Abstract
Background/Aim: Alcohol use disorder (AUD) is a chronic, multifactorial psychiatric condition with an enormous impact on public health and social cost. Genetic studies suggest a heritability, and genome-wide association studies (GWAS) have revealed genetic polymorphisms influencing AUD development. Our study aimed to investigate known variants located in ADH1B, DRD2, FAAH, SLC39A8, GCKR, and PDYN genes (rs1229984, rs7121986, rs324420, rs13107325, rs1260326, rs2281285 respectively) in an AUD Greek cohort in order to shed more light on the genetic predisposition to AUD. Materials and Methods: Alcohol-dependent individuals (n=251) meeting both the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) and the ICD-10 guidelines for alcohol abuse and dependence, and control individuals (n=280) were recruited. DNA was extracted from whole blood and PCR-restriction fragment length polymorphism (RFLP-PCR) or allele-specific PCR method was used for genotyping. Results: Individuals carrying the FAAH rs324420 A allele were significantly associated with increased risk of AUD (p<0.0001). SLC39A8 rs13107325 T allele and ADH1B rs1229984 T allele are overrepresented in control subjects (p<0.0001 and p<0.0001, respectively). The associations are maintained following an adjustment for age and sex and Bonferroni correction. GCKR rs13107325, DRD2 rs7121986, and PDYN rs2281285 polymorphisms did not show a significant association with AUD in the studied population after Bonferroni correction. Conclusion: Susceptibility to AUD is related to variations in FAAH, ADH1B, and SLC39A8 genes. These polymorphisms could serve as potential biomarkers for AUD risk.
Alcohol use disorders (AUDs) are characterized by uncontrolled alcohol consumption, compulsive drinking, and negative feelings during alcohol withdrawal that can lead to a chronic and relapsing course (1). AUD is described as a single spectrum of problematic use and clinically significant impairment based on endorsement of at least two of the 11 criteria that assess behavioral and physical manifestations of heavy alcohol consumption by the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) (2). Current estimates suggest that 5.6% of individuals met the AUD criteria during the previous year, leading to important socioeconomical issues and public health losses (3, 4). Recently, data showed that the total quantity of lifetime alcohol consumption and the combination of drinking frequency combined with the amount consumed per incident augment the risk of alcohol-related harm, in a dose-dependent manner (5). For instance, a causal and dose-related link between AUD and various types of cancer has been proposed mostly in the gastrointestinal system, breast, and larynx (6).
The prevalence of AUD is increased among high/upper middle-income countries in both sexes. Approximately 3 million deaths annually (5.3% of all deaths) are due to alcohol abuse, along with more than 5% of the disease burden globally as WHO data suggests (1). Nevertheless, alcohol use and its effects vary remarkably across countries. The European Union (EU) represents the region with the most increased alcohol consumption globally; 87% of the adolescent’s drink at least once in their life. This percentage is higher than that of the American adolescents which is 70% (7). According to WHO, in 2016, the prevalence of alcohol abuse in the Greek population was 9.4% for males and 2.9% for females, while alcohol dependence was 4.2% and 1.3%, respectively (8), indicating that AUDs in Greece are not as common as in North Europe. During the past two decades, nationwide trends present a decline in alcohol use; however, the frequency of alcohol intake by Greek teenagers remains one of the highest in Europe (9). Although AUDs present a warning prevalence and an economic burden (that affects the individuals, their families, and the society) no more than 20% of individuals seek or receive any treatment (10). Even worse, only a small fraction of the affected individuals is prescribed medication with demonstrated efficacy in heavy drinking reduction or abstinence promotion (11).
The pathophysiology of AUDs, as other chronic multifactorial diseases, is attributed to the combination of genetic risk and environmental factors (12). Strong predictors of AUD initiation could be the endophenotypes that are to an extent heritable and include an individual’s response to alcohol and neurobiological susceptibilities (13). A key for developing an effective treatment for AUD could be the deep understanding of its pathophysiological mechanisms (14). The substantial genetic component of alcohol consumption guides the efforts to recognize specific variants across the genome related to AUD, since the heritability of the disease is estimated as high as 50% (2). A plethora of variants have been identified by genome-wide association studies (GWAS) (15-19), with most studies using alcohol consumption (e.g., drinks/week), since it represents an easily assessable measurement.
A twin study found a single-nucleotide polymorphism (SNP)-based heritability of AUD in more than a third of patients (15). Accumulated data from GWAS showed various chromosomal loci to be associated with a greater AUD risk, with some of them presenting significant reproducibility among studies. The most profound connections found in GWAS were the functional polymorphisms in two enzymes affecting alcohol metabolism: alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) (19-24).
Among variants, ADH1B (rs1229984) has been unequivocally linked to the etiology of alcohol addiction (17, 25, 26). A significant conclusion was that missense polymorphisms in ADH1B were associated with AUD in two independent populations (15). An additional implicated gene is the glucokinase receptor gene (GCKR) that regulates cellular trafficking in liver cells. The SNP rs1260326 in GCKR was robustly correlated to alcohol intake (i.e., drinks/week) in large-scale GWAS; this coding missense SNP has been linked with over 25 metabolic traits including type II diabetes. (15, 17-19, 26). To date, another gene locus, (rs7121986) in DRD2 gene has been linked to AUD and other addiction phenotypes, but not to alcohol consumption (17). DRD2 represents a biologically plausible candidate for alcohol dependence susceptibility as shown by in vivo and in vitro experiments (27); since affected DRD2 expression results in heterogenous responses to substances (28) bearing a high addiction risk (26). A few GWAS have linked the rs13107325 polymorphism, located in the Zn transporter gene SLC39A8, to AUD in European populations (17, 26). SLC39A8, one of the most pleiotropic genes, is involved in several biological processes [blood pressure (29), BMI (30), Crohn’s disease (31), serum levels of Mn (32), HDL-cholesterol (33), and schizophrenia (34)]; however, its role in AUD is not sufficiently studied. The FAAH rs324420 variant has been linked to substance use disorders, such as cannabis dependence and evidence suggests that altered FAAH activity could influence alcohol use (35, 36), even though the findings are heterogeneous and complex (37-40). The above-mentioned variant has ancestry-specific effects, suggesting variable results between different populations (36). Likewise, various polymorphisms in PDYN are implicated in the risk for alcohol (41) opioid and cocaine dependence (42, 43). PDYN could be a biologically plausible candidate for substance use disorders, as this gene encodes dynorphins (DYNs), which belong to the opioid peptide family and are crucial regulators in a plethora of brain pathways. Specifically, PDYN rs2281825 has been correlated with depression symptoms in heroin addicted (44) and alcohol negative craving (45) but the findings remain inconsistent (46).
Most of the aforementioned gene polymorphisms have been linked to AUD susceptibility via the available GWAS. Although some of these SNPs have been already studied in multiple genetic studies, the results are inconsistent in different populations and therefore, their role remains to be elucidated. In an attempt to validate previous genetic associations with AUD, our study aimed to investigate known gene polymorphisms located in ADH1B, DRD2, FAAH, SLC39A8 and GCKR genes (rs1229984, rs7121986, rs324420, rs13107325, rs1260326, respectively) in an AUD Greek cohort in order to shed more light on AUD genetic risk.
Materials and Methods
Study population. This case-control study included a total of 531 participants of Greek origin, 251 were alcohol-dependent individuals (cases) and 280 healthy individuals (controls), recruited from the Psychiatric Hospital of Attica (PHA). Cases attended a treatment inpatient program for alcohol dependence during the current study. Diagnostic assessments were determined using the Greek version of the International Neuropsychiatric Interview (M.I.N.I.) clinical inventory (47). Eligible participants met the DSM-IV as well as the ICD-10 criteria for alcohol abuse and dependence, whereas cases with comorbid major mental disorders, such as major depression, bipolar disorder, and schizophrenia were excluded. Furthermore, a family history of alcoholism was recorded. Alcohol dependence severity was estimated through the co-assessment of factors such as the total duration of alcohol use in years, as well as the amount of daily use/abuse of alcohol in years. The non-alcoholic control group was recruited from local communities. All healthy controls were exposed to alcohol but did not report any harmful use or alcohol dependence. A history of drug abuse (except nicotine) and major psychiatric disorders were excluded following the completion of self-report questionnaires. All participants provided written informed consent. The study was conformed to the Declaration of Helsinki.
Genotyping. Genomic DNA was extracted from peripheral whole blood using the NucleoSpin Blood Kit (Macherey-Nagel, Düren, Germany) according to the manufacturer’s instructions. The quality and concentration of purified DNA was estimated using the NanoDrop 8000 Spectrophotometer (Thermo Fisher Scientific Inc., Waltham, MA, USA).
Genotypes for the rs324420 (FAAH gene), rs1260326 (GCKR gene) rs1229984 (ADH1B), and rs2281285 (PDYN) were determined using the PCR-restriction fragment length polymorphism (RFLP-PCR) method. The primer sequences for rs324420 were forward primer: 5′-GGA AGT GAA CAA AGG GAC CA-3′ and reverse primer: 5′-AAT GAC CCA AGA TGC AGA GC-3 (size 204 bp). The PCR products were digested by the restriction enzyme StyI (New England BioLabs, Ipswich, MA, USA) resulting in two fragments of 133 and 71 bp in CC genotype, whereas in the presence of the A allele, products remained uncut as a single fragment of 204 bp (48).
For the rs1260326, PCR was conducted using the forward primer: 5′-TGC AGA CTA TAG TGG AGC CG-3′ and reverse: 5′-CAT CAC ATG GCC ACT GCT TT-3′ followed by digestion with HpaII restriction enzyme (Fermentas, Burlington, ON, Canada). When the C allele was present, digestion resulted in 18, 63, and 150 bp fragments; whereas the TT genotype gave two fragments of 18 and 213 bp (49).
Primers used for the rs1229984 genotypes were forward: 5′ ACA ATC TTT TCT GAA TCT GAA CAG CTT CTC and reverse: 5′ TTG CCA CTA ACC ACG TGG TCA TCT GCG. The PCR product (97 bp) was digested by Hin6I restriction enzyme (Fermentas International Inc.). The PCR product was cut in 70 bp and 27 bp restriction fragments where the common C allele was present. The rs2281285 was genotyped as described previously by Hashemi et al. (46).
Genotyping of the rs13107325 (SLC39A8) and rs7121986 (DRD2) was performed by allele specific PCR. The sequences of the primers were as follows: Common: 5′ ACTTTGTGATCCTACT 3′, C allele: 5′ TATAATATTTGGAGC 3′, T allele: 5′ TATAATATTTGGAGC 3′ for the rs13107325 and common 5′ GTAGAAGAAAACATGAATGC 3′ allele-specific C: 5′ TGGCCTGCCTTCTCCAC 3′, T: 5′ GGCCTGCCTTCTCCAT 3′ for the rs7121986.
Briefly, PCR for all SNPs was carried out in a total volume of 25 μl, containing 100 ng of genomic DNA, 2.5 μl of 10×PCR buffer, 0.5 μmol/l of each primer, 0.15 mmol/l of dNTP, 1.5 mmol/l of MgCl2, and 1 U of Taq DNA polymerase (Kappa Biosystems, Cape Town, South Africa).
Statistical analysis. The association between SNP genotypes and alcoholic status was evaluated using the SNPStats tool applying a chi-squared test (50). A Bonferroni corrected p-value was applied to the multifactorial analysis p-values to account for the multiple testing of six different SNPs in the same samples (corrected α=0.05/6=0.008). Hardy-Weinberg equilibrium was tested separately in patients and healthy controls using the Fischer’s exact test. p≤0.05 (two-sided) was considered significant.
Results
Two hundred fifty-one (251) alcohol-dependent individuals, 191 males (76%) and 60 females (24%) with a mean age of 43.5±11.5 years (range=26-62 years) were recruited. The healthy control group consisted of two hundred eighty (280) non-alcohol dependent subjects with an average age of 42.8±14.3 years (range=21-68 years), 188 males (67%) and 92 females (33%). A positive family history of alcoholism in first degree relatives was reported by 88 cases (35%). Within cases, the average duration of alcohol use was 20.46±8.1 years, while the average daily alcohol use and abuse was 11.93±6.67 years. The demographic and clinical characteristics of participants are presented in Table I. The allele frequencies were in Hardy-Weinberg equilibrium in both patients and control groups (p>0.05). Table II depicts genotype distributions for each SNP in alcohol-dependent and non-dependent healthy individuals. FAAH rs324420 A allele was found to be significantly associated with increased risk of AUD (p<0.0001). This association remained significant and after Bonferroni correction. A marginal association was observed between GCKR, rs1260326 TT genotype and AUD (p=0.04); however, this association did not remain significant after Bonferroni correction. SLC39A8 rs13107325 T allele, and ADH1B rs1229984 T allele were over-represented in non-alcohol dependent controls (p<0.0001, and p<0.0001 respectively), and remained significant after Bonferroni correction, suggesting that SLC39A8 rs13107325 C allele and ADH1B rs1229984 C allele are risk alleles for AUD. Regarding DRD2 rs7121986 polymorphism, even if there is a marginal association before Bonferroni correction of TT genotype and AUD (p=0.04), the presence of the T allele was not found to be associated with AUD risk. For DPYN rs2281285, there is a marginal association before Bonferroni correction of the G allele and AUD (p=0.04); however, this association was not significant after Bonferroni correction.
Characteristics of alcohol-dependent individuals and nondependent controls.
Genotype frequencies and allele distribution between alcohol-dependent individuals and controls.
It is important to note that, the same trends were maintained following an adjustment for age and sex (Table III) and after Bonferroni correction.
Genotype distribution between alcohol-dependent individuals and controls adjusted for sex and age.
Discussion
Alcohol use disorder is a chronic, complex, multifactorial psychiatric condition with an enormous impact on public health and social cost. The likelihood of AUD is possibly attributed to environmental and genetic risk factors (12), yet the underlying pathophysiology of AUD remains poorly understood. Genetic components seem to be crucial in AUD pathogenesis with heritability estimated to be approximately 50% (51, 52). However, identifying genetic risk variants remains a challenge, mostly because of the large genetic and clinical heterogeneity, and the vast number of the implicated variants, which are only partially responsible for the total disease risk (53).
Linkage studies failed to identify specific risk alleles associated with AUD due to its complex, polygenetic pathobiology; thus, GWAS represent the most efficient approach to reveal associated SNPs (52). GWAS of AUD or excessive drinking using various assessment methods have successfully uncovered contingent risk genes (52). Recent large-scale GWAS and meta-analyses including many thousands of participants have revealed associations between AUD susceptibility and common genetic variants in GCKR (15-19, 26), ADH1B (15-19, 26), DRD2 (16, 18, 26), and SLC39A8 (16-19) gene loci.
In the current study, we aimed to clarify the associations between known DNA polymorphisms located in ADH1B, DRD2, FAAH, SLC39A8, GCKR, and PDYN genes and disease risk in a Greek cohort of AUD cases. The findings showed a robust association between FAAH rs324420, SLC39A8 rs13107325 and ADH1B rs1229984 polymorphisms and AUD. A recent systematic review concluded that FAAH protein product (fatty acid amide hydrolase) contributes to the biology and clinical features of AUD; the pharmaceutical targeting of this molecule could be effective for alcohol withdrawal as it may reduce anxiety and alcohol intake reinstatement (54). Fatty acid amide hydrolase metabolizes the endogenous cannabinoid anandamide (AEA), which regulates the brain reward signaling, thus possibly leading to increased addiction susceptibility (55). FAAH variant Pro129Thr (rs324420), reduces FAAH catalytic activity and influences the addictive properties of several substances (36). The association of rs324420 with substance use disorders (56) is in accordance with earlier studies reporting genetic associations with the use of methamphetamine (48), marijuana (57), cannabis (35), and cocaine (58). Regarding alcohol dependence, similarly with our results, Sloan et al. concluded that American European adults (mean age: 39 years) carrying the A allele had a significantly increased frequency of compulsive drinking episodes and increased AUDIT scores as opposed to individuals with the CC genotype (36). Similarly, Best et al. suggested that both AC and AA genotypes of the FAAH rs324420 polymorphism are responsible for abnormal drinking behaviors and increased AUDIT scores in youths (59). Animals carrying the polymorphism have displayed higher alcohol intake and alcohol dependence severity (60), while pharmacological inhibition of FAAH increased anandamide levels and ethanol intake (61).
Regarding, GCKR rs1260326 polymorphism even if this locus has consistently been linked to AUD through GWAS, in contrast to previous studies, in our population, GCKR rs1260326 T allele was found to be slightly over-presented in AUD cases compared to controls; however, this association was not significant (15, 17, 18). This discrepancy, maybe due to the differences between different ethnic groups or/and, the limitation of our study regarding the number of participants. GCKR regulates cellular trafficking in liver cells. Its polymorphism rs1260326 has also been implicated in diverse metabolic diseases (62, 63). Since alcohol intake is connected to metabolic and lipid profiles alike, it remains to be elucidated whether GCKR rs1260326 may have a functional impact on metabolic diseases or alcohol influences glucose and lipid metabolism depending on GCKR genotype.
SLC39A8, one of the most pleiotropic genes, is implicated in various pathophysiological pathways and has been linked to schizophrenia (64, 65), inflammatory bowel disease (31), cardiovascular (29, 66), and metabolic phenotypes (30). A functional study by Evangelou et al. indicated the pivotal role of SLC39A8 in alcohol consumption in Drosophila. Furthermore, the same group suggested a significant association of SNP rs13107325 in the SLC39A8 gene and putamen volume differences (16). Interestingly, evidence from animal studies has linked putamen with alcohol consumption (67). In accordance with our results, Thompson et al. (26) reported the SNP rs13107325 C allele as risk allele for alcohol consumption in European ancestry populations. Other member of the SLC39 family have also been associated to mental disorders, as in the case of SLC39A3 that is associated with bipolar disorder and SLC39A11 with depressive disorder, implying that disrupted transport of metal ions could disturb brain homeostasis (65).
Another genetic locus widely studied in conjunction with alcohol addiction is DRD2, coding for dopamine D2 receptor. The central dopaminergic system is believed to have a vital role in the development of addiction to a plethora of psychoactive substances such as opiates, cocaine, nicotine, and alcohol. DRD2 encodes a receptor of the post-synaptic dopaminergic neurons; its down-regulation has been implicated with alcohol craving stimulating the medial prefrontal cortex (27). Earlier studies of the dopamine receptors have indicated that common DRD2 polymorphisms (−141C Ins/Del, TaqI B, and TaqI A) are associated with alcohol dependence risk (68-73). Subsequent meta-analyses have robustly showed a link between polymorphisms near DRD2 and alcohol dependence (18, 74); however, this gene only exhibits a mild effect that could be partially explained via publication bias influenced by racial ancestry (74). A recent GWAS meta-analysis suggested another intronic variant, the rs7121986, located in DRD2, to be associated with alcohol intake (16). Our study did not find an association with AUD risk in the Greek population. To the best of our knowledge, no other genetic association study has been performed to investigate rs7121986 in alcohol dependence.
The most extensively investigated and well-replicated risk alleles for AUD are located in the ADH gene locus. There are several isoforms of ADH involved in liver alcohol metabolism (ADH1A, ADH1B, ADH1C, and ADH4-7). Alcohol dehydrogenase isoform 1B (ADH1B) is an important ethanol-oxidizing enzyme but is also involved in multiple molecular mechanisms and metabolic processes of several molecules such as fatty acids, acetone, epinephrine, glucose, and neurotransmitters (for instance serotonin and noradrenaline) (75, 76). The ADH1B rs1229984 is associated with alcohol-flush reaction; individuals with the rs1229984 X-allele present a higher ADH activity leading to an increased rate of alcohol metabolism (77). Consistent with previous studies that characterize the T allele as protective (21, 23, 78), our results confirm the decreased risk of developing AUD among those carrying the minor rs1229984 T-allele. Of note, this association is also obvious across different populations (17), such as individuals of European (15, 16, 26), European American (24), African American (23), and Asian origin (78-80).
The last gene examined in our study was PDYN. Either animal experimental studies or postmortem brain human studies have indicated that the dynorphin system has a noteworthy contribution in alcohol and substance addiction. DYNs are enriched in brain circuits affecting mood, motivation, and stimulus-response (habit) and have been associated to drug-seeking behavior (81, 82). The dynorphin (DYN)/k-opioid receptor (KOR) system could be responsible for unpleasant feelings and emotions and affect the motivational parameters of stress by inducing anhedonia, dysphoria, pain, and aversion in humans and animals (45, 83). Various polymorphisms in PDYN have been studied for their correlation to substance addiction (41, 84), but most recently, the rs2281285 has been further discussed for its role in alcohol dependence and negative craving (45, 83, 85). Our results showed no statistical association between this SNP and AUD and are in accordance with the results of Xuei et al. Although Karpyak et al. detected an association between alcohol dependence and rs2281285 (85), results could not reach statistical significance after correction. However, the role of this SNP in negative craving is well established (45) and may present a sex-specific effect (83). Of note, haplotypes including rs2281285 SNP are linked to both alcohol dependence and negative craving, suggesting its involvement with these disorders (85); thus, further studies are needed to elucidate the exact role of this SNP.
In conclusion, our study demonstrated that rs324420 in FAAH, rs13107325 in SLC39A8, and rs1229984 in ADH1B are linked with AUD susceptibility in a Greek population. These polymorphisms could serve as potential biomarkers for AUD risk; however, taking into consideration the complexity of AUD pathogenesis and the variety of the genetic and environmental factors involved, further case-control studies including increased population size and of different origin are needed to confirm these findings.
Footnotes
↵† Deceased Scientist during the study.
Authors’ Contributions
EL, AH, MG analyzed the data and wrote the paper. DT, ES, MP, GM, VM, LL collected the samples and clinical data. DT, MG, NS designed the study. MG, AH and NS reviewed and revised the paper. All Authors contributed to the article and approved the submitted version.
Conflicts of Interest
The Authors have no conflicts of interest to declare in relation to this study.
- Received June 8, 2022.
- Revision received July 1, 2022.
- Accepted July 4, 2022.
- Copyright © 2022, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
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