An overview of the genetic susceptibility to alcoholism

Abstract

Aims

Alcoholism is a multifactorial, genetically influenced disorder. It is a major health and social issue, a highly frequent disease and a cause of premature death. It is also the most expensive addictive disorder due to morbidity, mortality, societal and legal problems. Besides their involvement in alcohol-related fatalities, forensic scientists are also required to assess driving and working ability as well as permanent invalidity due to alcohol-related conditions. Greater knowledge of the genetic basis of alcoholism could improve prevention by identifying specific risk factors and mechanisms, leading to effective therapeutic strategies and eventually to personalized treatments.

Methods

This overview of the recent scientific literature on the genetic basis of alcoholism summarizes the analytical strategies currently applied to the identification of candidate genes involved in alcohol-use disorders (AUDs) and discusses some genes and related phenotypes that have been shown to influence the risk of alcoholism.

Results

Alcoholism is a complex heterogeneous genetic disease. It is a quantitative disorder, in which the combined incidence of multiple genetic factors and environmental factors varies from one subject to another. Family, twin and adoption studies indicate that 50-60% of the risk of alcoholism is due to genetic factors. Risk loci for AUDs include both genes involved in alcohol pharmacokinetics and pharmacodynamics as well as genes moderating neurophysiological responses such as impulsivity, disinhibition, sensation-seeking and externalizing behaviours. Alcoholism also co-exists with other addictions and psychiatric disorders. Such co-morbidity suggests the existence of shared aetiological factors.

Conclusions

Despite several genes that influence the risk for AUDs having been identified, the genetic bases of alcoholisn remain largely unknown. Particularly the mechanism of action or the understanding of the physiology of some genes, as well as the gene-environment interactions, is still unknown. Technological progress and advances in transcriptomics, epigenomics and proteomics are expected to enhance our knowledge of the genetic susceptibility to alcoholism.

Introduction

Alcoholism is a complex medical and genetic disease. It is a quantitative disorder,¹ where the combined incidence of multiple factors, both environmental (e.g. cultural, social political, religious, economic, legal) and genetic (polygenic disorder), varies widely from one subject to another, affecting men and women in a roughly similar way.² Alcoholism is a major health and social issue, being one of the most frequent diseases and a cause of premature death. It is also the most expensive addictive disorder due to morbidity, mortality, societal and legal problems. The 2004 Global Status Report on Alcohol by the World Health Organization estimated that 76.3 million of the two billion people who consume alcoholic beverages suffer from an alcohol-use disorder (AUD) (http://www.who.int/substance_abuse/publications/globalstatusreportalcoholchapters/en/).

According to family, twin and adoption studies 50-60% of the risk of alcoholism is due to genetic factors.^3–5 In early adolescence the initiation and use of alcohol, and of other addictive drugs, is more strongly determined by familial and social factors; their importance gradually diminishes during progression to young and middle adulthood, when the effects of genetic factors become maximal, and then finally declines with ageing.⁶ Only about 25% of people with AUDs seek help, with a greater proportion among women.⁷

Current research is increasingly oriented towards identifying the genes responsible for the genetic susceptibility to alcoholism; differences among individuals are almost certainly due to the combined action of multiple genes, each exerting a small effect, with major contributions from gene-gene and gene-environment interactions. Risk loci for AUDs include both genes involved in alcohol pharmacokinetics (the study of absorption, distribution, metabolism and excretion of a drug), pharmacodynamics (the study of the relationship between the drug and its receptors, its mechanism of action and therapeutic effect) and genes moderating neurophysiological responses such as impulsivity, disinhibition, sensation-seeking and externalizing behaviours.

The understanding of the causes of alcoholism is hampered by its heterogeneous presentation, including a frequent co-occurrence with other addictions (e.g. to illicit substances and nicotine) and with other psychiatric disorders, both internalizing (e.g. depression and anxiety) and externalizing (e.g. antisocial personality disorder, conduct disorder and attention deficit hyperactivity disorder).^8,9 At least some of the co-morbidity is attributable to shared genetic liability. Given the difficulty of isolating the relevant genes, due to non-Mendelian transmission, the phenotypes of affected individuals have been collected to find intermediate phenotypes or endophenotypes resulting from the deconstruction of complex phenotypes to mechanism-related manifestations of genes and environment, which are expected to help identify the genes responsible for the genetic susceptibility to alcoholism. Although it is conceivable that a small number of genes are directly involved, it is more likely that they affect a range of genetically influenced intermediate characteristics that in turn affect the risk for AUDs.¹⁰ Three endophenotypes have been linked to AUDs: (1) alcohol-induced flushing reaction, a protective intermediate phenotype characterized by skin flush upon consumption, associated with a lower AUD risk; (2) low level of response to the effects of alcohol, predictive of the risk of developing AUDs; and (3) electrophysiological, psychological, neuroendocrinological and neuroimaging phenotypes, predictive of diatheses such as alcoholism and other psychiatric disorders.^7,11,12

Although the complexity and heterogeneity of alcoholism hampers identification of the genes involved, knowing the genes and pathways that affect the susceptibility to AUDs may be critical towards isolating specific risk factors and mechanisms, adopting effective prevention strategies, and developing new therapeutic targets and personalized treatments.¹³

To do this it is important to identify: (a) genes predisposing individuals to AUDs; (b) genes modulating the consequences of alcohol exposure, clinical course and treatment response; (c) mechanisms through which genes exert their effects on behaviour; and (d) interactions of genes with other genes and with environmental factors.¹¹

Analytical strategies for the identification of specific genes

Alcoholism is a genetically complex disorder without a clear Mendelian pattern of inheritance (although genes do have an influence, and the close relatives of probands are at increased risk), where a strong influence by lifestyle, individual choices and inherited functional variations makes identification of the relevant alleles essential in order to understand the puzzle of causality.^12,14

Two main strategies are being applied to map genes conferring susceptibility to complex diseases: genome-wide linkage analysis and the candidate gene approach. Linkage and gene association analyses study the co-inheritance of DNA variants by examining the association between polymorphic markers and disease expression. A point of integration between the two strategies of analysis is the genome-wide association study (GWAS), which investigates candidate genes located in chromosome regions that have already been identified.

Linkage analysis is applied to families with several affected individuals to establish whether specific alleles of marker genes are found more often in individuals with the disease than in healthy subjects. The whole genome is analysed using markers that are uniformly distributed on all chromosomes, seeking chromosome regions that could contain genes involved in AUD susceptibility. The linkage is sought only in recent ancestors. Since only a small number of recombination events are involved, the gene regions detected by linkage analysis are likely to be large and to encompass hundreds or even thousands of genes.

Genome-wide linkage studies have identified promising chromosomal regions for AUD susceptibility loci. Linkage studies have been performed by the Collaborative Study on Genetics of Alcoholism (COGA) in a sample recruited at six sites in the United States¹⁵ and by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) in a sample from a Southwest American Indian Tribe (www.niaaa.nih.gov). Extremely high rates of alcoholism have been observed in some American Indian populations, i.e. approximately 80% in men and 50% in women. Well-defined populations such as American Indian tribes are advantageous for identifying the causes underlying complex diseases, as they are often more genetically and environmentally homogeneous than the general population, they are geographically restricted and large families are common.¹⁶ Both studies published by the COGA and by the NIAAA have identified human chromosome regions (hot spots) containing genes that influence risk for alcohol dependence mapping on chromosome 4q. In the COGA sample there was also evidence for linkage to chromosomes 1, 2 and 7. Alcohol dependence was also linked to regions on chromosomes 3 and 8.^17–19

Whereas linkage analyses define vast chromosome regions that are likely to contain the gene(s) that contribute to disease development, association studies identify the genes more accurately. Genetic association studies assess correlations between genetic variants and trait differences on a population scale and they have been used widely to identify regions of the genome and candidate genes that contribute to complex disease. However, there are numerous examples of associations that cannot be replicated, which has led to scepticism about the utility of this approach. This lack of reproducibility is due to poor study design, incorrect assumptions about the underlying genetic architecture and simple over-interpretation of the data. The common errors encountered in association studies of complex diseases are the small sample size, subgroup analysis and multiple testing, random error, poorly matched control group, failure to attempt study replication and to detect linkage disequilibrium with adjacent loci, over-interpreting results and positive publication bias, unwarranted ‘candidate gene’ declaration after identifying association in arbitrary genetic region.²⁰ Despite these known limitations, the power of association analysis to detect genetic contributions to complex disease can be much greater than that of linkage studies.²¹ The power of an association study is the probability of correctly detecting a true association. Power calculations are based on variables such as sample size, the genotypic relative risk, the allele frequency, the strength of linkage disequilibrium between the marker and a causal variant and the mode of transmission.²²

Association studies can be distinguished into family-based, which use the transmission disequilibrium test, and population-based, which use case-control testing. Case-control studies compare genes from two groups of individuals, healthy and diseased. Ideally, the two groups should be homogeneous, with subjects matching for measures like age, ethnicity, years of education, and marital status, and differing only in terms of the disease studied. The allele frequency of the gene markers (e.g. single nucleotide polymorphisms [SNPs]) in or close to the genes are analysed and frequency differences between the groups taken to indicate that the gene contributes to the disease.

Association studies draw from historic recombination so disease-associated regions are extremely small in outbred random mating populations, encompassing only one gene or gene fragment. As the disease mutation is transmitted from one generation to the next, recombination will separate it from the alleles of its original haplotype. A haplotype is a combination of allelic states of a set of polymorphic markers found on the same chromosome.²⁰ The scope for recombination depends mainly on the genetic distance between the markers, but also on locus characteristics. The tendency of specific alleles of separate loci to be co-inherited, because of reduced or absent genetic recombination, known as linkage disequilibrium (LD), could lead to their association in a population. Recent studies examining LD through analysis of the haplotype structures of SNPs have suggested a ‘block’ structure, at least for some parts of the genome. Haplotype blocks appear as regions made up of consecutive co-inherited alleles and within each block most or all SNPs are in high LD. Because haplotype diversity within blocks is limited, many SNPs may be redundant, enabling use of a minimum number of informative markers, or tag SNPs, to identify the shared haplotypes in each block.²³ Block structure variations between populations have important implications for association studies, because tag SNPs identified in one population will not be useful in another if they lie in different blocks. The HapMap (Haplotype Map) project is working to determine the haplotype block structure of the entire genome. Polymorphisms must therefore be selected according to the degree of LD; the haplotype blocks that characterize the relevant population; the resulting amino acid variation; and the gene region where the polymorphisms are found.

The high levels of LD among SNPs are assumed to be true for alleles that increase the risk of complex inherited diseases. This idea, combined with the development of efficient methods for surveying large numbers of SNPs, has led to the many recent GWASs that involve large datasets of unrelated individuals and panels of more than 500,000 polymorphisms. They are more powerful than linkage analyses in identifying genes without prior knowledge of physiology or disease pathophysiology, and have the unique ability to identify risk loci whose effects are much smaller than those detected by linkage strategies. GWA studies have detected SNPs associated with breast cancer,^24,25 colorectal cancer,²⁶ type 2 diabetes^27,28 and heart disease.²⁹

Although, until recently, the only genes known to affect the risk for AUDs were those encoding a number of alcohol metabolizing enzymes, several other genes can be regarded as confirmed risk loci.^13,30

Alcohol dehydrogenase-aldehyde dehydrogenase

About 90% of ethanol oxidation takes place in the liver. The first stage of ethanol metabolism is oxidation to an intermediate toxic substance, acetaldehyde, by alcohol dehydrogenase (ADH). Under normal conditions, acetaldehyde is rapidly oxidized to acetic acid by aldehyde dehydrogenase (ALDH2). There are seven ADH genes (ADH1-7), all found in a cluster of approximately 380 kb located on the long arm of chromosome 4 (4q21-23). The ADH1 class includes three variants, ADH1A, ADH1B and ADH1C.³¹ ADH1B and ADH1C have alleles that encode for enzymes that catalyse ethanol oxidation at different rates. Two functional ADH variants, ADH1B∗2 (47His-369Arg) and ADH1C∗1 (349Ile), encoding the subunits with higher enzyme activity, have been found to be more frequent in east Asian populations, which have a much lower risk of alcohol dependence compared with other populations.

The gene coding for ALDH2 lies in chromosome 12q24. A structural mutation of the gene encodes an isozyme with low catalytic activity. The low activity of allele ALDH2∗2 (Lys487) is dominant over allele ALDH2∗1 (Glu487), and a monozygotic or heterozygotic individual presents a lower rate of acetaldehyde oxidation.³³ It follows that the functional variants of the two main enzymes involved in alcohol metabolism represent genes related to the development of the risk of alcohol dependence. Alleles ADH1B∗2 and ADH1C∗1 enhance acetaldehyde formation, whereas ALDH2∗2 lowers its rate elimination. Accumulation of the metabolite after alcohol consumption constitutes a protection factor against alcoholism. Acetaldehyde causes a flushing reaction very similar to that produced if alcohol is consumed following drugs that block aldehyde dehydrogenase (e.g. disulphiram, which is used in the treatment for alcoholism) as well as vasodilation, sweating, hyperventilation, tachycardia, vertigo, headache, nausea, palpitations and asthenia.

Recently, genotyping of 110 SNPs throughout the ADH gene cluster provided significant evidence for the association of 12 SNPs in and around the ADH4 gene with the alcoholism phenotype.³⁴ These results were confirmed by different authors^35,36 and by our group in an Italian sample of 430 subjects (in press).

Gamma-aminobutyric acid

Gamma-aminobutyric acid (GABA) is the most abundant inhibitory neurotransmitter in the central nervous system and is implicated in many of the effects of alcohol via GABA_A receptors. Strong evidence for a linkage was found with a beta EEG electrophysiological phenotype (13-28 Hz)³⁷ in a relatively small region involving a cluster of four genes encoding the GABA_A receptor subunits GABRG1, GABRA2, GABRA4 and GABRB1. Elevated beta power has also been found in alcohol-dependent subjects and their male offspring.³⁸ In addition, genotyping of 69 SNPs in the four GABA_A subunits from a large number of families with several members affected by alcoholism showed that 31 SNPs in the GABRA2 gene were significantly associated with alcoholism.³⁹ These results were confirmed by subsequent studies.^40–43 However these findings have not been replicated in some case-control and family studies.^44,45 This lack of association was found in families with minimal co-morbidity by Matthews and colleagues⁴⁵ and in alcohol-dependent unrelated individuals from COGA.⁴⁴ The inconsistent data about the involvement of GABRA2 in alcohol addiction have been addressed by other researchers and explanation of confounding offered: as alcoholism is frequently co-incident with illicit drug dependence, the observed association was hypothesized to be a consequence of a genetic predisposition to polysub-stance abuse. The GABRA2 gene may be implicated in poly-substance dependence rather than in alcoholism alone.

Cholinergic muscarinic 2

Cholinergic muscarinic 2 receptor (CHRM2) has been implicated in memory processes. It plays a functional role in cognition via modulation of neuroelectrical oscillations,⁴⁶ and there is direct evidence that its alteration is involved in the development of neuropsychiatric disorders. The CHMR2 gene is localized on the long arm of chromosome 7 and it is a good positional candidate gene for an association with multiple alcoholism and depression-related phenotypes.¹⁹ Recent evidence from the COGA project indicates that the CHRM2 gene is not only associated with neuroelectrical oscillations but also with clinical diagnosis, since polymorphism of CHRM2 introns 4 and 5 was significantly associated with the risk of susceptibility to alcoholism and depression as well as with a spectrum of externalizing disorders.^19,47 The most common haplotype seems to be protective against both alcoholism and depression, and to be undertransmitted to individuals with either disease.¹⁹

OPRM1

Mu-opioid receptor (MOR), encoded by the OPRM1 gene, is widely distributed in the brain. It has high affinity for beta-endorphin and enkephalin, but low affinity for dynor-phin (which preferentially binds to kappa opioid receptor); it also binds exogenous opioids (e.g. morphine, heroin and methadone) with high affinity. In addition, some of the effects of non-opioid substances (e.g. cocaine and alcohol) may be exerted directly or indirectly by interaction with MOR. These findings suggest that the OPRM1 gene could be a joint point of alcohol and drug dependence.⁴⁸

A SNP located at position 118 of exon 1 (188A/G) causes an amino acid substitution (Asn40Asp) in the extracellular portion of MOR.⁴⁹ MOR encoded by the Asp40 variant has greater affinity for beta-endorphin than MOR encoded by Asn40,⁴⁹ even though some studies have provided evidence for reduced affinity of receptors due to the Asp40 variant.⁵⁰ Although this polymorphism appears to be functional, current data on its association with substance dependence phenotypes are inconclusive.

The OPRM1 gene seems to be involved in predicting the response to alcoholism treatment, modulating the response to naltrexone, a MOR antagonist used to maintain abstinence. Its action mechanism is primarily based on blocking the receptor. Here, too, the polymorphism involved is the Asn40Asp variant. A better response to naltrexone among carriers of the Asp40 variant, reported in some trials, has not been confirmed in others.⁵¹

Conclusion

Over the last few years much effort has been devoted to conducting and sustaining biomedical and behavioural investigations into the causes, consequences, treatment and prevention of alcoholism. Understanding this complex, mul-tifactorial disorder clearly requires an approach involving a wide range of biomedical and sociolegal disciplines.

Sequencing of the human genome and large-scale identification of polymorphisms have provided insights into the genetic basis of interindividual differences in the response to potential toxicants such as alcohol. The new opportunities, offered by toxicogenetics, to analyse the genetic variations related to the risk of susceptibility to AUDs are of considerable interest to forensic scientists, who beside their involvement in alcohol-related fatalities may also be required to assess driving and working ability as well as permanent invalidity due to alcohol-related conditions. The identification of genes predisposing individuals to alcoholism could enhance prevention measures. Of course such knowledge does not indicate who will and will not become alcoholics, but could give information about the mechanism of risk involved, and may be a useful tool to follow-up individuals at risk. The identification of a population at risk of alcoholism could enhance the ability to develop new and more effective pharmacologic and behavioural approaches to help alcoholics or subjects at risk of becoming alcoholics.

Despite the identification of several genes influencing the risk for AUDs, technological progress and advances in tran-scriptomics, epigenomics and proteomics make them promising tools for gaining further insights into the genetic susceptibility to alcoholism and into many other complex traits.

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