1. Introduction 
In Iran, both illegal and legally prescribed opioid consumption is common (Amin-Esmaeili et al., 2016), and it is associated with high levels of opioid use disorder (OUD) and related burden (Amin-Esmaeili et al., 2012; Malekinejad et al., 2015; Rahimi et al., 2020). According to the published reports, Iran has one of the largest populations of opioid users in the world (Rahimi-Movaghar et al., 2018), with an approximation of 2 million individuals suffering from OUD (Noroozi et al., 2022). The most commonly used opioid in Iran is opium, followed by heroin, crack heroin, and prescription opioids, respectively (Amin-Esmaeili et al., 2016). Crack is the street term for a type of illegal narcotic in the Iranian drug market whose main constituent is heroin (Akhgari et al., 2012).
In Iran, methadone maintenance therapy (MMT) is frequently used to treat patients with OUD (Ekhtiari et al., 2020; Momtazi et al., 2015). Methadone, a potent chiral µ-opioid receptor agonist, is also used to treat withdrawal symptoms and manage pain (Ahmad et al., 2018; Bonhomme et al., 2012; Carpenter et al., 2000). The most crucial target associated with the typical effects of opioids, such as morphine and methadone, is the µ-opioid receptor (Wang et al., 2015). Although the receptor is shared, methadone has a lower abuse likelihood, a longer duration of action, and less sedating effects in comparison to morphine or heroin. Based on these characteristics, methadone complications such as tolerance and withdrawal are less described (Davis & Walsh, 2001). These properties make methadone a suitable medication in maintenance programs to treat OUD. However, despite the worldwide clinical indication of methadone, the reactions to this drug may differ considerably between patients, which leads to variations in the amount of methadone consumed from person to person. Thus, a central challenge in MMT is to optimize the medication dosage to have the best efficiency of treatment while facing the fewest side effects (Saloner & Karthikeyan, 2015). Typically, the decision on the dosage of methadone is taken based on factors such as the patient’s clinical situation, reaction to the first dose prescribed, and the guidelines approved for the MMT program in that country (Tenegra & Leebold, 2016). Another critical element that could affect methadone dose requirements in a patient is genetic variability (Packiasabapathy et al., 2020). The data have revealed that variations in genes implicated in the pharmacokinetics and pharmacodynamics of methadone are crucial in defining the dose of the medication (Crettol et al., 2006; Fonseca et al., 2010; Hung et al., 2011).
The ATP-binding cassette subfamily B member-1 (ABCB1) gene is an environment-susceptible gene that codes P-glycoprotein, which is not only associated with multidrug resistance and the efficacy of many drugs but also functions as a drug-transport pump at the blood-brain barrier (Beer et al., 2013; Finch & Pillans, 2014). Several reports have demonstrated that the DNA changes of the ABCB1 gene are linked to the alterations of P-gp function (Fung & Gottesman, 2009; Hoffmeyer et al., 2000; Sia et al., 2010). It has been widely investigated that the single nucleotide polymorphisms (SNPs) of the ABCB1 gene are involved in pain perception. In addition, it has been reported that ABCB1 gene SNPs play a critical role in methadone dosage requirements in patients (Beer et al., 2013; Coller et al., 2006; Levran et al., 2008). Moreover, evidence indicates that the genetic polymorphisms of the gene modulate methadone dose, metabolism, and response (Dennis et al., 2014). 
The OPRM1 gene encodes the mu-opioid receptor, which is extensively expressed in the brain. A famous variation described in this gene is the rs1799971 (A118G) polymorphism in exon 1, leading to an amino acid change from asparagine to aspartate (Taqi et al., 2019). Studies have shown that the A118G polymorphism is involved in OUDs through decreased receptor expression and signaling efficiency (Beer et al., 2013; Wang et al., 2015). OPRM1 is the primary site of action of methadone as an agonist of the mu-opioid receptor, and studies have claimed that the OPRM1 variant A118G could affect the patient’s response to methadone treatment (Barratt et al., 2012). 
Methadone is processed by cytochrome P450 (CYP) through first-pass hepatic metabolism (Ahmad et al., 2018). CYP consists of multiple isomers encoded by P450 genes, including CYP3A4, CYP2B6, CYP2D6, CYP2C19, etc. (Chang et al., 2011). Race and ethnic background have been recognized as significant factors in the prevalence of variant alleles coding for CYP families among the population (Marwa et al., 2014). Previous studies have reported that CYP3A4, CYP2B6, and CYP2C19 are among the most critical CYPs involved in methadone metabolism and dose requirements (Chen, et al., 2011; Crettol et al., 2005; Gadel et al., 2015; Wang et al., 2013). In this setting, there is strong evidence linking the variation in methadone response and dose requirements with CYP polymorphisms (Ahmad et al., 2018; Crettol et al., 2006; Kharasch & Stubbert, 2013; Shinderman et al., 2003).
Based on reports, the challenge of adjusting the methadone dose is the primary reason for failure in the MMT program in the first year of treatment (Lo et al., 2018). In this regard, due to the limited evidence of the effect of gene polymorphisms on methadone treatment outcomes in Iranian populations, we aimed to investigate the relationship between the appropriate methadone dose in patients involved in the MMT program and polymorphisms of genes of CYP3A4 (−392A>G), CYP2C19 (-3402C>T), CYP2B6 (G516T and A785G), OPRM1 (A118G), and ABCB1 (C3435T, G2677T, G2677A, and C1236T) in Mazandaran Province, Iran. 

2. Materials and Methods

Study subjects
In a cross-sectional and multi-centric study, 216 cases out of 521 approaching patients on MMT who were confirmed to have a previous OUD in Mazandaran Province in Iran were defined as eligible to be enrolled in the research. The participants were randomly recruited from six MMT clinics in Mazandaran Province between 2018 and 2020. Although the samples were randomly chosen, each center was assigned a subsample proportional to the total number of patients in the MMT. Methadone was administered to patients in the form of syrup, tablets, or both. According to the previous research (Akbari et al., 2021), the adequate daily oral dose of methadone taken by subjects was classified as low (≤40 mg/d), medium (41-109 mg/d), and high (≥110 mg/d). To be eligible for enrollment in the study, patients had to be male, aged 20 to 45 years old, and have been in the MMT program for at least three months. Participants with a medical history and patients who took antivirals, antipsychotics, or other drugs that interfered with the MMT package were excluded from the study. In addition, patients using medications that interfered with the function of CYPs, such as fluconazole, rifampin, carbamazepine, chloramphenicol, phenobarbital, primidone, cimetidine, phenytoin, and isoniazid, were prevented from enrollment in the study.

Study questionnaire
Before the tests, the opioid dosage adequacy scale (ODAS) questionnaire was filled out to confirm that the patients were receiving stable, adequate doses of methadone (González-Saiz, 2004). The ODAS has been known as a suitable measurement tool to evaluate the dose adequacy of methadone medication in MMT programs. The questionnaire comprises six dimensions and covers the areas of heroin consumption, narcotic blockade, subjective and objective opiate withdrawal symptoms, craving for heroin, and overmedication. Scores are based on the Likert scale and range between 1 (worst) and 5 (best) (Walcher et al., 2016).
In addition, a brief history was taken to determine the patients’ demographics, overall health state, and use of medications. 

Genotyping
The patients’ venous blood samples (4 mL) were collected 24 hours after the last oral methadone consumption. STAR Blood DNA Extraction Kit (Arian Gene Gostar, Iran) was used to isolate DNA from blood samples, and the extracted materials were kept at -20 °C. Polymerase chain reaction (PCR) followed by restriction fragment length polymorphism (RFLP) was performed to determine sample SNPs. Also, the variants were confirmed via the sequencing technique. Following the PCR product validation, the fragment digestion was performed using restriction enzymes, and the results were visualized by electrophoresis. The primer sequences and restriction enzymes used in the study are listed in Table 1.



Statistical analysis
Statistical analysis was performed by the SPSS, software, version 24 (Armonk, NY: IBM Corp.). The chi-square and Fisher exact tests were used to compare the variation frequencies of studied SNPs in three groups of subjects. The results were considered significant with a P<0.05.

3. Results
We included only male subjects in the study to avoid the possible effects of gender on the results. The sample size in this research consisted of 216 male MMT subjects, including 22 individuals with the age range of 20-25(10%), 37 with the age range of 26-30(17%), 52 with the age range of 31-35(24%), 56 with the age range of 36-40(26%), and 49 with the age range of 41-45(23%) years. 
The medication consumption of study subjects was as follows: 82.87% (179 individuals) received methadone in the form of syrup (70.28±28.37 mg/d), 10.65% (23 individuals) in the form of a tablet (70.16±22.12 mg/d), and 6.48% (14 individuals) in both tablet and syrup forms (71.92±20.56 mg/d). Patients received methadone in a mean dosage of 69.63±27.59 mg/d (15-200 mg/kg). The mean length of MMT in patients was 33.7 months. It should be mentioned that the patients enrolled in the study were all in the stable maintenance phase of MMT, and those subjects willing to decrease or discontinue methadone were not included in the study. The classification of patients based on their consumed dose of methadone and the number of subjects in each group is shown in Table 2. 



The frequency and percentage of SNPs in the study subjects have been shown in detail in Table 3. The distribution of genotypes in the study groups was evaluated via chi-square statistics and found to be in Hardy-Weinberg equilibrium for variations A (P=0.73), B1 (P=0.06), C (P=0.06), and H (P=0.65), but not in equilibrium for B2 (P<0.001), D (P<0.001), E (P<0.05), F (P<0.01), and G (P<0.05).



In addition, as shown in Table 4, there were no significant differences (P>0.05) in SNP frequencies of studied genes between three categories of low-, moderate-, and high-dose methadone consumers.



4. Discussion
The primary purpose of this study was to investigate the association of ABCB1, OPRM1, and CYP genetic variations with the methadone dose in MMT patients in Mazandaran, Iran. Based on the findings, we may conclude that there is no association between the studied genetic polymorphisms and the dosage of methadone intake in this context. 
CYP3A4 is extensively involved in methadone metabolism, as are, to a lesser extent, CYP2B6 and CYP2C19 (Kapur et al., 2011). Despite the prominent role of CYP in the metabolism of methadone, limited investigations have been conducted to verify the influence of its genetic variations on MMT results. In this setting, Chen and colleagues have reported that patients carrying the allele type CYP3A4*1B demonstrate higher methadone plasma levels. Furthermore, the increase in methadone plasma level confirms the variations in methadone requirement levels in that studied population (Chen, et al., 2011). Regarding our findings, no significant relationship was detected between the studied genotypes and allele types of CYP3A4, CYP2B6, and CYP2C19 and methadone dose requirement. In agreement with our results, Akbari and colleagues have reported no significant association between the CYP3A4*1B variant and methadone dose in Iranian patients undergoing the MMT program (Akbari et al., 2021).
The µ-opioid receptor is a promising target in opioid consumption. It is claimed that the enantiomers of methadone differentially exert their effects via the activation of µ-opioid receptors (Matsui & Williams, 2010). In this setting, numerous studies have focused on the association of polymorphisms of the µ-opioid receptor (OPRM1) gene with the treatment response of methadone. However, the conflicting results in the literature regarding any correlation between µ polymorphism and MMT response have been challenging. For example, the SNP rs558025 was reported to have an association with MMT outcome (Levran et al., 2013), while the studies done by two other groups of researchers could not show a correlation between µ polymorphism and MMT results or dosage of methadone (Crettol et al., 2008; Hung et al., 2011). In agreement with the latter, our results revealed that the A118G polymorphism of the OPRM1 gene had no significant association with methadone intake. In line with this finding, Beer and colleagues found no significant correlation between A118G genotyping and drug abuse in the European population (Beer et al., 2013).
It is well known that P-gp expression and function are strongly linked to ABCB1 gene variations. Therefore, any functional impairment in P-gp could be a possible consequence of the ABCB1 gene polymorphism (Jiang et al., 2019; Lin, 2020). It is well established that the ABCB1 multi-locus genotype is a critical factor in the outcome of the MMT program and opioid dosage requirements (Beer et al., 2013; Parchure & Peng, 2020). Based on a previous report, the ABCB1 gene SNPs, including rs1045642, rs2032582, and rs1128503, could significantly affect the chance of requiring a higher or lower dose of methadone in people undergoing an MMT program who were previously involved in heroin use disorder (Levran et al., 2008). In line with these findings, further studies have confirmed the prominent role of ABCB1 gene polymorphisms in opioid dosage requirements (Coller et al., 2006; Horvat et al., 2017; Hung et al., 2011; Luo et al., 2017). On the other hand, some other investigations have reported no significant correlation between the methadone dose requirement and ABCB1 polymorphisms (Crettol et al., 2006; Fonseca et al., 2011; Hamraz et al., 2019). In agreement with the latter studies, our results also revealed that the most frequently occurring ABCB1 multi-locus genotype patterns, such as C3435T, G2677A, and C1236T, did not demonstrate any significant linkage to the dose of consumed methadone in 216 MMT patients.

5. Conclusion 
Our results indicated no potential contribution of ABCB1, CYP, and OPRM1 genes variations to the variability in methadone dosage in the MMT population. The results of this study and previous investigations suggest that the effect of genetic polymorphisms on OUD development and maintenance treatment outcomes needs to be further investigated in future studies. In addition, regarding the current study’s findings, it would be informative if correlations between demographic characteristics (e.g. age, education), length of MMT, genetic variables, and dosing groups were evaluated in subsequent reports. Furthermore, it would be helpful to use other categorizations, such as patients receiving very high maintenance doses (above 150 mg/day) with the different groups in the subsequent studies.

Ethical Considerations

Compliance with ethical guidelines
The study protocols were approved by the Ethics Committee of the Tehran University of Medical Sciences, Tehran, Iran (Code: IR.TUMS.REC.1394.172). All the volunteers were fully informed about the study objectives and methods and gave informed written consent. 

Funding
The research was conducted with grant from the Tehran University of Medical Sciences, Tehran, Iran (Grant No.: 94-03-87-30261).

Authors' contributions
Conceptualization and supervision: Nasim Vousooghi, Mohammad Reza Zarrindast, and Anahita Torkaman-Boutorabi; Methodology: Nasim Vousooghi, Emran Mohammad Razaghi, and Mohammad Reza Mahdavi; Data collection and data: Abdollah Golnezhad and Mohammad Reza Mahdavi; Investigation and writing the original draft: Abdollah Golnezhad; Review, editing, funding acquisition and project administration: Nasim Vousooghi.

Conflict of interest
The authors declared no conflict of interest.

Acknowledgments
The authors thank everyone who helped with this study, especially the dear participants. 




References

Ahmad, T., Valentovic, M. A., & Rankin, G. O. (2018). Effects of cytochrome P450 single nucleotide polymorphisms on methadone metabolism and pharmacodynamics. Biochemical Pharmacology, 153, 196–204. [DOI:10.1016/j.bcp.2018.02.020] [PMID] [PMCID] 

Akbari, A., Kheradmand, A., Sina, M., Ahmadiani, A., & Asadi, S. (2021). OPRM1 and CYP3A4 association with methadone dose in Iranian patients undergoing methadone maintenance therapy. Journal of Addictive Diseases, 39(3), 357-362. [DOI:10.1080/10550887.2021.1886566] [PMID] 

Akhgari, M., Jokar, F., Bahmanabadi, L., & Aleagha, A. E. (2012). Street-level heroin seizures in Iran: A survey of components. Journal of Substance Use, 17(4), 348-355. [DOI:10.3109/14659891.2011.592898] 

Amin-Esmaeili, M., Rahimi-Movaghar, A., Haghdoost, A. A., & Mohraz, M. (2012). Evidence of HIV epidemics among non-injecting drug users in Iran: A systematic review. Addiction, 107(11), 1929-1938. [DOI:10.1111/j.1360-0443.2012.03926.x] [PMID] 

Amin-Esmaeili, M., Rahimi-Movaghar, A., Sharifi, V., Hajebi, A., Radgoodarzi, R., & Mojtabai, R., et al. (2016). Epidemiology of illicit drug use disorders in Iran: Prevalence, correlates, comorbidity and service utilization results from the Iranian Mental Health Survey. Addiction, 111(10), 1836-1847. [DOI:10.1111/add.13453] [PMID] 

Barratt, D. T., Coller, J. K., Hallinan, R., Byrne, A., White, J. M., & Foster, D. J., et al. (2012). ABCB1 haplotype and OPRM1 118A > G genotype interaction in methadone maintenance treatment pharmacogenetics. Pharmacogenomics and Personalized Medicine, 5, 53–62. [DOI:10.2147/PGPM.S29272] [PMID] [PMCID] 

Beer, B., Erb, R., Pavlic, M., Ulmer, H., Giacomuzzi, S., & Riemer, Y., et al. (2013). Association of polymorphisms in pharmacogenetic candidate genes (OPRD1, GAL, ABCB1, OPRM1) with opioid dependence in European population: A case-control study. Plos One, 8(9), e75359. [DOI:10.1371/journal.pone.0075359] [PMID] [PMCID] 

Bonhomme, J., Shim, R. S., Gooden, R., Tyus, D., & Rust, G. (2012). Opioid addiction and abuse in primary care practice: A comparison of methadone and buprenorphine as treatment options. Journal of the National Medical Association, 104(7-8), 342-350. [DOI:10.1016/S0027-9684(15)30175-9] [PMID]

Carpenter, K. J., Chapman, V., & Dickenson, A. H. (2000). Neuronal inhibitory effects of methadone are predominantly opioid receptor mediated in the rat spinal cord in vivo. European Journal of Pain, 4(1), 19-26. [DOI:10.1053/eujp.1999.0147] [PMID] 

Chang, Y., Fang, W. B., Lin, S. N., & Moody, D. E. (2011). Stereo-selective metabolism of methadone by human liver microsomes and cDNA-expressed cytochrome P450s: A reconciliation. Basic & Clinical Pharmacology & Toxicology, 108(1), 55-62. [DOI:10.1111/j.1742-7843.2010.00628.x] [PMID] [PMCID] 

Chen, C. H., Wang, S. C., Tsou, H. H., Ho, I. K., Tian, J. N., & Yu, C. J., et al. (2011). Genetic polymorphisms in CYP3A4 are associated with withdrawal symptoms and adverse reactions in methadone maintenance patients. Pharmacogenomics, 12(10), 1397-1406. [DOI:10.2217/pgs.11.103] [PMID] 

Coller, J. K., Barratt, D. T., Dahlen, K., Loennechen, M. H., & Somogyi, A. A. (2006). ABCB1 genetic variability and methadone dosage requirements in opioid-dependent individuals. Clinical Pharmacology & Therapeutics, 80(6), 682-690. [DOI:10.1016/j.clpt.2006.09.011] [PMID] 

Crettol, S., Besson, J., Croquette-Krokar, M., Hämmig, R., Gothuey, I., & Monnat, M., et al. (2008). Association of dopamine and opioid receptor genetic polymorphisms with response to methadone maintenance treatment. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 32(7), 1722–1727. [DOI:10.1016/j.pnpbp.2008.07.009] [PMID] 

Crettol, S., Déglon, J. J., Besson, J., Croquette-Krokkar, M., & Gothuey, I., et al. (2005). Methadone enantiomer plasma levels, CYP2B6, CYP2C19, and CYP2C9 genotypes, and response to treatment. Clinical Pharmacology and Therapeutics, 78(6), 593–604. [DOI:10.1016/j.clpt.2005.08.011] [PMID] 

Crettol, S., Déglon, J. J., Besson, J., Croquette-Krokar, M., Hämmig, R., & Gothuey, I., et al. (2006). ABCB1 and cytochrome P450 genotypes and phenotypes: Influence on methadone plasma levels and response to treatment. Clinical Pharmacology & Therapeutics, 80(6), 668-681. [DOI:10.1016/j.clpt.2006.09.012] [PMID] 

Davis, M. P., & Walsh, D. (2001). Methadone for relief of cancer pain: a review of pharmacokinetics, pharmacodynamics, drug interactions and protocols of administration. Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer, 9(2), 73–83. [DOI:10.1007/s005200000180] [PMID] 

Dennis, B. B., Bawor, M., Thabane, L., Sohani, Z., & Samaan, Z. (2014). Impact of ABCB1 and CYP2B6 genetic polymorphisms on methadone metabolism, dose and treatment response in patients with opioid addiction: A systematic review and meta-analysis. PloS One, 9(1), e86114. [DOI:10.1371/journal.pone.0086114] [PMID] [PMCID] 

Ekhtiari, H., Noroozi, A., Farhoudian, A., Radfar, S. R., Hajebi, A., & Sefatian, S., et al. (2020). The evolution of addiction treatment and harm reduction programs in Iran: A chaotic response or a synergistic diversity? Addiction, 115(7), 1395-1403. [DOI:10.1111/add.14905] [PMID] 

Finch, A., & Pillans, P. (2014). P-glycoprotein and its role in drug-drug interactions. Australian Prescriber, 37(4), 137-139. [DOI:10.18773/austprescr.2014.050] 

Fonseca, F., de la Torre, R., Díaz, L., Pastor, A., Cuyàs, E., & Pizarro, N., et al. (2011). Contribution of cytochrome P450 and ABCB1 genetic variability on methadone pharmacokinetics, dose requirements, and response. Plos One, 6(5), e19527. [DOI:10.1371/journal.pone.0019527] [PMID] [PMCID] 

Fonseca, F., Gratacòs, M., Escaramís, G., De Cid, R., Martín-Santos, R., & Fernández-Espejo, E., et al. (2010). Response to methadone maintenance treatment is associated with the MYOCD and GRM6 genes. Molecular Diagnosis & Therapy, 14(3), 171–178. [DOI:10.1007/BF03256370] [PMID] 

Fung, K. L., & Gottesman, M. M. (2009). A synonymous polymorphism in a common MDR1 (ABCB1) haplotype shapes protein function. Biochimica et Biophysica Acta, 1794(5), 860–871. [DOI:10.1016/j.bbapap.2009.02.014] [PMID] [PMCID] 

Gadel, S., Friedel, C., & Kharasch, E. D. (2015). Differences in methadone metabolism by CYP2B6 variants. Drug Metabolism and Disposition: The Biological Fate of Chemicals, 43(7), 994–1001. [DOI:10.1124/dmd.115.064352] [PMID] [PMCID] 

González-Saiz, F. (2004). Opiate Dosage Adequacy Scale (ODAS): A clinical diagnostic tool as a guide to dosing decisions. Heroin Addiction and Related Clinical Problems, 6(3), 41-50. [Link]

Hamraz, S. V., Mousavi, S. A., Shayannia, A., & Mirzaii, M. (2019). ABCB1 Polymorphisms in high-dose and low-dose dependent patients under methadone maintenance treatment in an Iranian Population. Iranian Journal of Psychiatry and Behavioral Sciences, 13(2), e90236. [DOI:10.5812/ijpbs.90236] 

Hoffmeyer, S., Burk, O., von Richter, O., Arnold, H. P., Brockmöller, J., & Johne, A., et al. (2000). Functional polymorphisms of the human multidrug-resistance gene: multiple sequence variations and correlation of one allele with P-glycoprotein expression and activity in vivo. Proceedings of the National Academy of Sciences, 97(7), 3473-3478. [DOI:10.1073/pnas.97.7.3473] [PMID] 

Horvat, C. M., Au, A. K., Conley, Y. P., Kochanek, P. M., Li, L., & Poloyac, S. M., et al. (2017). ABCB1 genotype is associated with fentanyl requirements in critically ill children. Pediatric Research, 82(1), 29-35. [DOI:10.1038/pr.2017.103] [PMID] [PMCID] 

Hung, C. C., Chiou, M. H., Huang, B. H., Hsieh, Y. W., Hsieh, T. J., & Huang, C. L., et al. (2011). Impact of genetic polymorphisms in ABCB1, CYP2B6, OPRM1, ANKK1 and DRD2 genes on methadone therapy in Han Chinese patients. Pharmacogenomics, 12(11), 1525-1533. [DOI:10.2217/pgs.11.96] [PMID] 

Jiang, B., Yan, L. J., & Wu, Q. (2019). ABCB1 (C1236T) polymorphism affects P-glycoprotein-mediated transport of methotrexate, doxorubicin, actinomycin D, and etoposide. DNA and Cell Biology, 38(5), 485-490. [DOI:10.1089/dna.2018.4583] [PMID] 

Kapur, B. M., Hutson, J. R., Chibber, T., Luk, A., & Selby, P. (2011). Methadone: A review of drug-drug and pathophysiological interactions. Critical Reviews in Clinical Laboratory Sciences, 48(4), 171-195. [DOI:10.3109/10408363.2011.620601] [PMID] 

Kharasch, E. D., & Stubbert, K. (2013). Role of cytochrome P4502B6 in methadone metabolism and clearance. Journal of Clinical Pharmacology, 53(3), 305–313. [DOI:10.1002/jcph.1] [PMID] [PMCID] 

Levran, O., O'Hara, K., Peles, E., Li, D., Barral, S., & Ray, B., et al. (2008). ABCB1 (MDR1) genetic variants are associated with methadone doses required for effective treatment of heroin dependence. Human Molecular Genetics, 17(14), 2219-2227. [DOI:10.1093/hmg/ddn122] [PMID] [PMCID] 

Levran, O., Peles, E., Randesi, M., Shu, X., Ott, J., & Shen, P. H., et al. (2013). Association of genetic variation in pharmacodynamic factors with methadone dose required for effective treatment of opioid addiction. Pharmacogenomics, 14(7), 755-768. [DOI:10.2217/pgs.13.58] [PMID] [PMCID] 

Lin, A. (2020). Effect of functional polymorphisms in ABCB1 gene on Opioid Doses in Patients with Chronic Low Back Pain. North Texas: UNTHSC Scholar. [Link]

Lo, A., Kerr, T., Hayashi, K., Milloy, M. J., Nosova, E., & Liu, Y., et al. (2018). Factors associated with methadone maintenance therapy discontinuation among people who inject drugs. Journal of Substance Abuse Treatment, 94, 41–46. [DOI:10.1016/j.jsat.2018.08.009] [PMID] [PMCID] 

Luo, R., Li, X., Qin, S., Luo, Z., Luo, X., & Hu, P., et al. (2017). Impact of SNP-SNP interaction among ABCB1, ARRB2, DRD1 and OPRD1 on methadone dosage requirement in Han Chinese patients. Pharmacogenomics, 18(18), 1659-1670. [DOI:10.2217/pgs-2017-0072] [PMID] 

Malekinejad, M., Navadeh, S., Lotfizadeh, A., Rahimi-Movaghar, A., Amin-Esmaeili, M., & Noroozi, A. (2015). High hepatitis C virus prevalence among drug users in Iran: Systematic review and meta-analysis of epidemiological evidence (2001-2012). International Journal of Infectious Diseases, 40, 116-130. [DOI:10.1016/j.ijid.2015.09.022] [PMID] [PMCID] 

Marwa, K. J., Schmidt, T., Sjögren, M., Minzi, O. M., Kamugisha, E., & Swedberg, G. (2014). Cytochrome P450 single nucleotide polymorphisms in an indigenous Tanzanian population: a concern about the metabolism of artemisinin-based combinations. Malaria Journal, 13, 420. [DOI:10.1186/1475-2875-13-420] [PMID] [PMCID] 

Matsui, A., & Williams, J. T. (2010). Activation of µ-opioid receptors and block of KIR3 potassium channels and NMDA receptor conductance by L-and D-methadone in rat locus coeruleus. British Journal of Pharmacology, 161(6), 1403-1413. [DOI:10.1111/j.1476-5381.2010.00967.x] [PMID] [PMCID] 

Momtazi, S., Noroozi, A., & Rawson, R. A. (2015). An overview of Iran drug treatment and harm reduction programs. In N. el-Guebaly, G. Carrà, & M. Galanter (Eds.), Textbook of addiction treatment: International perspectives (pp. 543-554). Milan: Springer. [DOI:10.1007/978-88-470-5322-9_25] 

Noroozi, A., Conigrave, K. M., Mirrahimi, B., Bastani, P., Charkhgard, N., & Salehi, M., et al. (2022). Factors influencing engagement and utilisation of opium tincture-assisted treatment for opioid use disorder: A qualitative study in Tehran, Iran. Drug and Alcohol Review, 41(2), 419–429. [DOI:10.1111/dar.13357] [PMID] 

Packiasabapathy, S., Aruldhas, B. W., Horn, N., Overholser, B. R., Quinney, S. K., & Renschler, J. S., et al. (2020). Pharmacogenomics of methadone: A narrative review of the literature. Pharmacogenomics, 21(12), 871-887. [DOI:10.2217/pgs-2020-0040] [PMID] [PMCID] 

Parchure, A. S., & Peng, Y. B. (2020). The impact of opioid analgesics and the pharmacogenomics of ABCB1 in opioid dependence and pharmacotherapies: A short review. The Open Pain Journal, 13, 7-21. [Link]

Rahimi-Movaghar, A., Gholami, J., Amato, L., Hoseinie, L., Yousefi-Nooraie, R., & Amin-Esmaeili, M. (2018). Pharmacological therapies for management of opium withdrawal. The Cochrane Database of Systematic Reviews, 6(6), CD007522.[DOI:10.1002/14651858.CD007522.pub2] [PMID] [PMCID] 

Rahimi, J., Gholami, J., Amin-Esmaeili, M., Fotouhi, A., Rafiemanesh, H., & Shadloo, B., et al. (2020). HIV prevalence among people who inject drugs (PWID) and related factors in Iran: A systematic review, meta-analysis and trend analysis. Addiction, 115(4), 605-622. [DOI:10.1111/add.14853] [PMID] 

Saloner, B., & Karthikeyan, S. (2015). Changes in substance abuse treatment use among individuals with opioid use disorders in the United States, 2004-2013. JAMA, 314(14), 1515-1517. [DOI:10.1001/jama.2015.10345] [PMID] 

Shinderman, M., Maxwell, S., Brawand-Amey, M., Golay, K. P., Baumann, P., & Eap, C. B. (2003). Cytochrome P4503A4 metabolic activity, methadone blood concentrations, and methadone doses. Drug and Alcohol Dependence, 69(2), 205–211.[DOI:10.1016/s0376-8716(02)00320-4] [PMID] 

Sia, A. T., Sng, B. L., Lim, E. C., Law, H., & Tan, E. C. (2010). The influence of ATP-binding cassette sub-family B member-1 (ABCB1) genetic polymorphisms on acute and chronic pain after intrathecal morphine for caesarean section: A prospective cohort study. International Journal of Obstetric Anesthesia, 19(3), 254-260. [DOI:10.1016/j.ijoa.2010.03.001] [PMID] 

Taqi, M. M., Faisal, M., & Zaman, H. (2019). OPRM1 A118G polymorphisms and its role in opioid addiction: Implication on severity and treatment approaches. Pharmacogenomics and Personalized Medicine, 12, 361–368. [DOI:10.2147/PGPM.S198654] [PMID] [PMCID] 

Tenegra, J. C., & Leebold, B. (2016). Substance abuse screening and treatment. Primary Care, 43(2), 217–227. [DOI:10.1016/j.pop.2016.01.008] [PMID] 

Walcher, S., Koc, J., Reichel, V., Schlote, F., Verthein, U., & Reimer, J. (2016). The opiate dosage adequacy scale for identification of the right methadone dose-a prospective cohort study. BMC Pharmacology and Toxicology, 17, 15. [DOI:10.1186/s40360-016-0058-9] [PMID] [PMCID] 

Wang, S. C., Ho, I. K., Tsou, H. H., Liu, S. W., Hsiao, C. F., & Chen, C. H., et al. (2013). Functional genetic polymorphisms in CYP2C19 gene in relation to cardiac side effects and treatment dose in a methadone maintenance cohort. Omics: A Journal of Integrative Biology, 17(10), 519–526. [DOI:10.1089/omi.2012.0068] [PMID] [PMCID] 

Wang, X. S., Song, H. B., Chen, S., Zhang, W., Liu, J. Q., & Huang, C., et al. (2015). Association of single nucleotide polymorphisms of ABCB1, OPRM1 and COMT with pain perception in cancer patients. Journal of Huazhong University of Science and Technology, 35(5), 752-758. [DOI:10.1007/s11596-015-1502-6] [PMID]