Abstract
Background:
Genetic variability in ABCB1, encoding the P-glycoprotein efflux transporter, has been linked to altered methadone maintenance treatment dose requirements. However, subsequent studies have indicated that additional environmental or genetic factors may confound ABCB1 pharmacogenetics in different methadone maintenance treatment settings. There is evidence that genetic variability in OPRM1, encoding the mu opioid receptor, and ABCB1 may interact to affect morphine response in opposite ways. This study aimed to examine whether a similar gene-gene interaction occurs for methadone in methadone maintenance treatment.
Methods:
Opioid-dependent subjects (n = 119) maintained on methadone (15–300 mg/day) were genotyped for five single nucleotide polymorphisms of ABCB1 (61A > G; 1199G > A; 1236C > T; 2677G > T; 3435C > T), as well as for the OPRM1 118A > G single nucleotide polymorphism. Subjects’ methadone doses and trough plasma (R)-methadone concentrations (Ctrough) were compared between ABCB1 haplotypes (with and without controlling for OPRM1 genotype), and between OPRM1 genotypes (with and without controlling for ABCB1 haplotype).
Results:
Among wild-type OPRM1 subjects, an ABCB1 variant haplotype group (subjects with a wild-type and 61A:1199G:1236C:2677T:3435T haplotype combination, or homozygous for the 61A:1199G:1236C:2677T:3435T haplotype) had significantly lower doses (median ± standard deviation 35 ± 5 versus 180 ± 65 mg/day, P < 0.01) and Ctrough (78 ± 22 versus 177 ± 97 ng/mL, P < 0.05) than ABCB1 wild-type subjects. Among subjects with the most common ABCB1 haplotype combination (wild-type with 61A:1199G:1236T:2677T:3435T), the OPRM1 118 A/G genotype was associated with a significantly higher Ctrough than 118 A/A (250 ± 126 versus 108 ± 36 ng/mL, P = 0.016). No ABCB1 haplotype group or OPRM1 genotype was associated with dose or Ctrough without taking into account confounding genetic variability at the other locus. Therefore, two interacting pharmacogenetic determinants of methadone maintenance treatment response were identified, ie, ABCB1, where variants are associated with lower methadone requirements, and OPRM1, where the variant is associated with higher methadone requirements.
Conclusion:
These opposing pharmacogenetic effects therefore need to be considered in combination when assessing methadone maintenance treatment pharmacogenetics.
Acknowledgements
DTB was supported by a National Health and Medical Research Council of Australia Post-graduate scholarship; JKC is a FTT Fricker Research Fellow at the University of Adelaide (Medical Endowment Funds). This study was supported by the Faculty of Health Sciences, University of Adelaide, and National Health and Medical Research Council of Australia project grants (229050, 565387).
Disclosure
The authors have no conflicts of interest to report in this work.
Supplementary material A
ABCB1 2677G > T genotype determination by restriction fragment length (Figure SA1).
Figure SA1 BanI restriction fragment patterns for 2677G > T genotyping.
Notes: bp: size of marker bands in base pairs; M: pUC19/HpaII DNA molecular weight marker; 1, negative control; 2, homozygous variant genotype (T/T) with 224 bp undigested polymerase chain reaction product; 3, heterozygous genotype (G/T) with 224 bp undigested + 198 bp digested fragment; and 4, homozygous wild-type genotype (G/G) with 198 bp digested fragment. 26 bp digested fragments not visible on gel.
Supplementary material B
Regression analysis
Methods
Multiple linear regression analysis (IBM SPSS Statistics 19) was used to investigate the effects of demographic covariates on methadone dose, Ctrough, and Ctrough/dose. For these analyses, Ctrough and Ctrough/dose data were normalized by log-transformation (dose data could not be normalized by any standard transformation). Because the contributions of ABCB1 haplotype groups AGCGC/AGTTT and AGTTT/AGTTT were unclear from this study, only the AGCGC/AGCGC and AGCTT groups were included in regression analysis, and coded 0 and 1, respectively. OPRM1 118A/A, 118A/G, and 118G/G genotypes were coded 0, 1, and 2, respectively.
Firstly, gender, age, and weight (log-transformed) were submitted to stepwise inclusion (F probability < 0.05) regression for each dependent variable. Based on these results, any significant covariate was then automatically entered for all regression analyses of relevant dependent variable (dose, Ctrough, or Ctrough/dose) prior to stepwise inclusion (F probability < 0.05) of: OPRM1 genotype then ABCB1 haplotype; ABCB1 haplotype in OPRM1 118 A/A subjects; or OPRM1 118A > G genotype in ABCB1 AGCGC/AGTTT subjects. A subsequent conditional removal (F probability > 0.1) step for weight was also included for comparison.
Results
Of the demographic variables examined, weight was the only significant predictor of methadone dose by regression analysis (positive correlation, model P = 0.013). Subsequent regression analyses identified ABCB1 haplotype in OPRM1 118A/A subjects (negatively correlated), and OPRM1 118A > G genotype in ABCB1 AGCGC/AGTTT subjects (positively correlated), but not ABCB1 haplotype group or OPRM1 118A > G genotype, as significant predictors of dose ().
Table SB1 Multiple linear regression models for estimation of methadone dose based on weight and ABCB1 and OPRM1 genetic variability
No demographic variable was a significant predictor of Ctrough or Ctrough/dose. ABCB1 haplotype in OPRM1 118A/A subjects (model adjusted R2 = 0.481, P = 0.023), and OPRM1 118A > G genotype in ABCB1 AGCGC/AGTTT subjects (model adjusted R2 = 0.458, P = 0.019) were the only significant predictors of Ctrough. Neither ABCB1 haplotype group, nor ABCB1 haplotype group in OPRM1 118A/A subjects, were significant predictors of Ctrough/dose.
Supplementary material C
Supplementary tables
Table SC1 Frequencies of ABCB1 haplotypesTable Footnotea and OPRM1 118A > G minor allele and genotypes in opioid-dependent methadone maintenance treatment patients