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Mu Opioid Receptor Genetic Variation and Heroin Addiction
Commentary
Biological Psychiatry
Mu Opioid Receptor Genetic Variation and Heroin Addiction Jon-Kar Zubieta
The article by Hancock et al. (1) examines the functional significance of single nucleotide polymorphisms (SNPs) in the mu opioid receptor (OPRM1) gene as it pertains to associations with heroin addiction. In this work, cis-expression quantitative trait analyses in control, nonaddicted postmortem samples (BrainCloud participants) were employed to reduce an initial sample of 103 SNPs to 16 that were found to be associated with changes in messenger RNA expression and presented functional significance. The 16 SNPs were tested for association with heroin addiction using blood samples from participants in the Urban Health Study. Control data were acquired using six cohorts from the Database of Genotypes and Phenotypes. Final samples included 2004 subjects with heroin addiction and 8753 population control subjects; both samples comprised European Americans and African Americans. Four common functional SNPs, rs9478495, rs3778150, rs9384169, and rs562859, with a range of allelic frequencies of 16%–38%, were significantly associated with heroin addiction. A replication study employing samples from the Alcohol Dependence GWAS in European- and African Americans study and Australian data sets comprised 2828 subjects with heroin/other opioid addiction and 3689 control subjects. Among the SNPs initially significantly associated, rs3778150, with its C allele showing lower OPRM1 expression in the BrainCloud sample, was replicated in the second cohort. This is the largest and most comprehensive study of linkages between variation in the OPRM1 gene and heroin addiction. The authors also made an effort to explain the potential sources of discrepancies among previous studies, in particular, associations with rs1799971, which has been the most widely studied functional missense variant in this gene. Although no associations between rs1799971 and heroin addiction were observed in either the initial or the replication cohorts, rs3778150 and rs1799971 were observed to be in linkage disequilibrium in European, but not African, ancestry samples. Haplotypes carrying rs3778150-C and rs1799971-A (its major allele) were significantly associated with heroin addiction across all samples, whereas haplotypes carrying rs1799971-A without rs3778150-C were not associated with heroin addiction. The SNP rs3778150 was also observed to present varying levels of linkage disequilibrium with other alleles associated with heroin addiction in previous studies. The data provided in this study are consistent with the premise that genetic variations inducing reductions in the function of the OPRM1 gene would impair compensatory changes in OPRM1 concentrations or function in response to heroin administration, a potent agonist known to induce
activation and downregulation of this receptor and its transduction mechanisms. The lack of compensatory upregulation in response to sustained exposure to a potent agonist, heroin, is hypothesized to increase the doses of the opiate to obtain the same rewarding effect and potentially exacerbate withdrawal symptom severity. Perhaps more importantly, this study underscores the need for examining the functionality of genetic variation as a background that allows for data reduction and biological hypothesis testing as well as the capacity to replicate the results in additional samples. The study by Hancock et al. (1) provides a strong foundation for replication and hypothesis testing at least among the relatively common variants examined. There is a direct relationship between the actions of heroin and OPRM1—the drug and its target. However, as noted by the authors and despite genetic variations in the OPRM1 gene being probably some of the best studied in the field, substantial inconsistencies have been present between studies. The authors present plausible explanations of the inconsistencies based on linkage disequilibrium patterns among SNPs and haplotype patterns. From a translational perspective, it is not yet resolved what makes rs3778150-C particularly linked to heroin dependence. Of 103 SNPs, 16 of them were associated with lower levels of OPRM1 mRNA expression, but only one of them or, by association, others in strong linkage disequilibrium were found to be significantly relevant to heroin addiction. Even frequently studied SNPs such as rs1799971, described to induce reductions in OPRM1 mRNA and receptor availability in animal models and human data (2,3), were not related to heroin addiction risk in this sample. Furthermore, only rs1799971-A, the major allele not typically associated with addiction risk across various pathologies, and not rs1799971-C, related to lower levels of OPRM1 mRNA expression (2), was strongly linked to the rs3778150-C risk haplotype. What makes rs3778150 in the OPRM1 intron-1 particularly relevant to heroin addiction remains to be resolved not only from a behavioral perspective but also from a mechanistic point of view. However, the authors present a convincing argument that such studies need to be conducted to understand fully the potential for opioid addiction risk. In that context, and in addition to heroin, OPRM1 is also the mediator of the effects of all common opiate medications. Prescription opioid dependence has escalated substantially over the last decade, and the analysis of putative modulatory gene variants could provide initial assessments of analgesic needs and risk profiles (e.g., risk stratification). This line of work would be relevant for patients expected to be exposed to
SEE CORRESPONDING ARTICLE ON PAGE 474
http://dx.doi.org/10.1016/j.biopsych.2015.08.002 ISSN: 0006-3223
439 & 2015 Society of Biological Psychiatry Biological Psychiatry October 1, 2015; 78:439–440 www.sobp.org/journal
Biological Psychiatry
Commentary
opiates for the treatment of acute pain in the context of injury or surgical procedures or, even more critically, patients likely to be chronically exposed for the treatment of persistent pain states. At the present time, protocols for opioid analgesic administration do not take into account genetic variation in clinical decision making. Studies such as the Hancock et al. study reveal the capacity to personalize protocols further taking into account analgesic efficacy and risk for tolerance and addiction. The potential to change the way we perceive and address individual variation in addiction risk and the capacity to translate that information into medical practice is exciting. The complexity of genetic variations linked to those processes also highlights the difficulty in translating genetic discovery processes into understanding of complex psychophysical processes. The OPRM1 gene is critical for the effects of opioid drugs, whether in therapeutic or abuse contexts. Additionally, this receptor system is implicated in numerous other processes that make the findings of this report particularly important from epidemiologic and translational perspectives. Animal models and human data have linked the function of this receptor system to homeostatic mechanisms interfacing social and environmental cues and stress regulatory mechanisms affecting processes such as responses to physical (e.g., pain) (4) and emotional (5–7) stressors. It has also been associated with the indirect effects of most drugs of abuse (e.g., alcohol, psychostimulants) potentially via dopamine to opioid system interactions (8,9) as well as the hedonic effects of natural rewards (10). Further examination of the influences of genetic variation in the OPRM1 gene would potentially clarify interindividual differences in many behavioral and pathophysiologic processes, with far-reaching implications.
Article Information From the Department of Psychiatry and University Neuropsychiatry Institute, University of Utah Health Science Center, University of Utah, Salt Lake City, Utah. Address correspondence to Jon-Kar Zubieta, M.D., Ph.D., Department of Psychiatry, University of Utah Health Science Center, University of Utah, 501 Chipeta Way, Salt Lake City, UT 84108; E-mail: jonkar.zubieta@hsc. utah.edu. Received Aug 5, 2015; accepted Aug 6, 2015.
References 1.
2.
3.
4.
5.
6.
7.
8.
9.
Acknowledgments and Disclosures The author reports no biomedical financial interests or potential conflicts of interest.
440
10.
Hancock DB, Levy JL, Gaddis NC, Glasheen C, Saccone NL, Page GP, et al. (2015): Cis-Expression quantitative trait loci mapping reveals replicable associations with heroin addiction in OPRM1. Biol Psychiatry 78:474–484. Zhang Y, Wang D, Johnson AD, Papp AC, Sadee W (2005): Allelic expression imbalance of human mu opioid receptor (OPRM1) caused by variant A118G. J Biol Chem 280:32618–32624. Pecina M, Love T, Stohler CS, Goldman D, Zubieta JK (2015): Effects of the Mu opioid receptor polymorphism (OPRM1 A118G) on pain regulation, placebo effects and associated personality trait measures. Neuropsychopharmacology 40:957–965. Zubieta JK, Smith YR, Bueller JM, Xu Y, Kilbourn MR, Meyer CR, et al. (2001): Regional mu opioid receptor regulation of sensory and affective dimensions of pain. Science 293:311–315. Panksepp J, Herman BH, Vilberg T, Bishop P, DeEskinazi FG (1980): Endogenous opioids and social behavior. Neurosci Biobehav Rev 4: 473–487. Moles A, Kieffer BL, D’Amato FR (2004): Deficit in attachment behavior in mice lacking the mu-opioid receptor gene. Science 304: 1983–1986. Hsu DT, Sanford BJ, Meyers KK, Love TM, Hazlett KE, Wang H, et al. (2013): Social feedback activates the endogenous opioid system. Mol Psychiatry 2013;18:1147. Roberts AJ, McDonald JS, Heyser CJ, Kieffer BL, Matthes HW, Koob GF, et al. (2000): mu-Opioid receptor knockout mice do not selfadminister alcohol. J Pharmacol Exp Ther 293:1002–1008. Unterwald EM (2001): Regulation of opioid receptors by cocaine. Ann N Y Acad Sci 937:74–92. Smith KS, Berridge KC (2007): Opioid limbic circuit for reward: Interaction between hedonic hotspots of nucleus accumbens and ventral pallidum. J Neurosci 27:1594–1605.
Biological Psychiatry October 1, 2015; 78:439–440 www.sobp.org/journal
Biological Psychiatry
Mu Opioid Receptor Genetic Variation and Heroin Addiction Jon-Kar Zubieta
The article by Hancock et al. (1) examines the functional significance of single nucleotide polymorphisms (SNPs) in the mu opioid receptor (OPRM1) gene as it pertains to associations with heroin addiction. In this work, cis-expression quantitative trait analyses in control, nonaddicted postmortem samples (BrainCloud participants) were employed to reduce an initial sample of 103 SNPs to 16 that were found to be associated with changes in messenger RNA expression and presented functional significance. The 16 SNPs were tested for association with heroin addiction using blood samples from participants in the Urban Health Study. Control data were acquired using six cohorts from the Database of Genotypes and Phenotypes. Final samples included 2004 subjects with heroin addiction and 8753 population control subjects; both samples comprised European Americans and African Americans. Four common functional SNPs, rs9478495, rs3778150, rs9384169, and rs562859, with a range of allelic frequencies of 16%–38%, were significantly associated with heroin addiction. A replication study employing samples from the Alcohol Dependence GWAS in European- and African Americans study and Australian data sets comprised 2828 subjects with heroin/other opioid addiction and 3689 control subjects. Among the SNPs initially significantly associated, rs3778150, with its C allele showing lower OPRM1 expression in the BrainCloud sample, was replicated in the second cohort. This is the largest and most comprehensive study of linkages between variation in the OPRM1 gene and heroin addiction. The authors also made an effort to explain the potential sources of discrepancies among previous studies, in particular, associations with rs1799971, which has been the most widely studied functional missense variant in this gene. Although no associations between rs1799971 and heroin addiction were observed in either the initial or the replication cohorts, rs3778150 and rs1799971 were observed to be in linkage disequilibrium in European, but not African, ancestry samples. Haplotypes carrying rs3778150-C and rs1799971-A (its major allele) were significantly associated with heroin addiction across all samples, whereas haplotypes carrying rs1799971-A without rs3778150-C were not associated with heroin addiction. The SNP rs3778150 was also observed to present varying levels of linkage disequilibrium with other alleles associated with heroin addiction in previous studies. The data provided in this study are consistent with the premise that genetic variations inducing reductions in the function of the OPRM1 gene would impair compensatory changes in OPRM1 concentrations or function in response to heroin administration, a potent agonist known to induce
activation and downregulation of this receptor and its transduction mechanisms. The lack of compensatory upregulation in response to sustained exposure to a potent agonist, heroin, is hypothesized to increase the doses of the opiate to obtain the same rewarding effect and potentially exacerbate withdrawal symptom severity. Perhaps more importantly, this study underscores the need for examining the functionality of genetic variation as a background that allows for data reduction and biological hypothesis testing as well as the capacity to replicate the results in additional samples. The study by Hancock et al. (1) provides a strong foundation for replication and hypothesis testing at least among the relatively common variants examined. There is a direct relationship between the actions of heroin and OPRM1—the drug and its target. However, as noted by the authors and despite genetic variations in the OPRM1 gene being probably some of the best studied in the field, substantial inconsistencies have been present between studies. The authors present plausible explanations of the inconsistencies based on linkage disequilibrium patterns among SNPs and haplotype patterns. From a translational perspective, it is not yet resolved what makes rs3778150-C particularly linked to heroin dependence. Of 103 SNPs, 16 of them were associated with lower levels of OPRM1 mRNA expression, but only one of them or, by association, others in strong linkage disequilibrium were found to be significantly relevant to heroin addiction. Even frequently studied SNPs such as rs1799971, described to induce reductions in OPRM1 mRNA and receptor availability in animal models and human data (2,3), were not related to heroin addiction risk in this sample. Furthermore, only rs1799971-A, the major allele not typically associated with addiction risk across various pathologies, and not rs1799971-C, related to lower levels of OPRM1 mRNA expression (2), was strongly linked to the rs3778150-C risk haplotype. What makes rs3778150 in the OPRM1 intron-1 particularly relevant to heroin addiction remains to be resolved not only from a behavioral perspective but also from a mechanistic point of view. However, the authors present a convincing argument that such studies need to be conducted to understand fully the potential for opioid addiction risk. In that context, and in addition to heroin, OPRM1 is also the mediator of the effects of all common opiate medications. Prescription opioid dependence has escalated substantially over the last decade, and the analysis of putative modulatory gene variants could provide initial assessments of analgesic needs and risk profiles (e.g., risk stratification). This line of work would be relevant for patients expected to be exposed to
SEE CORRESPONDING ARTICLE ON PAGE 474
http://dx.doi.org/10.1016/j.biopsych.2015.08.002 ISSN: 0006-3223
439 & 2015 Society of Biological Psychiatry Biological Psychiatry October 1, 2015; 78:439–440 www.sobp.org/journal
Biological Psychiatry
Commentary
opiates for the treatment of acute pain in the context of injury or surgical procedures or, even more critically, patients likely to be chronically exposed for the treatment of persistent pain states. At the present time, protocols for opioid analgesic administration do not take into account genetic variation in clinical decision making. Studies such as the Hancock et al. study reveal the capacity to personalize protocols further taking into account analgesic efficacy and risk for tolerance and addiction. The potential to change the way we perceive and address individual variation in addiction risk and the capacity to translate that information into medical practice is exciting. The complexity of genetic variations linked to those processes also highlights the difficulty in translating genetic discovery processes into understanding of complex psychophysical processes. The OPRM1 gene is critical for the effects of opioid drugs, whether in therapeutic or abuse contexts. Additionally, this receptor system is implicated in numerous other processes that make the findings of this report particularly important from epidemiologic and translational perspectives. Animal models and human data have linked the function of this receptor system to homeostatic mechanisms interfacing social and environmental cues and stress regulatory mechanisms affecting processes such as responses to physical (e.g., pain) (4) and emotional (5–7) stressors. It has also been associated with the indirect effects of most drugs of abuse (e.g., alcohol, psychostimulants) potentially via dopamine to opioid system interactions (8,9) as well as the hedonic effects of natural rewards (10). Further examination of the influences of genetic variation in the OPRM1 gene would potentially clarify interindividual differences in many behavioral and pathophysiologic processes, with far-reaching implications.
Article Information From the Department of Psychiatry and University Neuropsychiatry Institute, University of Utah Health Science Center, University of Utah, Salt Lake City, Utah. Address correspondence to Jon-Kar Zubieta, M.D., Ph.D., Department of Psychiatry, University of Utah Health Science Center, University of Utah, 501 Chipeta Way, Salt Lake City, UT 84108; E-mail: jonkar.zubieta@hsc. utah.edu. Received Aug 5, 2015; accepted Aug 6, 2015.
References 1.
2.
3.
4.
5.
6.
7.
8.
9.
Acknowledgments and Disclosures The author reports no biomedical financial interests or potential conflicts of interest.
440
10.
Hancock DB, Levy JL, Gaddis NC, Glasheen C, Saccone NL, Page GP, et al. (2015): Cis-Expression quantitative trait loci mapping reveals replicable associations with heroin addiction in OPRM1. Biol Psychiatry 78:474–484. Zhang Y, Wang D, Johnson AD, Papp AC, Sadee W (2005): Allelic expression imbalance of human mu opioid receptor (OPRM1) caused by variant A118G. J Biol Chem 280:32618–32624. Pecina M, Love T, Stohler CS, Goldman D, Zubieta JK (2015): Effects of the Mu opioid receptor polymorphism (OPRM1 A118G) on pain regulation, placebo effects and associated personality trait measures. Neuropsychopharmacology 40:957–965. Zubieta JK, Smith YR, Bueller JM, Xu Y, Kilbourn MR, Meyer CR, et al. (2001): Regional mu opioid receptor regulation of sensory and affective dimensions of pain. Science 293:311–315. Panksepp J, Herman BH, Vilberg T, Bishop P, DeEskinazi FG (1980): Endogenous opioids and social behavior. Neurosci Biobehav Rev 4: 473–487. Moles A, Kieffer BL, D’Amato FR (2004): Deficit in attachment behavior in mice lacking the mu-opioid receptor gene. Science 304: 1983–1986. Hsu DT, Sanford BJ, Meyers KK, Love TM, Hazlett KE, Wang H, et al. (2013): Social feedback activates the endogenous opioid system. Mol Psychiatry 2013;18:1147. Roberts AJ, McDonald JS, Heyser CJ, Kieffer BL, Matthes HW, Koob GF, et al. (2000): mu-Opioid receptor knockout mice do not selfadminister alcohol. J Pharmacol Exp Ther 293:1002–1008. Unterwald EM (2001): Regulation of opioid receptors by cocaine. Ann N Y Acad Sci 937:74–92. Smith KS, Berridge KC (2007): Opioid limbic circuit for reward: Interaction between hedonic hotspots of nucleus accumbens and ventral pallidum. J Neurosci 27:1594–1605.
Biological Psychiatry October 1, 2015; 78:439–440 www.sobp.org/journal