Association of COMT Gene Polymorphisms with Response to Methadone Maintenance Treatment Among Chinese Opioid-Dependent Patients

Abstract

Aim:

To explore the association of the COMT gene polymorphisms (rs4680, rs737866, and rs933271) with the response to methadone maintenance treatment (MMT) among Chinese opioid-dependent patients.

Methods:

A total of 820 patients who were receiving MMT from Chinese clinics were recruited. Questionnaires were used to collect patient information, including sociodemographics, history of drug use, and stable methadone dosages. Three polymorphisms of COMT, rs4680, rs737866, and rs933271, were selected and genotyped using the Sequenom MassARRAY platform.

Results:

After adjusting for related factors including age, marital status, and methadone dosage, the genotype TC at rs933271 was demonstrated as the dominant difference between the MMT responsive group and nonresponsive group (p = 0.02, odds ratios [OR]: 1.57). In the dominant model of inheritance, the individuals carrying the TC or CC genotypes at rs933271 were more likely to respond to MMT than patients with the genotype TT (p = 0.02, OR: 1.53). No significant associations were observed between any of the allelic or genotypic variants of the rs4680 and rs737866 loci, and the response to MMT in this Chinese population. Patients with the haplotype A-T-A (rs737866-rs933271-rs4680) were more frequent in the nonresponsive group than in the responsive group (p < 0.05).

Conclusion:

COMT genetic variability is associated with the response to MMT.

Introduction

Opioid dependence is a type of chronic recurrent encephalopathy that has a significant influence on the patients' physical and mental health of patients. Obligatory drug treatment and drug (methadone or buprenorphine) maintenance treatment have been internationally adopted as treatment with high evidence of retention and reduction in mortality and illicit opioid use. Methadone maintenance treatment (MMT) has been administered in developed countries for >50 years (Kreek and Vocci, 2002). In China, the pilot study of MMT clinics was initiated in 2003. As of June 31, 2016, there are 789 community MMT clinics nationwide, and the annual retention rate of patients receiving treatment reached 80.1% (NCAIDS et al., 2016).

Methadone is a synthetic μ-opioid receptor agonist that can reduce withdrawal symptoms and restrain drug-seeking behavior (NCAIDS et al., 2016). However, the therapeutic response to MMT in patients is not ideal. High dropout rate, high relapse rate, and considerable individual variability in outcomes have been found (Bell et al., 2006; Ren et al., 2013).

Previous studies have shown that age, patient satisfaction, methadone dosage, and other environmental factors may influence the outcomes of MMT (Villafranca et al., 2006; Haile et al., 2008). Some researchers found that individual variation could also alter the response to therapy by affecting the metabolic processing of methadone or its signaling pathways. For instance, genetic polymorphisms of methadone metabolic enzymes (CYP450 isoenzymes such as CYP2B6, CYP2C19, CYP3A4, and CYP2D6) have been shown to be responsible for the observed differences in methadone plasma levels, dose requirements of methadone, and the efficacy and side effects of methadone treatment (Crettol et al., 2005; Kringen et al., 2017; Ahmad et al., 2018);

P-glycoprotein, encoded by the ABCB1 gene, is an ATP-dependent membrane protein that mediates the transport of drugs into the cell, thereby affecting the absorption and distribution of various drugs including methadone (Crettol et al., 2007; Somogyi et al., 2014). Previous studies showed that ABCB1 genetic polymorphism may impact methadone dose requirements and plasma concentration of methadone (Levran et al., 2008; Barratt et al., 2012; Zahari et al., 2016).

Another gene (OPRM1), which was assumed to be associated with the efficacy of MMT, has also been widely studied, since the μ-opioid receptor encoded by this gene is the primary site of action of methadone (Ikeda et al., 2005). A previous study had reported carriers of the A allele of OPRM1 rs562859 tended to have a lower nonresponse rate (Peng et al., 2018). However, this association was not supported by other studies (Crettol et al., 2008).

Catechol-O-methyltransferase (COMT), encoded by the COMT gene, is located on chromosome 22q11.21 and is a vital metabolic enzyme that participates in the metabolism of dopamine. It can catalyze the methylation of the three hydroxyl groups of catecholamine, thus degrading it (Mannisto and Kaakkola, 1999). COMT has greater control over dopaminergic nerve transmission, particularly in brain regions with lower dopamine transporter density such as the prefrontal cortex, which holds >50% of the region's dopamine degraded by COMT (Moron et al., 2002; Yavich et al., 2007).

The reward pathway consisting of dopamine circuits is an essential neurobiological basis of substance addiction. Heroin and other addictive substances elevate dopamine levels in the synaptic cleft through activating the mesolimbic dopaminergic neurons, resulting in reward and drug-seeking behavior (Dackis and O'Brien, 2005). It has been suggested that COMT might affect the addictive behavior and the patient response to MMT through regulating dopamine metabolism. The COMT gene containing several single nucleotide polymorphism (SNP) loci is highly polymorphic, and its protein activity among different individuals is very diverse (Tammimäki and Männistö, 2010).

The COMT gene has been linked to opioid addiction, drug seeking and impulsivity, social cognition, and other psychiatric and substance addiction disorders (Zhu et al., 2001; DeMichele-Sweet and Sweet, 2010; Lin et al., 2013; Kumar and Rai, 2020). However, the role of COMT gene polymorphism in MMT remains controversial and needs further verification. One study showed that the dropout rate of GG genotype in rs4680 carriers (16.7%) was significantly higher than that of AA genotype carriers (6.3%) during MMT (Crist et al., 2018). Another study failed to find any association between COMT polymorphisms and methadone maintenance dose (Mouly et al., 2015).

The aim of this study is to explore the relationship between the response to MMT and genetic polymorphisms of COMT (rs4680, rs737866, and rs933271) by comparing the distribution of alleles, genotypes, and haplotypes of the COMT gene candidate SNPs among different treatment response groups. The results of this study demonstrate that COMT plays a role in individualized methadone treatment.

Materials and Methods

Participants

For this study, 820 subjects were selected and recruited from six MMT clinics in Hunan Province (MMT Clinic of Tianxin District; Changsha Voluntary Detoxification Center; Yiyang Fifth People's Hospital; MMT Clinic of Shaoyang; MMT Clinic of Xupu County; MMT Clinic of Loudi). The individuals had to meet Diagnostic and Statistical Manual of Mental Disorders criteria for opioid dependence.

All of the participants were recruited according to enrollment criteria as follows: participants were enrolled in MMT for the first time, they received MMT for at least 2 months and reached a stable methadone dosage, they were HIV negative, they only used heroin and no other addictive drugs such as cocaine and methamphetamine, and they were of Han Chinese ethnicity. All of them were followed up for 6 months. Exclusion criteria were pregnancy, HIV-positive patients, and patients with other mental diseases.

The study protocol was approved by the Institutional Review Board (IRB) of Xiangya School of Public Health, Central South University. Written informed consent was obtained from all participants.

Procedures

The characteristics of participants (including sociodemographic characteristics and history of substance abuse) were collected by self-report. The status of MMT including dosage and withdrawal symptoms was derived from outpatient electronic medical records. Consumption of drugs was confirmed by random weekly urine analysis. All subjects were divided into responder and nonresponder to MMT groups within a 6-month follow-up period according to the following criteria.

Responders met the following criteria: an absence of positive urine analysis, or at most, a one-time positive urine analysis for opioids during a 6-month follow-up period; nonconsumption of heroin or other types of opioid drugs according to participant self-reports; an absence of withdrawal symptoms; and a stable and regular attendance in the MMT therapeutic program. Nonresponse to MMT was defined according to the following criteria: more than two occurrences of heroin consumption or other opioid drugs based on participant self-reports or by positive urine analyses, a complaint of withdrawal symptoms, or the absence of regular attendance in the MMT therapeutic program.

SNP selection and genotyping

The SNP candidates for the COMT gene (including rs4680, rs737866, and rs933271) were selected based on the dbSNP databases of the NCBI and the International HapMap project. The chosen SNPs met the selection criteria as follows: high heterozygosity (minor allele frequency >0.1) and previous relevant functional reports.

Peripheral blood samples were collected in EDTA-treated tubes and then stored at −80°C until further DNA extraction. Genomic DNA was extracted from the blood sample by a commercial DNA extraction kit (RelaxGene Blood DNA System, Tiangen Biotech [Beijing] Co., Ltd.). The amplification primers for polymerase chain reaction were designed using Assay Design 3.1 software (Sequenom Company). All SNPs were genotyped using the MassARRAY Typer software version 4.0 (Sequenom, Inc., San Diego, CA).

Statistical analysis

Sociodemographic characteristics, history of substance abuse, and the MMT status were described and compared between different treatment response groups. Student's t-test was used for continuous data, and the chi-square test was conducted on classification data to determine the differences in the characteristics of subjects between the responder and nonresponder groups. Logistic regression was used to assess the genetic effect of the SNPs. Odds ratios (OR) and 95% confidence intervals were obtained by multivariate logistic regression. The mentioned analysis was carried out using SPSS software (version 22.0).

Hardy-Weinberg equilibrium tests as well as linkage disequilibrium analyses were performed using SHESIS software. Haplotype analysis was performed with R version 3.4.4 for Windows. For all analyses, a two-sided p-value ≤0.05 was considered as statistically significant.

Results

Characteristics of subjects

Among the 820 patients in this study, the ages ranged from 26 to 67 years with a mean of 44.9 ± 7.9. Six hundred and ten of the subjects were classified as nonresponders (with an average age of 44.5 ± 7.7 years, 491 males and 119 females), and 210 were classified as responders (with an average age of 46.2 ± 8.2 years, 179 males and 31 females). A significant difference in the distribution of the age between responders and nonresponders showed that the average age of the responders was significantly higher than that of the nonresponders (t = 2.79, p = 0.05, Table 1).

Table 1.

Comparison of the General Situation of Individuals Between the Methadone Treatment Nonresponder and Responder Groups

General situation	Nonresponders (n = 610)	Responders (n = 210)	χ²/t	p
Age	44.5 ± 7.7	46.2 ± 8.2	2.79	0.05
Gender			2.43	0.12
Male	491 (85.3)	119 (80.5)
Female	179 (14.7)	31 (19.5)
Marital status			6.06	0.05
Unmarried	219 (36.0)	80 (38.0)
Married	313 (51.4)	91 (43.4)
Divorced/widowed	77 (12.6)	39 (18.6)
Education			1.85	0.60
Primary school and below	66 (10.8)	19 (9.0)
Junior high school	338 (55.4)	110 (52.7)
High school	184 (30.2)	71 (33.6)
College graduate or above	22 (3.6)	10 (4.7)
Living conditions			7.63	0.06
Living with relatives/friends	436 (92.8)	150 (85.7)
Living alone	34 (7.2)	25 (14.3)

In addition, there was a significant association of lower response with married participants (χ² = 6.06, p = 0.05, Table 1). As an essential control factor in this study, the proportion of high-dose methadone in the nonresponder group was lower than that in the responder group (χ² = 13.39, p = 0.01, Table 2). Concerning gender, education, living conditions, age at first drug use, and duration of drug use before MMT, the two groups revealed similar characteristics (Tables 1 and 2).

Table 2.

Comparison of the Drug and Medication Situation of Individuals Between the Methadone Treatment Nonresponder and Responder Groups

Drug/medication situation	Nonresponders (n = 610)	Responders (n = 210)	χ²/t	p
Age of first drug use	26.5 ± 6.9	27.3 ± 7.7	1.17	0.24
Duration of drug use (years)	12.9 ± 6.0	13.5 ± 5.8	−1.20	0.23
Methadone dosage (mg/day)
<60	228 (37.4)	64 (30.3)	13.39	0.01
60-	359 (58.9)	126 (59.7)
≥120	23 (3.7)	20 (10.0)

Hardy-Weinberg equilibrium analysis

No deviation from Hardy-Weinberg equilibrium was observed for the SNPs rs737866, rs933271, and rs4680 in either responders or nonresponders (p > 0.05), which meets the law of genetic equilibrium. This indicated that the research object is derived from the source of random mating populations.

Linkage disequilibrium analysis

Rs737866, rs933271, and rs4680 were in linkage disequilibrium (D′ > 0.6, r² > 0.21); in particular, rs737866 and rs933271 (D′ = 0.96, r² = 0.37) were in near complete linkage.

Association of MMT response with COMT gene polymorphism

The association between genotypes of SNPs and MMT response was tested under the additive, dominant, and recessive models. In the additive inheritance model after adjusting age, marital status, and methadone dosage, the patients with the TC genotype showed better response to MMT than those with the CC genotype (p = 0.02, OR: 1.57). In the dominant model of inheritance, after the adjustment, individuals carrying the C allele at rs933271 had a 1.53-fold chance of being responders as TT genotype carriers (p = 0.02, OR: 1.53).

The SNPs rs737866 and rs4680 had not yet been found to be associated with the efficacy of MMT under the different genetic models (Table 3).

Table 3.

Association Between COMT Gene Polymorphisms and Response to Methadone Maintenance Treatment

	Responders	Nonresponders	OR ^a (95% CI)	p^a
rs737866
Additive
AA	113 (55.1)	298 (49.4)	1.00
GA	80 (39.0)	256 (42.5)	1.31 (0.65-2.64)	0.45
GG	12 (5.9)	49 (8.1)	1.62 (0.81-3.22)	0.17
Dominant
AA	113 (55.1)	298 (49.4)	1.00	0.14
A+GG	91 (44.9)	305 (50.6)	0.79 (0.56-1.08)
Recessive
GA+AA	192 (94.1)	550 (92.0)	1.00	0.25
GG	12 (5.9)	249 (8.0)	0.68 (0.34-1.33)
rs933271
Additive
TT	56 (26.9)	207 (34.4)	1.00
TC	115 (55.3)	301 (49.7)	1.57 (1.07-2.29)	0.02
CC	37 (17.8)	97 (15.9)	1.42 (0.86-2.34)	0.16
Dominant
TT	56 (26.9)	207 (34.4)	1.00	0.02
TC+CC	152 (73.1)	395 (65.6)	1.53 (1.06-2.20)
Recessive
TT+TC	171 (82.2)	506 (84.1)	1.00	0.74
CC	37 (17.8)	96 (15.9)	1.07 (0.70-1.66)
rs4680
Additive
GG	121 (57.6)	334 (54.9)	1.00
GA	76 (36.2)	233 (38.3)	0.95 (0.67-1.34)	0.78
AA	13 (6.2)	41 (6.8)	0.90 (0.46-1.77)	0.76
Dominant
GG	121 (57.9)	331 (54.9)	1.00	0.73
GA+AA	88 (42.1)	272 (45.1)	0.94 (0.68-1.31)
Recessive
GG+GA	196 (93.8)	562 (93.2)	1.00	0.81
AA	13 (6.2)	41 (6.8)	0.92 (0.47-1.78)

Adjustment for age, gender, and methadone dose.

CI, confidence interval; COMT, catechol-O-methyltransferase; OR, odds ratios.

Haplotype analysis

Haplotype-based association analysis was performed for three SNPs in COMT. After elimination of rare haplotypes (<0.03), this study examined six haplotypes. After adjusting age, marital status, and methadone dosage, it was determined that the patients carrying haplotype A-T-A (rs737866-rs933271-rs4680) were prone to being nonresponders to MMT (p = 0.04, Table 4). With the exception of haplotype A-T-A, no COMT haplotype was associated with response to MMT.

Table 4.

Haplotype Analysis of COMT Gene Single Nucleotide Polymorphisms (rs737866-rs933271-rs4680)

Haplotype	Responders (frequency)	Nonresponders (frequency)	Haplotype score	p^a
ATA	0.152	0.192	−1.98	0.04
GTG	0.223	0.266	−1.42	0.16
GTA	0.031	0.025	0.44	0.65
ACA	0.051	0.034	1.27	0.20
ATG	0.141	0.113	1.57	0.12
ACG	0.402	0.367	1.68	0.09
Global score				0.04

Adjustment for age, gender, and methadone dose.

Discussion

Our study suggests that the haplotype A-T-A (rs737866-rs933271-rs4680) carriers were prone to being nonresponder to MMT. Patients carrying the TC or CC genotype at rs933271 had a 1.53- fold chance of being responders to MMT as compared with patients with the TT genotype. In the additive model, the patients who carried the TC genotype had an increased response to MMT as compared with their CC genotype counterparts, indicating that there is an association between the polymorphism of rs933271 and the response to MMT.

Previous studies have reported the association between COMT gene polymorphisms and substance dependence. However, as far as we know, there is little research on the association of COMT gene polymorphisms with MMT response. Rs4680 that encodes either valine or methionine is the best known and most studied functional polymorphism of the COMT gene. The mutation at rs4680 (G>A) contributed to a three- to fourfold decrease in the enzymatic activity of COMT, which results in the reduction of dopamine removal efficiency within the synaptic cleft (Chen et al., 2004).

Christoffersen et al. (2016) found that among opioid addiction patients, the risk of death was lower in COMT rs4680 AA genotype carriers. A follow-up study of 564 heroin addicts in Shanghai found that heroin-dependent patients with the GG genotype at rs4680 were more likely to relapse because it influenced their impulsive personalities (Su et al., 2015). These results were similar to the study reported by Crist et al. (2018). Conversely, we did not find a relationship between rs4680 of the COMT gene and MMT response.

In addition to rs4680, evidence for the role of the rs737866 and rs933271 variants in addiction is similarly mixed. Li's study suggested that the patient with TT genotype had an earlier age of onset of drug use than the CC or TC genotype counterparts, which implies that rs737866 SNP in COMT affects the development of heroin dependence (Li et al., 2012). Levran et al. (2015) found that there was no significant association between rs737866 and cocaine addiction, whereas the CC genotype in rs933271 carriers conferred a higher susceptibility to cocaine dependence than the TC and TT genotype carriers in African Americans.

These results were not consistent with Beuten's study regarding SNP rs933271 in Americans (Beuten et al., 2006). Wang's study (Wang et al., 2011) demonstrated that for the C allele at rs737866 carriers, the risk of being heroin addicts was increased and individuals carrying the C allele in rs933271 had lower heroin addiction susceptibility. Our study showed that the patients carrying rs933271 TC or CC genotype have better outcome of MMT in Chinese population. It is similar to the report by Wang et al.

Evidence for the role of COMT gene mutations in MMT varies. First, ∼40% of heroin addicts have comorbidity of mental disorders, and many studies have shown that COMT is related to impulsive personality, schizophrenia, and other mental disorders. Therefore, COMT may change the drug response of maintenance therapy by affecting the mental state of heroin patients. However, we did not include psychiatric comorbidities in this study, which may lead to different results. Second, there are racial differences associated with the COMT gene polymorphism (Kunugi et al., 1997). This explains why the domestic and foreign research are not consistent in their findings on the relationship between COMT gene polymorphisms and substance dependence.

Since the haplotypes can affect enzyme synthesis through other mechanisms, such as mRNA stability, the effect of haplotypes of COMT gene on enzyme efficiency may be stronger than that of single functional polymorphism (Nackley et al., 2006). A large number of studies demonstrated that haplotypes of the COMT gene SNPs played very important roles in drug addiction. Wang's group discovered that the haplotype C-T-G of rs737866-rs933271-rs1544325 is a risk factor for heroin addiction, whereas the distribution of haplotype T-C-G formed by the same three SNPs in the patient group was low, which was the protective factor of heroin dependence (Wang et al., 2011). In a study of response to tobacco dependence (Berrettini et al., 2007), the Americans who carried haploid G-G (rs737865-rs165599) were found to have a poor response to smoking cessation drugs.

In this study, a haplotype-based association analysis for three SNPs in COMT was performed, and the results showed that the haplotype A-T-A (rs737866-rs933271-rs4680) carriers were more frequently nonresponders to MMT. There are few published studies on COMT haplotypes and MMT, and haplotype analyses include different SNPs. Hence, a direct comparison with our data is difficult. For the next analysis, additional SNPs need to be included to build other haplotype combinations.

Although the findings of this study provide a new perspective for individual methadone treatment, they also tend to predict the sensitivity of individuals to methadone and enable more effective treatment. There were also limitations to the study. First, because heroin addiction is a complex disease that is affected by multiple genes, the interaction between multiple genes may have an impact on the response to methadone treatment. In this study, only the effect of the COMT gene on the response during MMT was considered. Second, this study has not considered the interaction between mental disorders such as impulsive personality and COMT gene. Therefore, further study still needs to consider the interaction of multiple genes and comorbidity of mental disorders, and confirm in a large sample population of multiple centers.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This study was supported by National Natural Science Foundation of China (81202257); Teacher Research Foundation of Central South University (2013JSJJ032); Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry. These foundation organizations had no role in the study design, collection, analysis, or interpretation of the data, writing the article, or the decision to submit the article for publication.

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