Skip to main content
Egyptian Journal of Medical Human Genetics
Download PDF

Association of OPRM1 with addiction: a review on drug, alcohol and smoking addiction in worldwide population

Egyptian Journal of Medical Human Genetics volume 23, Article number: 35 (2022) Cite this article

Abstract

Background

Drugs are chemicals which can disrupt the nerve cell functions of the brain. The present study aims to investigate the addiction related gene (OPRM1) in three types of addiction—drugs, alcohol and smoking. Pathway for the addiction was ascertained through KEGG database, and the hotspot mutations for various populations were identified from Gnomad-exomes database. In silico analyses like SIFT, Polyphen, Hope, I-mutant and mutation taster were performed to understand the amino acid substitution, protein function, stability and pathogenicity of the variants.

Main body

Addiction-related variants were found in exons 1, 2 and 3, while the exon 4 did not exhibit any addiction related variation. Among all the variants from this gene, rs1799971 (A118G) polymorphism was the most commonly studied variation for addiction in different populations worldwide. Population-wise allele and genotype frequencies, demographic and epidemiological studies have also been performed from different populations, and the possible association of these variants with addiction was evaluated.

Conclusion

Our findings suggest that OPRM1 polymorphism impact as pharmacogenetic predictor of response to naltrexone and can also address the genetic predisposition related to addiction in human beings.

Background

The epidemic of narcotic addiction is emerging as the most serious clinical issue of current generation as it ruins families, society and countries. Addiction is defined as the inability to stop taking a substance or engaging in an activity, despite the fact that it is harmful to one's mental and physical health. It is about the way our body craves for a substance especially if it causes obsessiveness. Different single nucleotide polymorphisms (SNPs) in the OPRM1 gene have been reported in many populations which has an association with narcotic addiction. We reviewed on three types of addiction which are Drug/Substance addiction, smoking addiction and alcohol addiction related to OPRM1. OPRM1 encodes the mu opioids receptors, which is the primary site of action for the most commonly used opioids including morphine, heroin, fentanyl, etc. It gives the instruction for making the protein called mu opioid receptor. The endogenous opioid system plays a key role in narcotic addiction and mediates the analgesic and reward properties of drugs. The OPRM1 receptor is a membrane of the G-coupled receptor family [1]. This receptor spans more than 80 kbp of nucleotide sequences on chromosome 6q24-25 and is composed of transcript regulatory region, introns and exons [2]. The mu opioid receptor is the major site of action for endogenous opioids, opiate and opioid analgesic drugs and also the exogenous opioids drugs such as heroin, methadone [3]. Particularly, the genomic organization of the human OPRM1 gene locus is highly similar to the mouse locus. However, alternative splicing events display some substantial differences between human and mouse [4].

Addiction can be caused by genetic factors although environmental factors cannot be underestimated as it is also implicated to the development of the opioid addiction [5]. Among all receptors involved in opioid addiction, mu opioid receptor (MOR) has the major role in mediating opioid tolerance and independence [6]. Research findings have suggested that non-opioid drugs like alcohol, cocaine, etc., may again wield some of their effects through the activation of the opioids receptors. The receptors mediate drug-induced feeling and increases the production of chemicals which can lead to feelings of euphoria, analgesia, pleasure and withdrawal [7], and thus it plays a crucial role in reinforcing and rewarding the substance used to include alcohol. Alcohol dependence is a common disorder which might also lead to psychiatric disorder, and there are about 76 million people suffering from alcohol dependence worldwide.

The other non-opioid substances like nicotine/tobacco are also associated with the up-or down-regulation of the encephalic opioid receptor levels and enhance the endorphinis mu receptor mRNA and protein expression in the brain. It also stimulates endogenous opioid release resulting in the mu opioid receptor activation. Smoking remains very common among people with mental health problems, particularly among those who have substance abuse disorders [8]. Nicotine is the primary reward component in tobacco products, and therefore genes involved in the metabolism of nicotine are biologically plausible candidates for genetic studies of smoking behaviour because they determine the levels and persistence of nicotine in the body. Tobacco dependence occurs through nicotine which is the main psychoactive component in tobacco [9].

In the present study, we have conducted a literature review on addiction causing mutations in the OPRM1 gene related to drugs, alcohol and smoking addiction. We have also found the mutational hotspots in this gene in 4 exons from the Ensembl Genome browser and used the genome version of GRch37. Further, we conducted the HOPE, POLYPHEN-2, SIFT, MUTATION TASTER and i-MUTANT assay to test their pathogenicity and protein structure change followed by exploring the addiction pathways of OPRM1gene.

Main text

Association and pathway studies

A huge amount of studies has been reported in the association of opioids drugs/substance addiction with the OPRM1 gene, but the results are not always consistent. Some inconsistent result may be because of the small sample size, inadequate statistics or different diagnostic criteria’s (Table 1). The study included a range of phenotype for narcotic addiction like heroin addiction, cocaine addiction, methamphetamine addiction and amphetamine addiction. On the other way, in case of a long-term exposure, the brain starts to adapt to some amount of dopamine (DA) that can bind to dopamine transporter (DAT) which helps in transporting dopamine back to the nerve terminal. So, higher doses are needed to produce the same level of pleasure. Activation of PKA signalling pathway through D1R receptor results in activation of ΔFosB which plays a role in development and maintenance of addiction. Activation of this cdk5 and activators p35 and DARPP32 leads to activation of protein called postsynaptic density protein 95 (PSD 95) which results in reduction in the synaptic clustering of NMDARs (N-methyl-d-aspartic acid receptor) (Fig. 1).

Table 1 Association and pathway studies of drug addiction
Full size table
Fig. 1
figure 1

Addiction and its related signalling pathway: Long-term exposure, on the other hand, causes the brain to adapt to a certain level of dopamine (DA) that can bind to the dopamine transporter (DAT), which aids in the transit of dopamine back to the nerve terminal. To achieve the same level of enjoyment, greater doses are required. When the PKA signalling pathway is activated via the D1R receptor, FosB is activated, which plays a role in the development and maintenance of addiction. The activation of this cdk5 as well as the activators p35 and DARPP32 causes the protein Postsynaptic density protein 95 (PSD 95) to be activated, resulting in a reduction in NMDAR synaptic cluster

Full size image

Amphetamine Addiction pathway

Amphetamine is a psychostimulant drug that exerts persistent addictive effects. Most addictive drugs increase extracellular concentrations of DA in nucleus accumbens (NAc) and medial prefrontal cortex (mPFC), projection areas of mesocorticolimbic DA neurons and key components of the "brain reward circuit". Amphetamine achieves this elevation in extracellular levels of DA by promoting efflux from synaptic terminals.

Normal condition

Tyrosine hydroxylase (TH) catalyses the hydroxylation of tyrosine to L-DOPA (L-dihydroxyphenylalanine). TH is activated to make more DOPA which after decarboxylation by AADC (aromatic amino acid decarboxylase) the DA is transferred to synaptic cleft by Vesicular Monoamine Transporter (VMAT). At the same time, some amount of DA is converted to dihydroxyphenylacetic acid (DOPAC) and hydrogen per oxide by monoamine oxidase (MOA) in pre-synaptic cleft. DAT helps in transport of DA back to nerve terminal.

Acute amphetamine

Amphetamine-induced tyrosine hydroxylase (TH) results in increased production of DA from L-DOPA through ADCC. DA is transported to synaptic cleft by VMAT, but amphetamine inhibits the activity of MAO. Glutamate binds to its receptor NMDA (N-methyl-D-aspartate) receptor and AMPA. Activation of these receptor allows positive ions to flow through the membrane (Ca2+ and Na+). At the same time, released DA bind to D1R receptor. Influx of positive ions result in depolarization which leads to increased Ca2+ concentration. Activated D1R binds to Gs which leads to induced activation of Adenyl Cyclase, an enzyme which convert ATP to cAMP which in-turn activate PKA signalling pathway. The cAMP binds to CREB protein that regulates expression of genes and thus induces PDYN, arc, c-fos gene expression, which is responsible for induction and maintenance of addiction (Fig. 2).

Fig. 2
figure 2

Amphetamine and its related signalling pathway: Positive ions (Ca2+ and Na+) can pass through the membrane when these receptors are activated. Released DA binds to the D1R receptor at the same time. Depolarization occurs as a result of positive ion flux, resulting in an increase in Ca2+ concentration. When activated D1R binds to Gs, it causes adenyl cyclase, an enzyme that converts ATP to cAMP, to become activated, which activates the PKA signalling pathway. The cAMP binds to the CREB protein, which regulates gene expression and thereby induces the expression of PDYN, arc and c-fos genes, which are responsible for the induction and maintenance of addiction

Full size image

Chronic amphetamine

In case of chronic abuse, amphetamine-induced TH activity results in production of high concentration of DA from L-DOPA through ADCC. DA is transported to synaptic cleft through VMAT, but MAO activity is inhibited and reuptake of DA by DAT is blocked which leads to increased concentration of DA in synaptic cleft. Glutamine binds to its receptor NMDA and AMPA. Exposure to ethanol also influences the expression of Ca2+/calmodulin-dependent protein kinase IV (CaMKIV), where the CaMKIV main role is to activate the CREB, and thereby CREB phosphorylation occurs in the NAC. Not only is CREB phosphorylated upon activation of D1 cAMP-PKA signalling but also DARPP-32, which is a 32-kDa protein that is expressed predominantly in the synaptic neurons. The central action of nicotine is mediated by nicotine acetylcholine nACh receptor. In normal condition, GABA neurons are transported to synaptic vesicle by Vesicular GABA Transmitter (VGAT). GABA mediates its effect via its receptor GABAA. GABAA receptor present in postsynaptic cell contains chloride ions channel (OCl2−), calcium ions channel (OCa2+) and sodium ions channel (Na+) (Fig. 3).

Fig. 3
figure 3

Chronic amphetamine and its related signalling pathway: Ethanol also affects the production of Ca2+/calmodulin-dependent protein kinase IV (CaMKIV), a protein kinase whose major function is to activate CREB, resulting in CREB phosphorylation in the NAC. When D1 cAMP-PKA signalling is activated, not only CREB, but also DARPP-32, a 32-kDa protein produced mostly in synaptic neurons, is phosphorylated. Nicotine's central effect is mediated by the nicotine acetylcholine nACh receptor. Vesicular GABA transmitter transports GABA neurons to synaptic vesicles in normal conditions (VGAT). GABA's action is mediated via the GABAA receptor. Chloride ions channel (OCl2-), calcium ions channel (OCa2+) and sodium ions channel (Na+) are all present in the GABAA receptor in the postsynaptic cell

Full size image

Hotspot mutations

Ensembl Genome Browser of version 37 was used to explore the different variations present in the four exons of the OPRM1. Focus was given to the variant frequency which contains information about sample size, reference and alternate alleles in populations. In the present study, Gnomad-Exomes database was used to find hotspot mutations. The addiction genes were selected separately from all of the variants present in Gnomad-Exomes (Exons 1, 2, 3 and 4), and there were no addiction variants in exon4 from this database. We have seen three addiction variants in exon1, four in exon2 and five in exon3. These addiction variants were tested by using in silico analysis-HOPE, SIFT, POLYPHEN-2, MUTATION TASTER and i-MUTANT (Table 5).

Demographic and epidemiological studies in different populations

A case–control study was performed on addicted patients using opioid, cocaine, ecstasy, alcohol, cannabis and sedative substances and statistical diagnostic of DSM IV [32]. Alblooshi et al. (2018) clinically diagnosed for substance used disorder by DSM V and the epidemiological characteristics appeared to correlate with marital status, and the single males were the highest percentage in the cohort [33]. Coller et al. compared genotyped frequencies between opioid-dependent and control groups, and no difference was observed with a pooled OR (95% CI), from the 13 studies of 1.28 (0.77–2.11), p = 0.34, and the comparison of allele frequencies in case and controls has also no difference with a pooled OR (95% CI) of the 16 studies of 1.16 (0.91–1.47), p = 0.23 [25]. Puspitasari et al. used cross-sectional method and compared the participants as gender (male and female). The G allele tends to be higher in males (p = 0.029) (Table 6) [34].

Population based studies

The Genome Aggregation Database (gnomAD) is used to aggregate and harmonize exome and genome sequencing data from a variety of large-scale sequencing projects and to make summary data available for the wider scientific community (https://gnomad.broadinstitute.org/about). We observed population-based hotspot mutation for each of the variants selected for our review. Among all the 12 variants, rs1799971, rs17174794 and rs62638690 were reported in Clinvar as clinically significant, and among them the variant rs1799971 was associated with all the three types of addiction (drugs, alcohol and nicotine/smoking). Variant Asp-40 does not show altered binding affinities for most opioid peptides and alkaloids tested, but it binds to beta-endorphin, an endogenous opioid that activates the mu opioid receptor approximately 3 times more than the most common allelic form. The rs9282819 and rs9282817 are shown virtually monomorphic, and Clarke et al. showed that rs17174794 has no significant association, while rs17174801 and rs62638690 have shown a significant association for narcotic addiction [35] (Table 4).

Narcotic addiction

Drug/substance addiction is widely studied in different populations in various genes. In the case of the OPRM1 gene, overall there are about 273 SNPs, where variant rsID1799971 from exon1 (also known as A118G, Asn40Asp) are the common polymorphism and mostly studied for addiction [32]. It is the mutational hotspot for the Asian Population and is non-synonymous mutation which indicates the change in amino acid. Turkan et al. included 103 patients addicted to opioids and cocaine and have 83 healthy volunteers with similar demographic features as controls [32]. Their finding includes the genotyping where addicted patients scored 32.0% and control 16.9%, respectively (p value = 0.027), the prevalence of G allele was 16.1% in patient and 8.1% in control group (p value = 0.031) which shows that there is an association between A118G and substance addiction, while there is no result with psychiatric disorder. Schwantes-An et al. performed genetic meta-analysis and has demonstrated that the G allele of rs1799971 has a modest protective effect on substance dependence scoring. The OPRM1 (A118G) polymorphism in Indonesian population and genotype analysis was carried out by a modified allele-specific polymerase chain reaction (PCR) method [36]. Ahmed et al. performed SNPs genotyping of rsID1799971 (A118G) with PCR–RFLP method and found 13% controls and 7% addicts in heterozygous condition, and 8% controls and 22% addicts in homozygous condition [20]. Drakenberg et al. found the association between heroin and A118G SNP in OPRM1 in Caucasian European subjects [37].

Besides, the variant S147C (rs17174794) genotyped in European American was found to increase the potency of Morphine, N152D (rs17174801) mutant leads to the reduced expressions of the receptors [38], and N40D (rs1799971) leads to the loss of a glycosylation site in the extracellular N-terminal domain of the MOR, and association was found in many populations, but not found any of these three variants association with narcotic addiction in this paper. Nikolov et al. (2011) also studied heroin addiction in the Bulgarian population from the ethnic Bulgarian and Roma where allelic and genotyping analysis was done [39]. Different statistical analyses method was done to know the allele and genotype frequency. Various polymorphisms were studied from OPRM1 gene with different substance addiction. In allele frequency, the mutant allele and the wild-type allele frequency were recorded with the OR and p-value. Genotype frequency can be calculated using Hardy–Weinberg equilibrium. The level of statistical significance can be expressed by p-value. A p-value less than 0.05 (typically ≤ 0.05) is said to be statistically significant. The p value higher than 0.05 (> 0.05) is not statistically significant and indicates strong evidence for the null hypothesis.

Alcohol addiction

Frances et al. studied the association between the mu opioid receptor gene and alcohol and tobacco consumption in Spanish population [40]. Lara et al. studied the association between the alcohol and OPRM1 using an intravenous alcohol administration paradigm to investigate the association between sensitivity of OPRM1 and alcohol and the results showed that the alcohol would be higher in the carrier of the G-allele and they were almost three times more likely to have a family history of AUD [41]. The G-allele carriers were linked with higher urgency and regulation of impulsivity. Alblooshi et al. studied DRD2 and OPRM1 as candidate genes and performed a cross-sectional case–control cohort in United Arab Emirates (UAE) population [33] (Table 2). Another study investigated the association between OPRM1 and alcohol dependence in Taiwanese Han where three types of receptor genes were examined by the differences in allele frequency and genotype frequency distribution between cases–control as well as HWE was examined using Fisher’s exact tests.

Table 2 Association and pathway studies of alcohol addiction
Full size table

Nicotine addiction

Nicotine is a chemical found in tobacco, and most smokers use tobacco regularly as they are addicted to nicotine. It is an addictive substance which can affect the lungs through smoking tobacco. Nicotine also increases the levels of endogenous opioids that bind to mu opioid receptors on GABA interneurons in the VTA, and the mu opioid receptor (OPRM1) ASN40ASP functional variant has been associated with response to NRT; however, the direction of association in different populations has not been consistent [48]. The association between the nicotine dependence and the OPRM1 was systematic reviewed, and meta-analysis was performed [49]. The odd ratios (OR) and 95% confidence interval (95% CIs) were calculated in allele, homozygote, heterozygote, dominant and recessive allele. Lechner et al. (2016) found the influence of A118G polymorphism in OPRM1 gene and VNTR polymorphism in DRD2 gene on cigarette cravings after alcohol drinking where genotyping and analysis were done for these polymorphisms. Naltrexone may be an important and helpful in aiding smoking cessation for those who are having a heavy drink of alcohol [50]. Zhang et al. examined the association of smoking initiation and nicotine dependence with mu opioid receptor where the sample was drawn from two population-based twin studies (Table 3) [22]. Kleinjan et al. studied the development of nicotine craving in adolescence smokers who have smoked from the parental exposure of smoking. Three types of genes are genotyped—DRD2, DRD4 and OPRM1 (Fig. 4) [51] (Tables 4, 5 and 6).

Table 3 Association and pathway studies of nicotine/smoking addiction
Full size table
Fig. 4
figure 4

Signalling pathway related to nicotine addiction: Nicotine is a substance contained in tobacco, and most smokers are addicted to nicotine; therefore, they use tobacco on a regular basis. It is an addictive drug that can harm your lungs if you smoke tobacco. The mu opioid receptor (OPRM1) ASN40ASP functional variant has been associated with response to NRT, but the direction of association in different populations has not been consistent. Nicotine also increases the levels of endogenous opioids that bind to mu opioid receptors on GABA interneurons in the VTA

Full size image
Table 4 Population-based variants in the OPRM1
Full size table
Table 5 OPRM1 variants allele frequency and genotype frequency in different worldwide population
Full size table
Table 6 Demographic studies in different populations
Full size table

Conclusion

Taken collectively, our review shows that rs1799971 in exon 1 is the most commonly studied addiction variants in different population in substance addiction. Although there are many studies, the association between addiction and OPRM1 is not fully catalogued [55]. Based on previous studies, males have more chances to become addicted compared to females and different substance addiction was influenced by 60% genetics as well as environmental factor [56]. The identification of genes which involve in addiction pathway may prove our understanding of the disorder and may allow the development of treatment process. As the literature review covers only few exons of OPRM1, the full-length gene sequence data will throw more light for such types of studies. To conclude, as different studies showed conflicting results, researchers may need to study a larger sample size to have a better conclusion. The potential clinical utility of OPRM1 polymorphism which is influenced as a pharmacogenetic predictor of response to naltrexone needs much more study. Thus, it may be necessary to address the genetic predisposition and delineate the association with the clinical problems in future studies.

Availability of data and materials

Not applicable.

Abbreviations

OPRM1 :

Mu (μ) opioid receptor

KEGG:

Kyoto Encyclopedia of Genes and Genomes

SNPs:

Single nucleotide polymorphisms

MOR:

Mu opioid receptor

mRNA:

Messenger ribonucleic acid

DA:

Dopamine

DAT:

Dopamine transporter

D1R receptor:

Dopamine receptor D1

p35:

Cyclin-dependent kinase 5 activator protein

PKA:

CAMP-dependent protein kinase

NMDARs:

N-methyl-d-aspartic acid receptor

NAc:

Nucleus accumbens

mPFC:

Medial prefrontal cortex

TH:

Tyrosine hydroxylase

L-DOPA:

L-Dihydroxyphenylalanine

AADC:

Aromatic amino acid decarboxylase

VMAT:

Vesicular monoamine transporter

DOPAC:

Dihydroxyphenylacetic acid

MOA:

Monoamine oxidase

NMDA:

N-methyl-D-aspartate

CaMKIV:

Ca2+/calmodulin-dependent protein kinase IV

VGAT:

Vesicular GABA transmitter

OCl2:

Chloride ions channel

OCa2+:

Calcium ions channel

gnomAD:

The genome aggregation database

CI:

Confidence interval

PCR:

Polymerase chain reaction

PCR–RFLP:

Polymerase chain reaction–restriction fragment length polymorphism

HWE:

Hardey Weinberg equilibrium

DRD2 :

Dopamine receptor D2

DRD4 :

Dopamine receptor D4

DST:

Department of Science and Technology

References

  1. Bond C, LaForge KS, Tian M, Melia D, Zhang S, Borg L, Gong J, Schluger J, Strong JA, Leal SM, Tischfield JA, Kreek MJ, Yu L (1998) Single-nucleotide polymorphism in the human mu opioid receptor gene alters β-endorphin binding and activity: Possible implications for opiate addiction. PNAS 95:9608–9613

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Wang J, Jin P, Wang W-H, He M, Zhang Z-T, Liu Y (2015) Association of A118G polymorphism in the μ-opioid receptor gene with smoking behaviors: a meta-analysis. J Toxicol Sci 40:711–718

    CAS  PubMed  Google Scholar 

  3. Kreek MJ, Nielsen DA, Butelman ER, LaForge KS (2005) Genetic influences on impulsivity, risk taking, stress responsivity and vulnerability to drug abuse and addiction. Nat Neurosci 8:1450–1457. https://doi.org/10.1038/nn1583

    CAS  Article  PubMed  Google Scholar 

  4. Levran O, Yuferov V, Kreek MJ (2012) The genetics of the opioid system and specific drug addictions. Hum Genet 131:823–842

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Balachandar V, Kumar BL, Suresh K et al (2008) Evaluation of chromosome aberrations in subjects exposed to environmental tobacco smoke in Tamilnadu. India Bull Environ Contam Toxicol 81:270–276. https://doi.org/10.1007/s00128-008-9489-3

    CAS  Article  PubMed  Google Scholar 

  6. Glatt SJ, Bousman C, Wang RS, Murthy KK, Rana BK, Lasky-Su JA, Zhu CS, Zhang R, Li J, Zhang B, Li J, Lyons MJ, Faraone SV, Tsuang MT (2007) Evaluation of OPRM1 variants in heroin dependence by family-based association testing and meta-analysis. Drug Alcohol Depend 90:159–165

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Gianoulakis C (2001) Influence of the endogenous opioid system on high alcohol consumption and genetic predisposition to alcoholism. J Psychiat Neursci 26:304–318

    CAS  Google Scholar 

  8. Geetha B, Sukumar C, Dhivyadeepa E et al (2019) Autism in India: a case–control study to understand the association between socio-economic and environmental risk factors. Acta Neurol Belg 119:393–401. https://doi.org/10.1007/s13760-018-01057-4

    Article  PubMed  Google Scholar 

  9. Pidoplichko VI, DeBiasi M, Williams JT, Dani JA (1997) Nicotine activates and desensitizes midbrain dopamine neurons. Nature 390:401–404

    CAS  PubMed  Google Scholar 

  10. Deb I, Chakraborty J, Gangopadhyay PK, Choudhury SR, Das S (2010) Single-nucleotide polymorphism (A118G) in exon 1 of OPRM1 gene causes alteration in downstream signaling by mu-opioid receptor and may contribute to the genetic risk for addiction. J Neurochem 112:486–496

    CAS  PubMed  Google Scholar 

  11. Crist RC, Clarke T-K, Ang A et al (2013) An intronic variant in OPRD1 predicts treatment outcome for opioid dependence in African-Americans. Neuropsychopharmacol 38:2003–2010

    CAS  Google Scholar 

  12. Dlugos AM, Hamidovic A, Hodgkinson C, Shen P, Goldman D, Palmer AA, de Wit H (2011) OPRM1 gene variants modulate amphetamine-induced euphoria in humans. Genes Brain Behav 10:199–209

    CAS  PubMed  Google Scholar 

  13. Koijam AS, Hijam AC, Singh AS, Jaiswal P, Mukhopadhyay K, Rajamma U, Haobam R (2021) Association of dopamine transporter gene with heroin dependence in an Indian subpopulation from Manipur. J Mol Neurosci 71:122–136

    CAS  PubMed  Google Scholar 

  14. Gelernter J, Cubells J, Kidd J, Pakstis A, Kidd K (1999) Population studies of polymorphisms of the serotonin transporter protein gene. Am J Med Genet 88:61–66

    CAS  PubMed  Google Scholar 

  15. Hoehe MR, Köpke K, Wendel B, Rohde K, Flachmeier C, Kidd KK, Berrettini WH, Church GM (2000) Sequence variability and candidate gene analysis in complex disease: association of µ opioid receptor gene variation with substance dependence. Hum Mol Genet 9:2895–2908

    CAS  PubMed  Google Scholar 

  16. Ide S, Kobayashi H, Ujike H, Ozaki N, Sekine Y, Inada T, Harano M, Komiyama T, Yamada M, Iyo M, Iwata N (2006) Linkage disequilibrium and association with methamphetamine dependence/psychosis of μ-opioid receptor gene polymorphisms. Pharmacogenomics J 6:179–188

    CAS  PubMed  Google Scholar 

  17. Levran O, Londono D, O’hara K, Nielsen DA, Peles E, Rotrosen J, Casadonte P, Linzy S, Randesi M, Ott J, Adelson M (2008) Genetic susceptibility to heroin addiction: a candidate gene association study. Genes Brain Behav 7:720–9

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Levran O, Londono D, O’Hara K, Randesi M, Rotrosen J, Casadonte P, Linzy S, Ott J, Adelson M, Kreek MJ (2009) Heroin addiction in African Americans: a hypothesis-driven association study. Genes Brain Behav 8:531–540

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Xuei X, Flury-Wetherill L, Bierut L, Dick D, NurnbergerJr J, Foroud T, Edenberg HJ (2007) The opioid system in alcohol and drug dependence: family-based association study. Am J Med Genet B Neuropsychiatr Genet 144:877–884

    Google Scholar 

  20. Ahmed M, Ul-Haq I, Faisal M, Waseem D, Taqi MM (2018) Correction to: Implication of OPRM1 A118G polymorphism in opioids addicts in Pakistan: in vitro and in silico analysis. J Mol Neurosci 66:306.17

    Google Scholar 

  21. Zhang H, Kranzler H, Yang B, Luo X, Gelernter J (2008) The OPRD1 and OPRK1 loci in alcohol or drug dependence: OPRD1 variation modulates substance dependence risk. Mol Psychiatry 13:531–543

    CAS  PubMed  Google Scholar 

  22. Kleinjan M, Engels RCME, DiFranza JR (2015) Parental smoke exposure and the development of nicotine craving in adolescent novice smokers: the roles of DRD2, DRD4, and OPRM1 genotypes. BMC Pulm Med 15:115

    PubMed  PubMed Central  Google Scholar 

  23. Zhang H, Gelernter J, Gruen JR, Kranzler HR, Herman AI, Simen AA (2010) Functional impact of a single-nucleotide polymorphism in the OPRD1 promoter region. J Hum Genet 55:278–84

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Kranzler HR, Modesto-Lowe V, Nuwayser ES (1998) Sustained-release naltrexone for alcoholism treatment: a preliminary study. Alcohol Clin Exp Res 22:1074–9

    CAS  PubMed  Google Scholar 

  25. Coller JK, Beardsley J, Bignold J, Li Y, Merg F, Sullivan T, Cox TC, Somogyi AA (2009) Lack of association between the A118G polymorphism of the mu opioid receptor gene (OPRM1) and opioid dependence: a meta-analysis. Pharmacogenom Pers Med 2:9–19

    CAS  Google Scholar 

  26. Shi J, Hui L, Xu Y, Wang F, Huang W, Hu G (2002) Sequence variations in the mu-opioid receptor gene (OPRM1) associated with human addiction to heroin. Hum Mutat 19:459–460

    PubMed  Google Scholar 

  27. Asl SS, Roointan A, Bergen H, Amiri S, Mardani P, Ashtari N, Shabani R, Mehdizadeh M (2018) Opioid receptors gene polymorphism and heroin dependence in Iran. Basic Clin Neurosci 9:101

    Google Scholar 

  28. Huang C, Liu H, Su N, Hsu Y, Yang C, Chen C, Tsai P (2008) Association between human opioid receptor genes polymorphisms and pressure pain sensitivity in females. Anaesthesia 63:1288–1295

    CAS  PubMed  Google Scholar 

  29. Bousman CA, Glatt SJ, Everall IP, Tsuang MT (2009) Genetic association studies of methamphetamine use disorders: a systematic review and synthesis. Am J Med Genet B Neuropsychiatr Genet 150:1025–1049

    Google Scholar 

  30. Nagaya D, Zahari Z, Saleem M, Yahaya B, Tan S, Yusoff N (2018) An analysis of genetic association in opioid dependence susceptibility. J Clin Pharm Ther 43:80–6

    CAS  PubMed  Google Scholar 

  31. Bergen A, Kokoszka J, Peterson R, Long J, Virkkunen M, Linnoila M, Goldman D (1997) μ opioid receptor gene variants: lack of association with alcohol dependence. Mol Psychiatry 2:490–494

    CAS  PubMed  Google Scholar 

  32. Turkan H, Karahalil B, Kadıoğlu E, Eren K, Gurol DT, Karakaya AE (2019) The association between the OPRM1 A118G polymorphism and addiction in a Turkish population. Arc Hig Rada Toksikol 70:97–103

    Google Scholar 

  33. Alblooshi H, Hulse G, Osman W, Kashef AE, Shawky M, Ghaferi HA, Safar HA, Tay GK (2018) The frequency of DRD2 rs1076560 and OPRM1 rs1799971 in substance use disorder patients from the United Arab Emirates. Ann Gen Psychiatry 17:22

    PubMed  PubMed Central  Google Scholar 

  34. Puspitasari AA, Ikawati Z, Rahmawati SSA (2020) High frequency of the opioid receptor µ-1 (OPRM1) A118G polymorphism, an opioid drug therapy related gene, in the indonesian population. Curr Pharmacogenom Pers Med 17:64–69

    CAS  Google Scholar 

  35. Clarke TK, Crist RC, Kampman KM, Dackis CA, Pettinati HM, Brien CPO, Oslin DW, Ferraro TN, Lohoff Berrettini WH (2013) Low frequency genetic variants in the μ-opioid receptor (OPRM1) affect risk for addiction to heroin and cocaine. Neurosci Lett 542:71–5

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Schwantes-An TH, Zhang J, Chen LS et al (2016) Association of the OPRM1 variant rs1799971 (A118G) with non-specific liability to substance dependence in a collaborative de novo meta-analysis of European-ancestry cohorts. Behav Genet 46:151–169

    PubMed  Google Scholar 

  37. Befort K, Filliol D, Décaillot FM, Gavériaux-Ruff C, Hoehe MR, Kieffer BL (2001) A single nucleotide polymorphic mutation in the human μ-opioid receptor severely impairs receptor signaling. J Biol Chem 276:3130–3137

    CAS  PubMed  Google Scholar 

  38. Nikolov MA, Beltcheva O, Galabova A et al (2011) No evidence of association between 118A>G OPRM1 polymorphism and heroin dependence in a large Bulgarian case-control sample. Drug Alcohol Depend 117:62–65

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Frances F, Portoles O, Castello A, Costa JA, Verdu F (2015) Association between opioid receptor mu 1 (OPRM1) gene polymorphisms and tobacco and alcohol consumption in a Spanish population. Bosn J Basic Med Sci 15:31–36

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Ray LA, Barr CS, Blendy JA, Oslin D, Goldman D, Anton RF (2012) The role of the Asn40Asp polymorphism of the mu opioid receptor gene (OPRM1) on alcoholism etiology and treatment: a critical review. Alcohol Clin Exp Res 36:385–394

    CAS  PubMed  Google Scholar 

  41. Munafo MR, Johnstone EC, Aveyard P, Marteau T (2013) Lack of association of OPRM1 genotype and smoking cessation. Nicotine Tob Res 15:739–744

    CAS  PubMed  Google Scholar 

  42. Ehlers CL, Lind PA, Wilhelmsen KC (2008) Association between single nucleotide polymorphisms in the mu opioid receptor gene (OPRM1) and self-reported responses to alcohol in American Indians. BMC Med Genet 9:1–11

    Google Scholar 

  43. Schinka JA, Town T, Abdullah L, Crawford FC, Ordorica PI, Francis E, Hughes P, Graves AB, Mortimer JA, Mullan M (2002) A functional polymorphism within the μ-opioid receptor gene and risk for abuse of alcohol and other substances. Mol Psychiatry 7:224–228

    CAS  PubMed  Google Scholar 

  44. Xuei X, Dick D, Flury-Wetherill L, Tian HJ, Agrawal A, Bierut L, Goate A, Bucholz K, Schuckit M, Nurnberger J, Tischfield J (2006) Association of the κ-opioid system with alcohol dependence. Mol Psychiatry 11:1016–1024

    CAS  PubMed  Google Scholar 

  45. Rouvinen-Lagerström N, Lahti J, Alho H, Kovanen L, Aalto M, Partonen T, Silander K, Sinclair D, Räikkönen K, Eriksson JG, Palotie A (2013) µ-Opioid receptor gene (OPRM1) polymorphism A118G: lack of association in Finnish populations with alcohol dependence or alcohol consumption. Alcohol Alcohol 48:519–525

    PubMed  PubMed Central  Google Scholar 

  46. Kim SG, Kim CM, Kang DH, Kim YJ, Byun WT, Kim SY, Park JM, Kim MJ, Oslin DW (2004) Association of functional opioid receptor genotypes with alcohol dependence in Koreans. Alcohol Clin Exp Res 28:986–990

    CAS  PubMed  Google Scholar 

  47. Fang J, Wang X, He B (2014) Association between common genetic variants in the opioid pathway and smoking behaviors in Chinese men. Behav Brain Funct 10:1–8

    Google Scholar 

  48. Kong X, Deng H, Gong S, Alston T, Kong Y, Wang J (2017) Lack of associations of the opioid receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) with alcohol dependence: review and meta-analysis of retrospective controlled studies. BMC Med Genet 18:120

    PubMed  PubMed Central  Google Scholar 

  49. Lechner WV, Knopik VS, McGeary JE et al (2016) Influence of the A118G polymorphism of the OPRM1 gene and exon 3 VNTR polymorphism of the DRD4 gene on cigarette craving after alcohol administration. Nicotine Tob Res 18:632–636

    CAS  PubMed  Google Scholar 

  50. Zhang L, Kendler KS, Chen X (2006) The μ-opioid receptor gene and smoking initiation and nicotine dependence. Behav Brain Funct 2:28

    PubMed  PubMed Central  Google Scholar 

  51. Bart G, Heilig M, LaForge K, Pollak L, Leal S, Ott J, Kreek M (2004) Substantial attributable risk related to a functional mu-opioid receptor gene polymorphism in association with heroin addiction in central Sweden. Mol Psychiat 9:547–549

    CAS  Google Scholar 

  52. Munafò MR, Johnstone EC, Aveyard P, Marteau T (2013) Lack of association of OPRM1 genotype and smoking cessation. Nicotine Tob Res 15:739–744

    PubMed  Google Scholar 

  53. Türkan H, Karahalil B, Kadıoğlu E, Eren K, Gürol DT, Karakaya AE (2019) The association between the OPRM1 A118G polymorphism and addiction in a Turkish population. Arh Hig Rada Toksikol 70:97–103

    PubMed  Google Scholar 

  54. Al-Eitan LN, Rababa’h DM, Alghamdi MA (2021) Genetic susceptibility of opioid receptor genes polymorphism to drug addiction: a candidate-gene association study. BMC Psychitr 21:5. https://doi.org/10.1186/s12888-020-03006-z

    CAS  Article  Google Scholar 

  55. Balachandar V, Lakshmankumar B, Suresh K, Manikantan P, Sangeetha R, Mohanadevi S, Sasikala K (2016) Cytogenetic damage in khaini users of Tamilnadu, cytogenetic damage in khaini users of Tamilnadu, Cytogenetic damage in khaini users of Tamilnadu, Southern India. Braz J Oral Sci 7(25):1559–1562

    Google Scholar 

  56. Manikantan P, Balachandar V, Sasikala K, Mohanadevi S (2010) Lymphocyte DNA damage in chewing tobacco users of Coimbatore, Tamilnadu, by using comet assay. J Human Eco 31(1):53–58

    Google Scholar 

Download references

Acknowledgements

The authors acknowledge DST, India and Mizoram University, Aizawl, to complete this work successfully.

Funding

The authors are thankful to DST, New Delhi, for the Technology Enabling Centre which facilitated the work. The authors report no declarations of interest.

Author information

Authors and Affiliations

  1. Department of Biotechnology, Mizoram University, Aizawl, Mizoram, India

    Vanlal Hriatpuii, Krothapalli R. S. Sambasiva Rao & Nachimuthu Senthil Kumar

  2. Substance Abuse and Palliative Care Unit, Synod Hospital, Aizawl, Mizoram, India

    Hoikhe Priscilla Sema

  3. Community Medicine, Zoram Medical College, Falkawn, Mizoram, India

    Chenkual Vankhuma

  4. Livestock Farming and Bioresources Technology, Coimbatore, Tamil Nadu, India

    Mahalaxmi Iyer

  5. SN ONGC Department of Genetics and Molecular Biology, Vision Research Foundation, Sankara Nethralaya, Chennai, 600 006, India

    Mohana Devi Subramaniam

  6. Department of Human Genetics and Molecular Biology, Bharathiar University, Coimbatore, 641 046, India

    Balachandar Vellingiri

Authors
  1. Vanlal Hriatpuii
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hoikhe Priscilla Sema
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chenkual Vankhuma
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mahalaxmi Iyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mohana Devi Subramaniam
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Krothapalli R. S. Sambasiva Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Balachandar Vellingiri
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Nachimuthu Senthil Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

NSK, VH, CV and HPS performed conceptualization of the manuscript; VB, IM, SMD and KRSSR revised and edited the manuscript. All authors have reviewed the manuscript.

Corresponding authors

Correspondence to Balachandar Vellingiri or Nachimuthu Senthil Kumar.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hriatpuii, V., Sema, H.P., Vankhuma, C. et al. Association of OPRM1 with addiction: a review on drug, alcohol and smoking addiction in worldwide population. Egypt J Med Hum Genet 23, 35 (2022). https://doi.org/10.1186/s43042-022-00249-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s43042-022-00249-1

Keywords

  • OPRM1 gene
  • Addiction
  • Gnomad-exomes database
  • Smoking
  • Drug
  • Alcohol