Substantial attributable risk related to a functional mu-opioid receptor gene polymorphism in association with heroin addiction in central Sweden

SIR – The addictions are complex diseases whose onset, persistence, and treatment are influenced by interactions between genetic, environmental, and pharmacological factors.¹ A study of 3372 twin pairs found that genetic, shared environmental, and nonshared environmental factors similarly influence the development of drug abuse and dependence.² The authors also found that 54% of the total and 38% of the unique variance in heroin abuse were attributableto genetic factors.²

Mu-opioid receptor (OPRM1) gene polymorphisms are logical candidates for association studies in the addictive diseases.³ The endogenous opioid system is central to the function and modulation of physiological systems affected by all drugs of abuse.¹ Quantitative trait locus studies and studies in OPRM1 knockout mice have confirmed the importance of this receptor to the rewarding effects of opiates and other drugs of abuse.^4–6

Two single-nucleotide polymorphisms (SNP) within the coding region (C17 T and A118G) of exon 1 of the OPRM1 gene encode amino-acid substitutions and have a high frequency in specific populations (range 2–48%).³ Using in vitro cellular assays, we demonstrated that receptors encoded by the variant 118G allele of the A118G SNP have increased affinity for the endogenous mu-opioid ligand β-endorphin and increased activation of G protein-activated inwardly rectifying potassium channels following binding by β-endorphin.⁷ The influence of this SNP on human physiology has also been demonstrated in two studies of healthy volunteers showing increased hypothalamic–pituitary–adrenal axis response to the opiate antagonist naloxone in subjects with an 118G allele compared to subjects with only 118A alleles.^8,9 Another report also provides evidence that alcohol-dependent subjects with an 118G allele return to heavy drinking later following treatment with the opiate antagonist naltrexone than do similarly treated alcoholics with the prototype receptor.¹⁰

Owing to its demonstrated effect on cellular and human physiology, we again selected the A118G SNP for analysis in the current study. To reduce the potential effect of population admixture, we studied a population of primarily Swedish subjects from Huddinge-Stockholm, Sweden.

The participating institutions’ human subjects ethics committees approved this study and all subjects provided written informed consent for genetic studies. In all, 170 normal volunteer subjects with a mean age of 36.5 years (SD±8.3; 52% female) were recruited as population-based controls for a large general health study. Normal volunteer subjects with a lifetime diagnosis of any psychotic disorder, drug or alcohol abuse, or drug or alcohol dependence were excluded from this study. In all, 139 heroin-addicted subjects with a mean age of 45.6 years (SD±15.9; 23% female) were recruited from a chemical dependency unit where they were seeking detoxification for heroin dependence. DSM-IV criteria for opiate dependence was determined through a physician interview and the DSM-IV Checklist. Some opiate-dependent subjects met criteria for other axis I diagnoses such as alcohol abuse or dependence, and also major depression, anxiety, and panic disorder although the latter three diagnoses were generally secondary to substance dependence and not primary diagnoses.

Genomic DNA was isolated from peripheral blood lymphocytes and amplified by PCR using primers designed to amplify the complete coding region of exon 1 of the OPRM1 gene. PCR products were purified and sequenced at The Rockefeller University DNA Sequencing Center. Genotypes were determined by two independent assessors (GB and KSL) who were blind to the diagnostic data.

The overall frequency of each genotype and allele was determined. The odds ratio (OR) was calculated and the Mantel–Haenszel χ² test performed. Attributable risks were also computed, that is, the estimated proportion of cases in the population who are affected due to the given at-risk genotype(s). Genotype and allele distribution did not vary between genders so gender stratification was not performed. No subjects with the C17 T polymorphism were identified.

Distribution of the 118G allele was in Hardy–Weinberg equilibrium in all subgroups with an overall allelic frequency of 11.0%. A significantly greater OR for heroin addiction for subjects with an 118G allele (OR = 2.31, ${\chi }_{(1)}^2$ = 10.268, P = 0.0014) was found. Also, analysis by genotype revealed a significantly greater OR for genotypes containing an 118G allele and heroin addiction (autosomal dominant mode of inheritance) (OR = 2.86, ${\chi }_{(1)}^2$ 13.403, P = 0.00025). The attributable risk due to genotypes with a G allele was 18.0 (95% CI 8.0–28.0%) (Table 1).

Table 1.

Genotype and allelic distribution of the A118G polymorphism in all control and opiate-dependent subjects; subset data from Swedish subjects with two Swedish parents

	All subjects		Swedish with both parents Swedish
	Controls (n = 170)	Opiate dependent (n = 139)	Controls (n = 120)	Opiate dependent (n = 67)
Genotype
A/A	147 (0.865)	98 (0.705)	104 (0.867)	46 (0.687)
A/G	21 (0.123)	39 (0.281)	15 (0.125)	19 (0.283)
G/G	2 (0.012)	2 (0.014)	1 (0.008)	2 (0.030)
	OR=2.86, ${\chi }_{(1)}^2$ = 13.403 (P=0.00025)a		OR=2.97, ${\chi }_{(1)}^2$ = 8.740 (P=0.0031)a
Allele
A	315 (0.926)	235 (0.845)	223 (0.879)	111 (0.828)
G	25 (0.074)	43 (0.155)	17 (0.121)	23 (0.172)
	OR=2.31, ${\chi }_{(1)}^2$ = 10.268 (P=0.0014)		OR=2.72, ${\chi }_{(1)}^2$ = 9.125 (P=0.0025)
Attributable Risk Assessment (assumes autosomal dominant model)
Genotype
A/A	147 (0.865)	98 (0.705)	104 (0.867)	46 (0.687)
A/G, G/G	23 (0.135)	41 (0.295)	16 (0.133)	21 (0.313)
	AR 0.18, 95% CI=(0.08, 0.28)a		AR 0.21, 95% CI=(0.06, 0.34)a

Data are numbers (frequency).

OR, odds ratio; AR, attributable risk.

^aGenotype analysis assumes autosomal dominant model.

To minimize concerns about population admixture, a subgroup analysis was performed in subjects identifying themselves and both parents as Swedish (67 heroin addicts and 120 controls). Although the sample size is smaller, the association between the 118G allele and heroin addiction persists (OR = 2.72, ${\chi }_{(1)}^2$ = 9.125, P = 0.0025) as does the association by genotype (OR = 2.97, ${\chi }_{(1)}^2$ = 8.740, P = 0.0031). In this subgroup, the attributable risk due to genotypes with a G allele was 21.0 (95% CI 6.0–34.0%) (Table 1).

The results of our study provide evidence for association of the 118G allele in exon 1 of the OPRM1 gene contributing to increased OR for heroin addiction. The results also indicate that up to 21.0% of the attributable risk of heroin addiction is mediated by the 118G allele.

To date, studies in Caucasian populations have not found an association between opiate dependence and the A118G SNP. A possible explanation for these results may lie in the diversity of allele frequency across and within populations. This study was in subjects from central Sweden, a group with little admixture over the past several hundred years. In this report, we controlled for allelic frequency differences in populations by performing a subgroup analysis of Swedish subjects with two Swedish parents. In conclusion, the current study found a significant association between the 118G allele of this functional polymorphism in the OPRM1 gene and heroin addiction in central Sweden.