table 2 Orthologous candidate genes associated with human alcohol phenotypes, and their differential expression in three model organisms

Because at least 60% of Drosophila genes have conserved human orthologs, the latter can be identified and superimposed on computationally predicted networks from Drosophila. This allows identification of candidate genes for subsequent human association studies based on a previous unbiased genome-wide approach in Drosophila. Not only can this strategy empower human association analysis by reducing the prohibitive multiple testing correction of a GWAS, but it provides also functional contexts to the candidate genes as they form part of defined networks.

To provide proof of principle for the potential of this translational approach, the human ortholog of the Drosophila Men gene, which encodes malic enzyme, was targeted as a candidate gene based on artificial selection, mutational and transcriptional profiling studies [86, 93, 94]. The gene encoding malic enzyme is also differentially expressed in mice upon acute alcohol treatment [95]. Malic enzyme represents a metabolic switch, converting malate into pyruvate while generating NADPH, an essential co-factor for fatty acid biosynthesis (Figure 2). Thus, the malic enzyme reaction enables the development of alcohol-induced fatty liver syndrome. Association studies on the Framingham Offspring cohort showed that intronic SNPs of the gene encoding malic enzyme 1 (ME1) were associated with amount of cocktail drinking, indicating that variation in expression of cytoplasmic malic enzyme contributes to variation in alcohol consumption. Thus, translational approaches from model organisms to humans can identify SNPs that are associated with drinking behavior, with an effect size that could not have been resolved with large-scale unbiased GWASs [92].

Figure 2
figure 2

The malic enzyme metabolic switch. Malic enzyme mediates the conversion of malate to pyruvate, which is accompanied by the production of NADPH. NADPH is a necessary cofactor for the biosynthesis of fatty acids along with acetyl-CoA, generated by the metabolism of ethanol. The diagram highlights auxiliary pathways for the biosynthesis of fatty acids. Pyruvate carboxylase and malic enzyme mediate a cyclic metabolic pathway, which via the mitochondrial citrate and pyruvate transporters results in the transport of acetyl-CoA across the mitochondrial membrane and generation of cytosolic NADPH. An alternative metabolic pathway is the direct conversion of pyruvate into acetyl-CoA via the pyruvate dehydrogenase complex. This metabolic switch channels excess metabolic energy into the synthesis of fatty acids and contributes to the development of fatty liver syndrome during excessive alcohol consumption. Modified from [94].

Concluding remarks

During the past decade a wealth of information on alcohol consumption has been obtained from human and model organism studies, but rarely have data from different studies been integrated to form a comprehensive blueprint of the genetic networks that contribute to alcohol drinking. In future, studies integrating data on alcohol-related phenotypes from GWASs and transcriptional profiling studies on both humans and model organisms will make it possible to construct biologically meaningful networks of genes that contribute to alcohol consumption and dependence, and generate a deeper understanding of the genetic susceptibility for alcoholism.



alcohol dehydrogenase


aldehyde dehydrogenase


Collaborative Studies of Genetics of Alcoholism


gamma-aminobutyric acid


genome-wide association study


linkage disequilibrium




neuropeptide F


neuropeptide Y


quantitative trait locus


RNA interference


single nucleotide polymorphism.


  1. 1.

    American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders. 1994, Washington, DC: American Psychiatric Press, 4

    Google Scholar 

  2. 2.

    Brooks PJ, Goldman D, Li TK: Alleles of alcohol and acetaldehyde metabolism genes modulate susceptibility to oesophageal cancer from alcohol consumption. Hum Genomics. 2009, 3: 103-105.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  3. 3.

    Rehm J, Room R, Graham K, Monteiro M, Gmel G, Sempos CT: The relationship of average volume of alcohol consumption and patterns of drinking to burden of disease: an overview. Addiction. 2003, 98: 1209-1228. 10.1046/j.1360-0443.2003.00467.x.

    Article  PubMed  Google Scholar 

  4. 4.

    Sulik KK: Genesis of alcohol-induced craniofacial dysmorphism. Exp Biol Med (Maywood). 2005, 230: 366-375.

    CAS  Google Scholar 

  5. 5.

    Kendler KS, Gardner C, Dick DM: Predicting alcohol consumption in adolescence from alcohol-specific and general externalizing genetic risk factors, key environmental exposures and their interaction. Psychol Med. 2011, 41: 1507-1516. 10.1017/S003329171000190X.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  6. 6.

    Prescott CA, Kendler KS: Age at first drink and risk for alcoholism: a noncausal association. Alcohol Clin Exp Res. 1999, 23: 101-107.

    CAS  PubMed  Google Scholar 

  7. 7.

    Birley AJ, James MR, Dickson PA, Montgomery GW, Heath AC, Martin NG, Whitfield JB: ADH SNP associations with alcohol metabolism in vivo. Hum Mol Genet. 2009, 18: 1533-1542. 10.1093/hmg/ddp060.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  8. 8.

    Thomasson HR, Crabb DW, Edenberg HJ, Li TK: Alcohol and aldehyde dehydrogenase polymorphisms and alcoholism. Behav Genet. 1993, 23: 131-136. 10.1007/BF01067417.

    Article  CAS  PubMed  Google Scholar 

  9. 9.

    Hendershot CS, Lindgren KP, Liang T, Hutchison KE: COMT and ALDH2 polymorphisms moderate associations of implicit drinking motives with alcohol use. Addict Biol. 2011, 17: 192-201.

    PubMed Central  Article  PubMed  Google Scholar 

  10. 10.

    Edenberg HJ, Xuei X, Chen HJ, Tian H, Wetherill LF, Dick DM, Almasy L, Bierut L, Bucholz KK, Goate A, Hesselbrock V, Kuperman S, Nurnberger J, Porjesz B, Rice J, Schuckit M, Tischfield J, Begleiter H, Foroud T: Association of alcohol dehydrogenase genes with alcohol dependence: a comprehensive analysis. Hum Mol Genet. 2006, 15: 1539-1549. 10.1093/hmg/ddl073.

    Article  CAS  PubMed  Google Scholar 

  11. 11.

    Goldman D, Oroszi G, Ducci F: The genetics of addictions: uncovering the genes. Nat Rev Genet. 2005, 6: 521-532.

    Article  CAS  PubMed  Google Scholar 

  12. 12.

    Luo X, Kranzler HR, Zuo L, Wang S, Blumberg HP, Gelernter J: CHRM2 gene predisposes to alcohol dependence, drug dependence and affective disorders: results from an extended case-control structured association study. Hum Mol Genet. 2005, 14: 2421-2434. 10.1093/hmg/ddi244.

    Article  CAS  PubMed  Google Scholar 

  13. 13.

    Wang JC, Grucza R, Cruchaga C, Hinrichs AL, Bertelsen S, Budde JP, Fox L, Goldstein E, Reyes O, Saccone N, Saccone S, Xuei X, Bucholz K, Kuperman S, Nurnberger J, Rice JP, Schuckit M, Tischfield J, Hesselbrock V, Porjesz B, Edenberg HJ, Bierut LJ, Goate AM: Genetic variation in the CHRNA5 gene affects mRNA levels and is associated with risk for alcohol dependence. Mol Psychiatry. 2009, 14: 501-510. 10.1038/mp.2008.42.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  14. 14.

    Agrawal A, Edenberg HJ, Foroud T, Bierut LJ, Dunne G, Hinrichs AL, Nurnberger JI, Crowe R, Kuperman S, Schuckit MA, Begleiter H, Porjesz B, Dick DM: Association of GABRA2 with drug dependence in the collaborative study of the genetics of alcoholism sample. Behav Genet. 2006, 36: 640-650. 10.1007/s10519-006-9069-4.

    Article  PubMed  Google Scholar 

  15. 15.

    Chen AC, Tang Y, Rangaswamy M, Wang JC, Almasy L, Foroud T, Edenberg HJ, Hesselbrock V, Nurnberger J, Kuperman S, O'Connor SJ, Schuckit MA, Bauer LO, Tischfield J, Rice JP, Bierut L, Goate A, Porjesz B: Association of single nucleotide polymorphisms in a glutamate receptor gene (GRM8) with theta power of event-related oscillations and alcohol dependence. Am J Med Genet B Neuropsychiatr Genet. 2009, 150B: 359-368. 10.1002/ajmg.b.30818.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  16. 16.

    van der Zwaluw CS, Engels RC, Vermulst AA, Rose RJ, Verkes RJ, Buitelaar J, Franke B, Scholte RH: A serotonin transporter polymorphism (5-HTTLPR) predicts the development of adolescent alcohol use. Drug Alcohol Depend. 2010, 112: 134-139. 10.1016/j.drugalcdep.2010.06.001.

    Article  CAS  PubMed  Google Scholar 

  17. 17.

    Edenberg HJ, Xuei X, Wetherill LF, Bierut L, Bucholz K, Dick DM, Hesselbrock V, Kuperman S, Porjesz B, Schuckit MA, Tischfield JA, Almasy LA, Nurnberger JI, Foroud T: Association of NFKB1, which encodes a subunit of the transcription factor NF-kappaB, with alcohol dependence. Hum Mol Genet. 2008, 17: 963-970.

    Article  CAS  PubMed  Google Scholar 

  18. 18.

    Tikkanen R, Sjoberg RL, Ducci F, Goldman D, Holi M, Tiihonen J, Virkkunen M: Effects of MAOA-genotype, alcohol consumption, and aging on violent behavior. Alcohol Clin Exp Res. 2009, 33: 428-434. 10.1111/j.1530-0277.2008.00853.x.

    PubMed Central  Article  PubMed  Google Scholar 

  19. 19.

    Wetherill L, Schuckit MA, Hesselbrock V, Xuei X, Liang T, Dick DM, Kramer J, Nurnberger JI, Tischfield JA, Porjesz B, Edenberg HJ, Foroud T: Neuropeptide Y receptor genes are associated with alcohol dependence, alcohol withdrawal phenotypes, and cocaine dependence. Alcohol Clin Exp Res. 2008, 32: 2031-2040. 10.1111/j.1530-0277.2008.00790.x.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  20. 20.

    Xuei X, Dick D, Flury-Wetherill L, Tian HJ, Agrawal A, Bierut L, Goate A, Bucholz K, Schuckit M, Nurnberger J, Tischfield J, Kuperman S, Porjesz B, Begleiter H, Foroud T, Edenberg HJ: Association of the kappa-opioid system with alcohol dependence. Mol Psychiatry. 2006, 11: 1016-1024. 10.1038/

    Article  CAS  PubMed  Google Scholar 

  21. 21.

    Ray LA, Hutchison KE: A polymorphism of the mu-opioid receptor gene (OPRM1) and sensitivity to the effects of alcohol in humans. Alcohol Clin Exp Res. 2004, 28: 1789-1795. 10.1097/01.ALC.0000148114.34000.B9.

    Article  CAS  PubMed  Google Scholar 

  22. 22.

    Foroud T, Wetherill LF, Kramer J, Tischfield JA, Nurnberger JI, Schuckit MA, Xuei X, Edenberg HJ: The tachykinin receptor 3 is associated with alcohol and cocaine dependence. Alcohol Clin Exp Res. 2008, 32: 1023-1030. 10.1111/j.1530-0277.2008.00663.x.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  23. 23.

    Baik I, Cho NH, Kim SH, Han BG, Shin C: Genome-wide association studies identify genetic loci related to alcohol consumption in Korean men. Am J Clin Nutr. 2011, 93: 809-816. 10.3945/ajcn.110.001776.

    Article  CAS  PubMed  Google Scholar 

  24. 24.

    Bierut LJ, Agrawal A, Bucholz KK, Doheny KF, Laurie C, Pugh E, Fisher S, Fox L, Howells W, Bertelsen S, Hinrichs AL, Almasy L, Breslau N, Culverhouse RC, Dick DM, Edenberg HJ, Foroud T, Grucza RA, Hatsukami D, Hesselbrock V, Johnson EO, Kramer J, Krueger RF, Kuperman S, Lynskey M, Mann K, Neuman RJ, Nöthen MM, Nurnberger JI, Porjesz B: A genome-wide association study of alcohol dependence. Proc Natl Acad Sci USA. 2010, 107: 5082-5087. 10.1073/pnas.0911109107.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  25. 25.

    Edenberg HJ, Koller DL, Xuei X, Wetherill L, McClintick JN, Almasy L, Bierut LJ, Bucholz KK, Goate A, Aliev F, Dick D, Hesselbrock V, Hinrichs A, Kramer J, Kuperman S, Nurnberger JI, Rice JP, Schuckit MA, Taylor R, Todd Webb B, Tischfield JA, Porjesz B, Foroud T: Genome-wide association study of alcohol dependence implicates a region on chromosome 11. Alcohol Clin Exp Res. 2010, 34: 840-852. 10.1111/j.1530-0277.2010.01156.x.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  26. 26.

    Heath AC, Whitfield JB, Martin NG, Pergadia ML, Goate AM, Lind PA, McEvoy BP, Schrage AJ, Grant JD, Chou YL, Zhu R, Henders AK, Medland SE, Gordon SD, Nelson EC, Agrawal A, Nyholt DR, Bucholz KK, Madden PA, Montgomery GW: A Quantitative-trait genome-wide association study of alcoholism risk in the community: findings and Implications. Biol Psychiatry. 2011, 70: 513-518. 10.1016/j.biopsych.2011.02.028.

    PubMed Central  Article  PubMed  Google Scholar 

  27. 27.

    Johnson C, Drgon T, Liu QR, Walther D, Edenberg H, Rice J, Foroud T, Uhl GR: Pooled association genome scanning for alcohol dependence using 104,268 SNPs: validation and use to identify alcoholism vulnerability loci in unrelated individuals from the collaborative study on the genetics of alcoholism. Am J Med Genet B Neuropsychiatr Genet. 2006, 141B: 844-853. 10.1002/ajmg.b.30346.

    Article  PubMed  Google Scholar 

  28. 28.

    Lind PA, Macgregor S, Vink JM, Pergadia ML, Hansell NK, de Moor MH, Smit AB, Hottenga JJ, Richter MM, Heath AC, Martin NG, Willemsen G, de Geus EJ, Vogelzangs N, Penninx BW, Whitfield JB, Montgomery GW, Boomsma DI, Madden PA: A genome-wide association study of nicotine and alcohol dependence in Australian and Dutch populations. Twin Res Hum Genet. 2010, 13: 10-29. 10.1375/twin.13.1.10.

    PubMed Central  Article  PubMed  Google Scholar 

  29. 29.

    Liu QR, Drgon T, Johnson C, Walther D, Hess J, Uhl GR: Addiction molecular genetics: 639,401 SNP whole genome association identifies many "cell adhesion" genes. Am J Med Genet B Neuropsychiatr Genet. 2006, 141B: 918-925. 10.1002/ajmg.b.30436.

    Article  CAS  PubMed  Google Scholar 

  30. 30.

    Schumann G, Coin LJ, Lourdusamy A, Charoen P, Berger KH, Stacey D, Desrivieres S, Aliev FA, Khan AA, Amin N, Aulchenko YS, Bakalkin G, Bakker SJ, Balkau B, Beulens JW, Bilbao A, de Boer RA, Beury D, Bots ML, Breetvelt EJ, Cauchi S, Cavalcanti-Proença C, Chambers JC, Clarke TK, Dahmen N, de Geus EJ, Dick D, Ducci F, Easton A, Edenberg HJ, et al: Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption. Proc Natl Acad Sci USA. 2011, 108: 7119-7124. 10.1073/pnas.1017288108.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  31. 31.

    Treutlein J, Cichon S, Ridinger M, Wodarz N, Soyka M, Zill P, Maier W, Moessner R, Gaebel W, Dahmen N, Fehr C, Scherbaum N, Steffens M, Ludwig KU, Frank J, Wichmann HE, Schreiber S, Dragano N, Sommer WH, Leonardi-Essmann F, Lourdusamy A, Gebicke-Haerter P, Wienker TF, Sullivan PF, Nöthen MM, Kiefer F, Spanagel R, Mann K, Rietschel M: Genome-wide association study of alcohol dependence. Arch Gen Psychiatry. 2009, 66: 773-784. 10.1001/archgenpsychiatry.2009.83.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  32. 32.

    Wang KS, Liu X, Aragam N, Jian X, Mullersman JE, Liu Y, Pan Y: Family-based association analysis of alcohol dependence in the COGA sample and replication in the Australian twin-family study. J Neural Transm.

  33. 33.

    Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A, Cho JH, Guttmacher AE, Kong A, Kruglyak L, Mardis E, Rotimi CN, Slatkin M, Valle D, Whittemore AS, Boehnke M, Clark AG, Eichler EE, Gibson G, Haines JL, Mackay TF, McCarroll SA, Visscher PM: Finding the missing heritability of complex diseases. Nature. 2009, 461: 747-753. 10.1038/nature08494.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  34. 34.

    Dennis RA, McCammon MT: Acn9 is a novel protein of gluconeogenesis that is located in the mitochondrial intermembrane space. Eur J Biochem. 1999, 261: 236-243. 10.1046/j.1432-1327.1999.00267.x.

    Article  CAS  PubMed  Google Scholar 

  35. 35.

    Dick DM, Aliev F, Wang JC, Saccone S, Hinrichs A, Bertelsen S, Budde J, Saccone N, Foroud T, Nurnberger J, Xuei X, Conneally PM, Schuckit M, Almasy L, Crowe R, Kuperman S, Kramer J, Tischfield JA, Hesselbrock V, Edenberg HJ, Porjesz B, Rice JP, Bierut L, Goate A: A systematic single nucleotide polymorphism screen to fine-map alcohol dependence genes on chromosome 7 identifies association with a novel susceptibility gene ACN9. Biol Psychiatry. 2008, 63: 1047-1053. 10.1016/j.biopsych.2007.11.005.

    Article  CAS  PubMed  Google Scholar 

  36. 36.

    Flatscher-Bader T, van der Brug M, Hwang JW, Gochee PA, Matsumoto I, Niwa S, Wilce PA: Alcohol-responsive genes in the frontal cortex and nucleus accumbens of human alcoholics. J Neurochem. 2005, 93: 359-370. 10.1111/j.1471-4159.2004.03021.x.

    Article  CAS  PubMed  Google Scholar 

  37. 37.

    Mayfield RD, Lewohl JM, Dodd PR, Herlihy A, Liu J, Harris RA: Patterns of gene expression are altered in the frontal and motor cortices of human alcoholics. J Neurochem. 2002, 81: 802-813. 10.1046/j.1471-4159.2002.00860.x.

    Article  CAS  PubMed  Google Scholar 

  38. 38.

    Liu J, Lewohl JM, Harris RA, Iyer VR, Dodd PR, Randall PK, Mayfield RD: Patterns of gene expression in the frontal cortex discriminate alcoholic from nonalcoholic individuals. Neuropsychopharmacology. 2006, 31: 1574-1582. 10.1038/sj.npp.1300947.

    Article  CAS  PubMed  Google Scholar 

  39. 39.

    Lewohl JM, Wang L, Miles MF, Zhang L, Dodd PR, Harris RA: Gene expression in human alcoholism: microarray analysis of frontal cortex. Alcohol Clin Exp Res. 2000, 24: 1873-1882. 10.1111/j.1530-0277.2000.tb01993.x.

    Article  CAS  PubMed  Google Scholar 

  40. 40.

    Sokolov BP, Jiang L, Trivedi NS, Aston C: Transcription profiling reveals mitochondrial, ubiquitin and signaling systems abnormalities in postmortem brains from subjects with a history of alcohol abuse or dependence. J Neurosci Res. 2003, 72: 756-767. 10.1002/jnr.10631.

    Article  CAS  PubMed  Google Scholar 

  41. 41.

    Iwamoto K, Bundo M, Yamamoto M, Ozawa H, Saito T, Kato T: Decreased expression of NEFH and PCP4/PEP19 in the prefrontal cortex of alcoholics. Neurosci Res. 2004, 49: 379-385. 10.1016/j.neures.2004.04.002.

    Article  CAS  PubMed  Google Scholar 

  42. 42.

    Scholz H, Ramond J, Singh CM, Heberlein U: Functional ethanol tolerance in Drosophila. Neuron. 2000, 28: 261-271. 10.1016/S0896-6273(00)00101-X.

    Article  CAS  PubMed  Google Scholar 

  43. 43.

    Berger KH, Heberlein U, Moore MS: Rapid and chronic: two distinct forms of ethanol tolerance in Drosophila. Alcohol Clin Exp Res. 2004, 28: 1469-1480. 10.1097/01.ALC.0000141817.15993.98.

    Article  CAS  PubMed  Google Scholar 

  44. 44.

    Davies AG, Bettinger JC, Thiele TR, Judy ME, McIntire SL: Natural variation in the npr-1 gene modifies ethanol responses of wild strains of C. elegans. Neuron. 2004, 42: 731-743. 10.1016/j.neuron.2004.05.004.

    Article  CAS  PubMed  Google Scholar 

  45. 45.

    Lee J, Jee C, McIntire SL: Ethanol preference in C. elegans. Genes Brain Behav. 2009, 8: 578-585. 10.1111/j.1601-183X.2009.00513.x.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  46. 46.

    Scholz H, Mustard JA: Invertebrate models of alcoholism. Curr Top Behav Neurosci.

  47. 47.

    Park SK, Sedore SA, Cronmiller C, Hirsh J: Type II cAMP-dependent protein kinase-deficient Drosophila are viable but show developmental, circadian, and drug response phenotypes. J Biol Chem. 2000, 275: 20588-20596. 10.1074/jbc.M002460200.

    Article  CAS  PubMed  Google Scholar 

  48. 48.

    Maas JW, Vogt SK, Chan GC, Pineda VV, Storm DR, Muglia LJ: Calcium-stimulated adenylyl cyclases are critical modulators of neuronal ethanol sensitivity. J Neurosci. 2005, 25: 4118-4126. 10.1523/JNEUROSCI.4273-04.2005.

    Article  CAS  PubMed  Google Scholar 

  49. 49.

    Moore MS, DeZazzo J, Luk AY, Tully T, Singh CM, Heberlein U: Ethanol intoxication in Drosophila: genetic and pharmacological evidence for regulation by the cAMP signaling pathway. Cell. 1998, 93: 997-1007. 10.1016/S0092-8674(00)81205-2.

    Article  CAS  PubMed  Google Scholar 

  50. 50.

    Cowmeadow RB, Krishnan HR, Ghezzi A, Al'Hasan YM, Wang YZ, Atkinson NS: Ethanol tolerance caused by slowpoke induction in Drosophila. Alcohol Clin Exp Res. 2006, 30: 745-753. 10.1111/j.1530-0277.2006.00087.x.

    Article  CAS  PubMed  Google Scholar 

  51. 51.

    Martin GE, Hendrickson LM, Penta KL, Friesen RM, Pietrzykowski AZ, Tapper AR, Treistman SN: Identification of a BK channel auxiliary protein controlling molecular and behavioral tolerance to alcohol. Proc Natl Acad Sci USA. 2008, 105: 17543-17548. 10.1073/pnas.0801068105.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  52. 52.

    Davies AG, Pierce-Shimomura JT, Kim H, VanHoven MK, Thiele TR, Bonci A, Bargmann CI, McIntire SL: A central role of the BK potassium channel in behavioral responses to ethanol in C. elegans. Cell. 2003, 115: 655-666. 10.1016/S0092-8674(03)00979-6.

    Article  CAS  PubMed  Google Scholar 

  53. 53.

    Urizar NL, Yang Z, Edenberg HJ, Davis RL: Drosophila homer is required in a small set of neurons including the ellipsoid body for normal ethanol sensitivity and tolerance. J Neurosci. 2007, 27: 4541-4551. 10.1523/JNEUROSCI.0305-07.2007.

    Article  CAS  PubMed  Google Scholar 

  54. 54.

    Szumlinski KK, Toda S, Middaugh LD, Worley PF, Kalivas PW: Evidence for a relationship between Group 1 mGluR hypofunction and increased cocaine and ethanol sensitivity in Homer2 null mutant mice. Ann N Y Acad Sci. 2003, 1003: 468-471. 10.1196/annals.1300.055.

    Article  PubMed  Google Scholar 

  55. 55.

    Boehm SL, Ponomarev I, Jennings AW, Whiting PJ, Rosahl TW, Garrett EM, Blednov YA, Harris RA: Gamma-aminobutyric acid A receptor subunit mutant mice: new perspectives on alcohol actions. Biochem Pharmacol. 2004, 68: 1581-1602. 10.1016/j.bcp.2004.07.023.

    Article  CAS  PubMed  Google Scholar 

  56. 56.

    Manev H, Dzitoyeva S: GABA-B receptors in Drosophila. Adv Pharmacol. 2010, 58: 453-464.

    Article  CAS  PubMed  Google Scholar 

  57. 57.

    Chen J, Zhang Y, Shen P: A protein kinase C activity localized to neuropeptide Y-like neurons mediates ethanol intoxication in Drosophila melanogaster. Neuroscience. 2008, 156: 42-47. 10.1016/j.neuroscience.2008.07.008.

    Article  CAS  PubMed  Google Scholar 

  58. 58.

    Bowers BJ, Miyamoto-Ditmon J, Wehner JM: Regulation of 5-HT2A/C receptors and DOI-induced behaviors by protein kinase Cgamma. Pharmacol Biochem Behav. 2006, 85: 441-447. 10.1016/j.pbb.2006.09.022.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  59. 59.

    Crabbe JC, Phillips TJ, Harris RA, Arends MA, Koob GF: Alcohol-related genes: contributions from studies with genetically engineered mice. Addict Biol. 2006, 11: 195-269. 10.1111/j.1369-1600.2006.00038.x.

    Article  CAS  PubMed  Google Scholar 

  60. 60.

    Kong EC, Allouche L, Chapot PA, Vranizan K, Moore MS, Heberlein U, Wolf FW: Ethanol-regulated genes that contribute to ethanol sensitivity and rapid tolerance in Drosophila. Alcohol Clin Exp Res. 2009, 34: 302-316.

    PubMed Central  Article  PubMed  Google Scholar 

  61. 61.

    Thiele TE, Marsh DJ, Ste Marie L, Bernstein IL, Palmiter RD: Ethanol consumption and resistance are inversely related to neuropeptide Y levels. Nature. 1998, 396: 366-369. 10.1038/24614.

    Article  CAS  PubMed  Google Scholar 

  62. 62.

    Thorsell A: Neuropeptide Y (NPY) in alcohol intake and dependence. Peptides. 2007, 28: 480-483. 10.1016/j.peptides.2006.11.017.

    Article  CAS  PubMed  Google Scholar 

  63. 63.

    Wen T, Parrish CA, Xu D, Wu Q, Shen P: Drosophila neuropeptide F and its receptor, NPFR1, define a signaling pathway that acutely modulates alcohol sensitivity. Proc Natl Acad Sci USA. 2005, 102: 2141-2146. 10.1073/pnas.0406814102.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  64. 64.

    Bell RL, Rodd ZA, Lumeng L, Murphy JM, McBride WJ: The alcohol-preferring P rat and animal models of excessive alcohol drinking. Addict Biol. 2006, 11: 270-288. 10.1111/j.1369-1600.2005.00029.x.

    Article  PubMed  Google Scholar 

  65. 65.

    Tabakoff B, Saba L, Printz M, Flodman P, Hodgkinson C, Goldman D, Koob G, Richardson HN, Kechris K, Bell RL, Hübner N, Heinig M, Pravenec M, Mangion J, Legault L, Dongier M, Conigrave KM, Whitfield JB, Saunders J, Grant B, Hoffman PL, WHO/ISBRA Study on State and Trait Markers of Alcoholism: Genetical genomic determinants of alcohol consumption in rats and humans. BMC Biol. 2009, 7: 70-10.1186/1741-7007-7-70.

    PubMed Central  Article  PubMed  Google Scholar 

  66. 66.

    Rodd ZA, Kimpel MW, Edenberg HJ, Bell RL, Strother WN, McClintick JN, Carr LG, Liang T, McBride WJ: Differential gene expression in the nucleus accumbens with ethanol self-administration in inbred alcohol-preferring rats. Pharmacol Biochem Behav. 2008, 89: 481-498. 10.1016/j.pbb.2008.01.023.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  67. 67.

    Kimpel MW, Strother WN, McClintick JN, Carr LG, Liang T, Edenberg HJ, McBride WJ: Functional gene expression differences between inbred alcohol-preferring and -non-preferring rats in five brain regions. Alcohol. 2007, 41: 95-132. 10.1016/j.alcohol.2007.03.003.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  68. 68.

    Bennett B, Downing C, Parker C, Johnson TE: Mouse genetic models in alcohol research. Trends Genet. 2006, 22: 367-374. 10.1016/j.tig.2006.05.005.

    Article  CAS  PubMed  Google Scholar 

  69. 69.

    Ehlers CL, Walter NA, Dick DM, Buck KJ, Crabbe JC: A comparison of selected quantitative trait loci associated with alcohol use phenotypes in humans and mouse models. Addict Biol. 2010, 15: 185-199. 10.1111/j.1369-1600.2009.00195.x.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  70. 70.

    Davis JR, Li Y, Rankin CH: Effects of developmental exposure to ethanol on Caenorhabditis elegans. Alcohol Clin Exp Res. 2008, 32: 853-867. 10.1111/j.1530-0277.2008.00639.x.

    Article  CAS  PubMed  Google Scholar 

  71. 71.

    Buck KJ, Metten P, Belknap JK, Crabbe JC: Quantitative trait loci involved in genetic predisposition to acute alcohol withdrawal in mice. J Neurosci. 1997, 17: 3946-3955.

    CAS  PubMed  Google Scholar 

  72. 72.

    Shirley RL, Walter NA, Reilly MT, Fehr C, Buck KJ: Mpdz is a quantitative trait gene for drug withdrawal seizures. Nat Neurosci. 2004, 7: 699-700. 10.1038/nn1271.

    Article  CAS  PubMed  Google Scholar 

  73. 73.

    Buck KJ, Rademacher BS, Metten P, Crabbe JC: Mapping murine loci for physical dependence on ethanol. Psychopharmacology (Berl). 2002, 160: 398-407. 10.1007/s00213-001-0988-8.

    Article  CAS  Google Scholar 

  74. 74.

    Karpyak VM, Kim JH, Biernacka JM, Wieben ED, Mrazek DA, Black JL, Choi DS: Sequence variations of the human MPDZ gene and association with alcoholism in subjects with European ancestry. Alcohol Clin Exp Res. 2009, 33: 712-721. 10.1111/j.1530-0277.2008.00888.x.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  75. 75.

    Dascal N: Signalling via the G protein-activated K+ channels. Cell Signal. 1997, 9: 551-573. 10.1016/S0898-6568(97)00095-8.

    Article  CAS  PubMed  Google Scholar 

  76. 76.

    Kozell LB, Walter NA, Milner LC, Wickman K, Buck KJ: Mapping a barbiturate withdrawal locus to a 0.44 Mb interval and analysis of a novel null mutant identify a role for Kcnj9 (GIRK3) in withdrawal from pentobarbital, zolpidem, and ethanol. J Neurosci. 2009, 29: 11662-11673. 10.1523/JNEUROSCI.1413-09.2009.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  77. 77.

    Dick DM, Nurnberger J, Edenberg HJ, Goate A, Crowe R, Rice J, Bucholz KK, Kramer J, Schuckit MA, Smith TL, Porjesz B, Begleiter H, Hesselbrock V, Foroud T: Suggestive linkage on chromosome 1 for a quantitative alcohol-related phenotype. Alcohol Clin Exp Res. 2002, 26: 1453-1460. 10.1111/j.1530-0277.2002.tb02443.x.

    Article  CAS  PubMed  Google Scholar 

  78. 78.

    Hill SY, Shen S, Zezza N, Hoffman EK, Perlin M, Allan W: A genome wide search for alcoholism susceptibility genes. Am J Med Genet B Neuropsychiatr Genet. 2004, 128B: 102-113. 10.1002/ajmg.b.30013.

    PubMed Central  Article  PubMed  Google Scholar 

  79. 79.

    Wahlsten D, Metten P, Phillips TJ, Boehm SL, Burkhart-Kasch S, Dorow J, Doerksen S, Downing C, Fogarty J, Rodd-Henricks K, Hen R, McKinnon CS, Merrill CM, Nolte C, Schalomon M, Schlumbohm JP, Sibert JR, Wenger CD, Dudek BC, Crabbe JC: Different data from different labs: lessons from studies of gene-environment interaction. J Neurobiol. 2003, 54: 283-311. 10.1002/neu.10173.

    Article  PubMed  Google Scholar 

  80. 80.

    Lappalainen J, Long JC, Eggert M, Ozaki N, Robin RW, Brown GL, Naukkarinen H, Virkkunen M, Linnoila M, Goldman D: Linkage of antisocial alcoholism to the serotonin 5-HT1B receptor gene in two populations. Arch Gen Psychiatry. 1998, 55: 989-994. 10.1001/archpsyc.55.11.989.

    Article  CAS  PubMed  Google Scholar 

  81. 81.

    Ehlers CL, Gilder DA, Wall TL, Phillips E, Feiler H, Wilhelmsen KC: Genomic screen for loci associated with alcohol dependence in Mission Indians. Am J Med Genet B Neuropsychiatr Genet. 2004, 129B: 110-115. 10.1002/ajmg.b.30057.

    Article  PubMed  Google Scholar 

  82. 82.

    Tarantino LM, McClearn GE, Rodriguez LA, Plomin R: Confirmation of quantitative trait loci for alcohol preference in mice. Alcohol Clin Exp Res. 1998, 22: 1099-1105. 10.1111/j.1530-0277.1998.tb03707.x.

    Article  CAS  PubMed  Google Scholar 

  83. 83.

    Phillips TJ, Huson MG, McKinnon CS: Localization of genes mediating acute and sensitized locomotor responses to cocaine in BXD/Ty recombinant inbred mice. J Neurosci. 1998, 18: 3023-3034.

    CAS  PubMed  Google Scholar 

  84. 84.

    Uhl GR, Drgon T, Johnson C, Fatusin OO, Liu QR, Contoreggi C, Li CY, Buck K, Crabbe J: "Higher order" addiction molecular genetics: convergent data from genome-wide association in humans and mice. Biochem Pharmacol. 2008, 75: 98-111. 10.1016/j.bcp.2007.06.042.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  85. 85.

    Kitsios GD, Tangri N, Castaldi PJ, Ioannidis JP: Laboratory mouse models for the human genome-wide associations. PLoS One. 2010, 5: e13782-10.1371/journal.pone.0013782.

    PubMed Central  Article  PubMed  Google Scholar 

  86. 86.

    Morozova TV, Mackay TFC, Anholt RRH: Transcriptional networks for alcohol sensitivity in Drosophila melanogaster. Genetics. 2011, 187: 1193-1205. 10.1534/genetics.110.125229.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  87. 87.

    Feany MB, Quinn WG: A neuropeptide gene defined by the Drosophila memory mutant amnesiac. Science. 1995, 268: 869-873. 10.1126/science.7754370.

    Article  CAS  PubMed  Google Scholar 

  88. 88.

    Cheng Y, Endo K, Wu K, Rodan AR, Heberlein U, Davis RL: Drosophila fasciclin II is required for the formation of odor memories and for normal sensitivity to alcohol. Cell. 2001, 105: 757-768. 10.1016/S0092-8674(01)00386-5.

    Article  CAS  PubMed  Google Scholar 

  89. 89.

    Eddison M, Guarnieri DJ, Cheng L, Liu CH, Moffat KG, Davis G, Heberlein U: arouser reveals a role for synapse number in the regulation of ethanol sensitivity. Neuron. 2011, 70: 979-990. 10.1016/j.neuron.2011.03.030.

    Article  CAS  PubMed  Google Scholar 

  90. 90.

    Scholz H, Franz M, Heberlein U: The hangover gene defines a stress pathway required for ethanol tolerance development. Nature. 2005, 436: 845-847. 10.1038/nature03864.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  91. 91.

    Lasek AW, Giorgetti F, Berger KH, Tayor S, Heberlein U: Lmo genes regulate behavioral responses to ethanol in Drosophila melanogaster and the mouse. Alcohol Clin Exp Res. 2011, 35: 1600-1606.

    PubMed Central  CAS  PubMed  Google Scholar 

  92. 92.

    Morozova TV, Ayroles JF, Jordan KW, Duncan LH, Carbone MA, Lyman RF, Stone EA, Govindaraju DR, Ellison RC, Mackay TF, Anholt RR: Alcohol sensitivity in Drosophila: translational potential of systems genetics. Genetics. 2009, 183: 733-745. 10.1534/genetics.109.107490. 1SI-12SI

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  93. 93.

    Morozova TV, Anholt RR, Mackay TF: Phenotypic and transcriptional response to selection for alcohol sensitivity in Drosophila melanogaster. Genome Biol. 2007, 8: R231-10.1186/gb-2007-8-10-r231.

    PubMed Central  Article  PubMed  Google Scholar 

  94. 94.

    Morozova TV, Anholt RRH, Mackay TFC: Transcriptional response to alcohol exposure in Drosophila melanogaster. Genome Biol. 2006, 7: R95-10.1186/gb-2006-7-10-r95.

    PubMed Central  Article  PubMed  Google Scholar 

  95. 95.

    Yin HQ, Kim M, Kim JH, Kong G, Kang KS, Kim HL, Yoon BI, Lee MO, Lee BH: Differential gene expression and lipid metabolism in fatty liver induced by acute ethanol treatment in mice. Toxicol Appl Pharmacol. 2007, 223: 225-233. 10.1016/j.taap.2007.06.018.

    Article  CAS  PubMed  Google Scholar 

  96. 96.

    Mulligan MK, Ponomarev I, Hitzemann RJ, Belknap JK, Tabakoff B, Harris RA, Crabbe JC, Blednov YA, Grahame NJ, Phillips TJ, Finn DA, Hoffman PL, Iyer VR, Koob GF, Bergeson SE: Toward understanding the genetics of alcohol drinking through transcriptome meta-analysis. Proc Natl Acad Sci USA. 2006, 103: 6368-6373. 10.1073/pnas.0510188103.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  97. 97.

    Edenberg HJ, Strother WN, McClintick JN, Tian H, Stephens M, Jerome RE, Lumeng L, Li TK, McBride WJ: Gene expression in the hippocampus of inbred alcohol-preferring and -nonpreferring rats. Genes Brain Behav. 2005, 4: 20-30.

    Article  CAS  PubMed  Google Scholar 

  98. 98.

    Awofala AA: Gene regulation in Drosophila melanogaster in response to an acute dose of ethanol. PhD thesis. 2010, University of Sussex, Brighton, UK

    Google Scholar 

  99. 99.

    Sherva R, Rice JP, Neuman RJ, Rochberg N, Saccone NL, Bierut LJ: Associations and interactions between SNPs in the alcohol metabolizing genes and alcoholism phenotypes in European Americans. Alcohol Clin Exp Res. 2009, 33: 848-857. 10.1111/j.1530-0277.2009.00904.x.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  100. 100.

    Saito M, Szakall I, Toth R, Kovacs KM, Oros M, Prasad VV, Blumenberg M, Vadasz C: Mouse striatal transcriptome analysis: effects of oral self-administration of alcohol. Alcohol. 2004, 32: 223-241. 10.1016/j.alcohol.2004.02.005.

    Article  CAS  PubMed  Google Scholar 

  101. 101.

    Mulligan MK, Rhodes JS, Crabbe JC, Mayfield RD, Adron Harris R, Ponomarev I: Molecular profiles of drinking alcohol to intoxication in C57BL/6J mice. Alcohol Clin Exp Res. 2011, 35: 659-670. 10.1111/j.1530-0277.2010.01384.x.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  102. 102.

    Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Sikela JM, Williams RW, Miles MF: Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. J Neurosci. 2005, 25: 2255-2266. 10.1523/JNEUROSCI.4372-04.2005.

    Article  CAS  PubMed  Google Scholar 

  103. 103.

    GeneCards. []

Download references


This work was supported by grant AA016569 (TFCM and RRHA) from the National Institutes of Health. We apologize to those authors whose papers have not been cited in this review. Due to space restrictions we were not able to refer to all publications in the alcohol-related field.

Author information



Corresponding author

Correspondence to Robert RH Anholt.

Additional information

Competing interests

The authors declare that they have no competing interests.

Electronic supplementary material


Additional file 1: Candidate genes at nominal P-value for alcohol dependence in human genome-wide association studies. (XLSX 76 KB)

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Authors’ original file for figure 2

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Morozova, T.V., Goldman, D., Mackay, T.F. et al. The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks. Genome Biol 13, 239 (2012).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:


  • Addiction
  • alcohol sensitivity
  • disease susceptibility
  • genome-wide association studies
  • human genetics
  • model organisms