Introduction

Polysubstance abuse is common in subjects with heroin dependence, and nicotine is reported to be the most prevalent substance. In all, 77–93% patients under methadone maintenance treatment (MMT) were reported to smoke cigarettes.1, 2, 3, 4 It has been shown that tobacco consumption is positively correlated with concurrent administration of mu-opioid receptor (MOR) agonists, heroin, methadone and a MOR partial agonist buprenorphine.5, 6, 7 In addition, a previous study indicated that an increase in the dose of methadone could be associated with a stronger craving for nicotine in methadone maintenance patients.8 These data suggest that cigarette smoking may have an important role in the treatment responses to methadone.

The mechanisms underlying the high co-occurrence of opioid and nicotine dependence are not clear. MORs may be involved because methadone is a full μ-opioid receptor agonist.9 Several studies have reported the associations between smoking and opioid receptors.10, 11, 12, 13, 14, 15 For example, Li et al.16 reported that the prevalence of cigarette smoking is significantly increased in heroin-dependent patients. However, these studies were primarily based on self-report. Recall bias from self-report is a systematic bias, which often occurs when the answer of a question is based on a subject’s memory. To avoid recall bias, it is important to find a reliable biomarker for nicotine exposure.17 Cotinine is a metabolite derived from the 5′-hydroxylation metabolic pathway of nicotine18 and has been reported by the Society for Research on Nicotine and Tobacco Subcommittee on Biochemical Verification as a reliable biomarker in estimating an average nicotine exposure over an extended period of time.17 Plasma cotinine concentration offers a window of 5–7 days for detection of nicotine exposure. Thus, we used plasma cotinine concentration in this study in an attempt to estimate the severity of cigarette smoking more accurately in MMT patients.

MORs has been reported to be crucial to several biological functions, for instance, reward, analgesia and stress responses,19, 20 as well as the development of addiction,21 including nicotine dependence.22, 23, 24, 25 MOR mRNA and protein in brain regions have been reported to be upregulated by nicotine. This process may stimulate endogenous opioid release and subsequently activate the MOR.26, 27, 28 The human gene encoding the MOR, OPRM1, is located at the chromosome 6q24-q25 region. MOR is broadly expressed throughout the brain.29 Several single-nucleotide polymorphisms (SNPs) in OPRM1 gene have been identified to be associated with a range of substance dependence. The SNP rs1799971 is one of the most studied polymorphisms in the gene. It has been reported to be related to the risk of addictions30 and different types of pain perception.31, 32, 33 This A-to-G SNP is a non-synonymous polymorphism, which changes the amino acid from asparagine to aspartic acid (Asn40Asp) at a glycosylation site in the extracellular terminus of OPRM1.34 In our previous study, we found that patients with the G allele required higher a methadone dose than those with the A allele.35 Furthermore, rs1799971 has also been reported to be significantly associated with long-term smoking cessation in both males and females,36 with nicotine reinforcement in women, and with the brain μ-opioid receptor binding potential in smokers.11, 15 However, the results are not consistent. For example, Perkins et al.13 reported that rs1799971 was associated with smoking reward, but Zhang et al.10 addressed that rs1799971 was not associated with smoking initiation or nicotine dependence. Of note, none of these studies used nicotine or its metabolite concentration to measure the severity of cigarette smoking. Thus, this study was aimed to test the hypothesis that the genetic polymorphisms in the OPRM1 are associated with severity of smoking by direct measure of the cotinine concentration in a Taiwanese MMT cohort.

Subjects and methods

Subjects

This study was approved by the institutional review boards of the National Health Research Institutes (Zhunan, Taiwan) and the six participating hospitals. Written informed consent was obtained from all participants. The project has also been registered with the National Institutes of Health Clinical Trial (http://www.clinicaltrial.gov/ct/show/NCT01059747). A total of 366 subjects with heroin dependence undergoing MMT as outpatients were recruited. Briefly, the inclusion criteria were an age of 18 or above, undergoing MMT for at least 3 months with regular attendance for the past 7 days, and a methadone dosage adjustment for no >10 mg in the past 7 days. Exclusion criteria were comorbidity with physical and mental disorders that require immediate treatment or pregnancy.

Clinical assessments

Demographics, clinical characteristics and methadone treatment courses, including the dose and treatment duration, and the treatment adherence over the previous week, were obtained from the medical records. Information about other medications in the previous week was obtained from medical records or the subjects’ reports. Interviewer-administered assessments, including treatment outcomes profile37 for the amount and frequency of alcohol and other illicit substance use in the past 28 days, clinical opioid withdrawal scale for the severity of 11 opioid withdrawal symptoms38 were conducted before methadone was administered.

Methadone-related adverse events were assessed by research nurses using treatment emergent symptoms scale.39 The treatment emergent symptoms scale was composed of 43 treatment emergent symptoms. If the symptom occurred only after the initiation of MMT, it was counted as adverse event related to methadone. Severity of each symptom was rated on three-point Likert scale ranging from mild, moderate to severe. In this study, only the adverse events with a frequency >15% were included for further analysis.

Urine drug test

Urine specimens were collected before administration of methadone on the study day. The morphine levels were assayed via a kinetic interaction of microparticles method on an Integra 800 device (Roche Diagnostics, Basel, Switzerland). Urine morphine level >300 ng ml−1 was considered positive. The coefficients of variation of the morphine standards for positive and negative controls were 5.7% and 3.8%, respectively. In this study, the urine morphine test was used as a surrogate measurement for the methadone treatment outcome.

Plasma cotinine assay

The level of nicotine metabolite cotinine in plasma was measured by the cotinine enzyme-linked immunosorbent assay kit (Neogen, Lansing, MI, USA). A total of 20 μl of plasma sample or different concentrations of cotinine standards were added along with 100 μl of cotinine enzyme conjugate into the well of a plate coated with cotinine antibody for competitive immunoassay. The mixture was incubated at room temperature on a plate shaker for 30 min. In all, 300 μl wash buffer was added into each well after removing the mixture. In total, 150 μl substrate K-blue was then immediately added into each well of the plate and the plate was shaken for 15 min. In all, 150 μl stop solution was added into each well to stop the immunological reaction. The optical density was measured by a SpectraMax M2e microplate reader (Molecular Devices, Sunnyvale, CA, USA) at 450 nm wavelength. Patient plasma cotinine level was extrapolated from the inversely logarithmic linear regression curve built by the cotinine standards. The intra-plate and inter-plate coefficients of variation were approximately 1.4−4.3% and 8.4−11.6%, respectively.

OPRM1 SNP selection and genotyping

The OPRM1 SNPs were selected according to the literature reports,40, 41, 42 a minor allele frequency above 0.1 on the HapMap of Chinese ethnic group (http://hapmap.ncbi.nlm.nih.gov/index.html.en), and the functions predicted by the bioinformatics FastSNP.43 Fifteen SNPs were selected from this process for genotyping.

Genomic DNA was extracted from the buffy coat of 6 ml whole blood lymphocyte pellets using the Puregene Blood kit C (QIAGEN Sciences, Germantown, MD, USA), and was used for genotyping for all selected 15 SNPs on OPRM1. The genotypes of these 15 SNPs were identified using matrix-assisted laser desorption/ionization-time of flight mass spectrometry.44 Primers and probes flanking the SNPs were designed using SpectroDESIGNER software (Sequenom, San Diego, CA, USA). DNA fragments (100–300 bp) encompassing each SNP site were amplified by PCR (GeneAmp 9700 thermocycler, Applied Biosystems, Foster City, CA, USA) in accordance with the manufacturer’s instructions.

After removal of the un-incorporated dNTPs and inactivation with the shrimp alkaline phosphatase from the PCR reaction, primer extension was performed via the addition of the appropriate probe, Thermo Sequenase (Amersham Pharmacia, Piscataway, NJ, USA) and a dNTP mixture. The reaction conditions were 45 cycles of denaturation at 94 °C for 5 s, annealing at 56 °C for 5 s and extension at 72 °C for 5 s. The various extension products were differentiated by matrix-assisted laser desorption/ionization-time of flight analysis. This genotyping method has been applied in a broad variety of clinical applications because of the accuracy of SNP detection, sufficient sensitivity to score SNPs from small amounts of template, flexibility of the procedure and cost-effectiveness.45 DNA sample of a subject were genotyped twice to evaluate the consistency of the results. The call rate and consistency were 100% for all 15 SNPs.

Quantitative real-time polymerase chain reactions for OPRM1

Human brain total RNAs in 10 brain regions were purchased from Clontech (Palo Alto, CA, USA). The brain regions included caudate nucleus, cerebellum, cerebral cortex, frontal lobe, hippocampus, insula, medulla oblongata, nucleus accumbens, substantial nigra and the temporal lobe. Total RNAs of these regions were converted to complementary DNA with random hexamers of Fermentas (Hanover, MD, USA).

mRNA level of OPRM1 was measured by the TaqMan Gene Expression real-time PCR assay (Hs01053957_m1) purchased from Applied Biosystems. In all, 200 ng of complementary DNA was quantified in duplicates at OPRM1 probe with TATA-box-binding protein (TBP; Hs00920497_m1) as internal control probe. Real-time PCR amplification was conducted on a StepOnePlus Real-Time PCR System (Applied Biosystems). Gene expression was quantified relative to TBP expression using StepOne Software v2.1 (Applied Biosystems) and the relative quantification method. The relative expression level of OPRM1 compared with that of TBP was defined as −ΔCT=−(CTOPRM1−CTTBP). The OPRM1 mRNA/TBP mRNA ratio was calculated from 2−ΔCT × K, in which K is a constant.

Statistical analyses

All statistical analyses were conducted using SAS software, version 9.1 (SAS Institute, Cary, NC, USA). The demographics and plasma methadone concentrations were analyzed using a non-parametric Wilcoxon two-sample test or χ2 test between the treatment responders, who were defined as negative for the urine morphine test, versus the non-responders. The Spearman correlation coefficient was used to test the associations between the plasma cotinine concentration and clinical characteristics. Association analyses between SNPs in OPRM1 (genotype or allele type) and plasma cotinine concentration were calculated using general linear model (GLM) with the GLM procedure. In addition, the false discovery rate (FDR) with the MULTTEST procedure was used to correct for multiple comparisons46 including multiple genotype models correction. A dominant model was defined when the genotypes with the major allele were grouped to compare with the genotypes without the major allele. Conversely, a recessive model was defined when the genotypes with the minor allele were grouped for comparison. The Hardy–Weinberg equilibrium tests and haplotype block association analyses were performed using HAPLOVIEW version 4.2.47 A haplotype block was constructed according to 95% confidence bounds on D prime (D′). GENMOD procedure was used to test the association between haplotypes and plasma cotinine concentrations, and to calculate global P-values. Power analyses were calculated by GLMPOWER procedure under the assumption of independent observation, normality in the distribution of residuals, and homogeneity of variance. The statistical significant level was designated with P-values of <0.05.

Results

Clinical characteristics and methadone treatment outcome

A total of 366 Han Chinese patients on MMT (297 males and 69 females) were recruited. The average age was 38.17 years and the average body mass index was 23.58 kg m–2. In all, 364 out of 366 subjects (99.5%) on MMT smoked cigarettes. The average plasma concentration of cotinine was 397.1±189.2 ng ml−1 (Table 1). Methadone treatment responders were defined as MMT patients who were tested negative in the urine morphine test, whereas the non-responders were tested positive in the urine morphine test. Responders had a lower plasma concentration of cotinine than the non-responders (368.1±171.2 ng ml−1 vs 427.1±202.0 ng ml−1, Wilcoxon two-sample test P=0.005), but a higher plasma concentration-to-dose ratio of both R- and S-methadone than the non-responders.

Table 1 Demographics and clinical characteristics of methadone maintenance subjects (N=366)
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We found that the plasma cotinine concentration was significantly and positively correlated with age (r2=0.12, P=0.025), S-methadone (r2=0.13, P=0.013), S-2-ethylidene-1,5-dimethyl-3,3-diphenyl-pyrrolidine (S-EDDP; r2=0.12, P=0.023), (R+S)-methadone (r2=0.11, P=0.042) and (R+S)-EDDP (r2=0.11, P=0.037).48 It also showed a significantly negative correlation with the total clinical opioid withdrawal scale score (r2=−0.11, P=0.036), tremor (r2=−0.10, P=0.049), malaise (r2=−0.44, P=0.021) and weight loss (r2=−0.45, P=0.048; Supplementary Table 1).

Details of this study cohort, including demographics, MMT duration, methadone daily dose, plasma concentrations of methadone and its metabolites, the methadone treatment response, and its side effects, were reported in our previous report.35

Single locus and haplotype of OPRM1

All 15 selected SNPs were spanning for 63 195 base pairs (bps) across the OPRM1 genetic region with an average distance of 4213 bps between two selected SNPs (Supplementary Table 2). The locations of these selected SNPs include the promoter, the exon and the intron. Six SNPs are tag SNPs and seven other SNPs are intronic enhancers in those selected 15 SNPs. All these SNPs were in Hardy–Weinberg equilibrium distribution with minor allele frequencies >0.059. A single haplotype block composed of the 14 SNPs of OPRM1 from rs1074287 (promoter) to rs563649 (intron 1; Ref. 35) was created using the default algorithm15 of HAPLOVIEW.47

OPRM1 is associated with plasma concentration of cotinine

The plasma concentration of cotinine was significantly associated with those selected SNPs of OPRM1 using additive model of analyses in allele types (P<0.03 after adjusted with age, gender and body mass index; Table 2), except rs499796. After controlled for multiple testing by the FDR, the results remained statistically significant for the allele types (FDR⩽0.049), except rs2075572. Carriers with the allele type of rs1074287 (G), rs6912029 (T), rs1799971 (A), rs12209447 (T), rs510769 (A), rs3798676 (T), rs553202 (T), rs7748401 (G), rs495491 (C), rs10457090 (G), rs589046 (A), rs3778152 (G), rs563649 (A) and rs2075572 (G) had higher plasma concentrations of cotinine than their counter allele type carriers. All these SNPs were located from promoter to intron 2 regions in OPRM1.

Table 2 Association analysis of the OPRM1 and the cotinine concentration using the genotype recessive model and the allelic additive model
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Using recessive model of analyses, the genotypes of all OPRM1 SNPs were significantly associated with the plasma concentrations of cotinine (P<0.038 after adjusted with age, gender and body mass index), except rs499796 and rs2075572. After multiple model correction, the recessive model showed a higher significant level than the additive model. However, there were no statistically significant associations between these SNPs and the plasma cotinine concentrations using dominant model of analyses (P⩾0.059 after adjusted with age, gender and body mass index; data not shown).

Analysis of OPRM1 haplotype and plasma concentrations of cotinine

Although the tetradeca-nucleotide single haplotype block (rs1074287-rs6912029-rs1799971- rs12209447-rs510769-rs3798676-rs553202-rs499796-rs7748401-rs495491-rs10457090-rs589046-rs3778152-rs563649) did not show significant associations with the plasma concentrations of cotinine (global P=0.241; data not shown), subjects with the 5′-AGGCGCCTTTAGAG-3′ haplotype were found to have a significantly lower plasma cotinine concentration than other haplotypes (P=0.013) (Table 3). Furthermore, higher plasma cotinine concentrations were shown in those with the 5′-GTATATCTGCGAGA-3′ haplotype (P=0.010). However, it did not reach a statistical significance after controlled by the FDR.

Table 3 Association between individual haplotypes for OPRM1 block and the cotinine concentration
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OPRM1 expressions in different areas of the human brain

Levels of the total OPRM1 mRNA expression measured by quantitative real-time polymerase chain reaction were higher in the cerebellum and nucleus accumbens areas (Supplementary Figure 1).

Discussion

In this study, we have demonstrated the first time that the OPRM1 genetic polymorphisms are strongly associated with the severity of co-occurring nicotine dependence by direct measurement of plasma cotinine concentrations in a MMT cohort. Although several studies have suggested that OPRM1 may be associated with the propensity of tobacco smoking and nicotine dependence,10, 11, 12, 13, 14, 15 most of these reports did not use nicotine or its metabolite as a marker. Fourteen SNPs selected from the promoter to intron 2 of OPRM1 of both genotypes recessive model and allele types showed significant associations with the plasma concentrations of cotinine. The trideca-nucleotide haplotype block identified in this study was similar to the haplotype block reported in a study on European Americans,49 and it showed a borderline significant association with the plasma concentrations of cotinine. However, it did not reach a statistical significance after adjustment for multiple testing. This suggested that SNP may be a better predictor for the severity of co-occurring nicotine dependence than haplotype in OPRM1 gene.

Our results suggested that cigarette smoking may be a mechanism for patients to cope with the low efficacy of methadone treatment: when using urine morphine test as a surrogate outcome measure for subgrouping the MMT patients into the treatment responders and non-responders, the non-responders had a higher plasma cotinine concentration than the responders. As the responders had higher plasma levels of both S- and R-methadone concentration-to-dose ratios than the non-responders, it suggested that the cigarette smoking may be a physiological compensation for the low efficacy of methadone treatment. Similarly, Fonseca et al.50 have reported the non-responders smoked more cigarettes per day than responders in a Spanish MMT program.

Cigarette smoking is highly prevalent (77–93%) in MMT patients.1, 2, 3, 4 A previous study has shown that an increase in the dose of methadone could cause more craving for nicotine.8 In this study, our analyses of the coefficients of variation for the plasma cotinine concentrations were similar to those reported in other studies.51 We found that plasma cotinine concentration may reflect the metabolism of methadone as positive correlations were found between plasma cotinine concentration and the plasma S-methadone, S-EDDP, total (R+S)-methadone and total (R+S)-EDDP concentrations. Furthermore, the plasma cotinine concentration was negatively correlated with the total opioid withdrawal score rated by clinical opioid withdrawal scale, the tremor score, the malaise score and the weight loss score. The higher the plasma cotinine concentration, the lower the withdrawal symptoms and less side effect symptoms were found in the MMT patients. These results support the finding that cigarette smoking may enhance the effect of methadone on the decrease in the opioid withdrawal symptom scores.52 This may in part explain a high cigarette smoking rate in patients undergoing MMT.

rs1799971, located in exon 1, is the most investigated SNP in the OPRM1 in which an adenine to guanine substitution (A118G) causes an amino-acid change, which in turn may reduce the MOR binding potentials,11 and alter the downstream signaling.30 The minor allele frequencies of rs1799971 are 15–30% in European descendants, 40–50% in Asian ancestry and 1–3% in African American and Hispanic populations, respectively.53, 54, 55 In this study, we found that the G allele carrier of rs1799971 had a lower plasma cotinine concentration than the AA homozygote. This result suggested that the G allele in rs1799971 had a protective effect against cigarette smoking in patients under MMT.

In this study, the OPRM1 SNPs that were significantly associated with plasma cotinine concentrations were also significantly associated with change in libido side effect in our previous report.35 Minor allele carriers, who had higher change in libido scores, had higher plasma cotinine concentration than their counter allele in our MMT cohort. Without the involvement of OPRM1 genetic polymorphism, our database did not show a directly significant association between the change in libido score and the plasma cotinine concentration (Kruskal–Wallis test P=0.701; data not shown). It has been reported that an intermediate dose of isolated nicotine would significantly reduce erectile response in healthy, young, nonsmoking men.56 Impairment of sexual performance were commonly reported by men undergoing MMT.57 Previous studies suggested that nicotine may be the primary pharmacological agent responsible for genital hemodynamic disruption by acting on the nervous system centrally or peripherally. Our results provided further evidence that the OPRM1 gene may be involved in nicotine-induced pathological process in change of libido.

We also found that those OPRM1 SNPs that were significantly associated with the plasma cotinine concentrations in recessive model were also significantly associated with insomnia side effect in recessive model in our previous report,35 except SNPs rs1799971 and rs553202. Insomnia is a relatively uncommon side effect in heroin-dependent patients under methadone treatment.58, 59 In this study, there were 18% MMT patients that reported to have sleep disturbance. Our results indicated that the genotype associated with lower insomnia scores, which indicated a better sleep quality, were also associated with higher plasma cotinine concentrations in our MMT cohort. This result was contradicted to the finding in healthy adolescents and adults who had been reported with sleep disturbances after tobacco exposure.60, 61, 62, 63, 64 There was no significant correlations between the insomnia score and the plasma cotinine concentration (Kruskal–Wallis test P=0.173; data not shown) in the cohort unless the involvement of OPRM1 genetic polymorphism. We therefore consider that the plasma cotinine concentration may be helpful in reducing the methadone-induced insomnia side effect through OPRM1 receptor.

Neuroimaging studies have been reported that a few brain regions of activation were associated with cigarette craving when subjects were presented with some smoking-related cues.65 For example, left anterior cingulate cortex, medial prefrontal cortex, left middle cingulate gyrus, bilateral posterior cingulate gyrus and bilateral precuneus, were areas associated with attention, decision-making and episodic memory, and also associated with cigarette craving in nicotine-dependent subjects.66 Using quantitative real-time PCR, we also found that OPRM1 expressed across all areas in the brain. The expression levels were relatively higher in the cerebellum and the nucleus accumbens, the regions that have been reported to be associated with substance abuse.67

Nevertheless, some limitations of this study should be considered. First, this study did not examine the metabolic influence of the genetic polymorphisms of the genes encoding liver cytochrome P-450 isozymes on nicotine and cotinine. Second, the majority of participants were male. Also, this study was a cross-sectional design. A longitudinal study would warrant in order to clarify any cause and effect relation. In addition, other genetic factors, such as genetic variants in other opioid receptor genes would, warrant further studies.

Conclusions

In summary, we found that several OPRM1 genetic variants were significantly associated with the plasma concentrations of cotinine in MMT patients when using recessive model for genotypes and additive model for allele types of analyses. Methadone treatment non-responders had a higher plasma cotinine level, and lower plasma concentration-to-dose ratio of both R- and S-methadone than the responders. It appears that the SNPs of OPRM1 are better indicators for heavy smoking than haplotype combinations.