Abstract

The main aim of this work was to collect and present the polymorphisms that have been identified and tested and that may potentially have an influence on the effect of analgesic therapies. Opioid drugs are one of the most commonly used painkillers in the treatment of postoperative, neoplastic and post-traumatic pain. Opioid receptors and their types: μ, δ, κ, purinergic and adrenergic receptors contribute to nociceptive stimulation and their modulation. The analgesic effect induced by opioids is dependent on many factors, such as age, sex, body mass and the occurrence of different polymorphic variants of genes encoding opioid, purinergic and adrenergic receptors. Many polymorphisms have been identified within the following genes: OPRM, OPRK, OPRD, ADRB1 and P2RX7, encoding the following receptors: μ, κ, δ, purinergic P2X and β1-adrenergic. The most common polymorphism is the single nucleotide polymorphism (SNP-single nucleotide polymorphism). The occurrence of some polymorphic forms may generate differences in expression and have an impact on the physicochemical properties of receptors, which results in different levels of analgesia in the population and the generation of side effects. The relation between the occurrence of polymorphic variants of the genes of receptors participating in nociceptive stimulation and the increased or reduced demand for opioids necessary to achieve analgesia has been confirmed. Mechanisms in which polymorphisms affect the modification of the anesthetic response to opioids in most cases remain unknown. Further research on opioid, purinergic and adrenergic receptors polymorphisms may improve the effectiveness of opioid therapies by regulating the dose to the patient’s individual pain phenotype, and may reduce the risk of side effects resulting from using too high doses of the drug.

References

• 1. Bal J.: Genetyka medyczna i molekularna. Wydawnictwo Naukowe PWN, Warszawa 2017
  Google Scholar
• 2. Belfer I., Wu T., Kingman A., Krishnaraju R.K., Goldman D., Max M.B.: Candidate gene studies of human pain mechanisms: methods for optimizing choice of polymorphisms and sample size. Anesthesiology, 2004; 100: 1562-1572
  Google Scholar
• 3. Cagliani R., Fumagalli M., Pozzoli U., Riva S., Comi G.P., Torri F., Macciardi F., Bresolin N., Sironi M.: Diverse evolutionary histories for β-adrenoreceptor genes in humans. Am. J. Hum. Gen., 2009; 85: 64-75
  Google Scholar
• 4. Feng S., Li N., Xu S., Wang H., Yu W., Lu Y., Cao J., Meng Y.: Association of ADRB1 gene polymorphisms with pain sensitivity in a Chinese population. Int. J. Clin. Exp. Med., 2015; 8: 11514-11518
  Google Scholar
• 5. Frielle T., Kobilka B., Lefkowitz R.J., Caron M.G.: Human β1- and β2-adrenergic receptors: structurally and functionally related receptors derived from distinct genes. Trends Neurosci., 1988; 11: 321-324
  Google Scholar
• 6. Fukuda K., Hayashida M., Ide S., Saita N., Kokita Y., Kasai S., Nishizawa D., Ogai Y., Hasegawa J., Nagashima M., Tagami M., Komatsu H., Sora I., Koga H., Kaneko Y. i wsp.: Association between OPRM1 gene polymorphisms and fentanyl sensitivity in patients undergoing painful cosmetic surgery. Pain, 2009; 147: 194-201
  Google Scholar
• 7. Gene Cards. Human Gene Database. OPRD1 Gene (Protein Coding) Opioid Receptor Delta 1. http://www.genecards.org/cgi-bin/carddisp.pl?gene=OPRD1 (04.12.2017)
  Google Scholar
• 8. GeneCards. The Human Gene Database. OPRK1 Gene (Protein Coding) Opioid Receptor Kappa 1. http://www.genecards.org/cgi-bin/carddisp.pl?gene=OPRK1# (04.12.2017)
  Google Scholar
• 9. Gibson S.J., Helme R.D.: Age-related differences in pain perception and report. Clin. Geriatr. Med., 2001; 17: 433-456
  Google Scholar
• 10. Gong X.D., Wang J.Y., Liu F., Yuan H.H., Zhang W.Y., Guo Y.H., Jiang B.: Gene polymorphisms of OPRM1 A118G and ABCB1 C3435T may influence opioid requirements in Chinese patients with cancer pain. Asian Pac. J. Cancer Prev., 2013; 14: 2937-2943
  Google Scholar
• 11. Hajj A., Halepian L., Osta N.E., Chahine G., Kattan J., Rabbaa Khabbaz L.: OPRM1 c.118A>G polymorphism and duration of morphine treatment associated with morphine doses and quality-of-life in palliative cancer pain settings. Int. J. Mol. Sci., 2017; 18: 669
  Google Scholar
• 12. Hayashida M., Nagashima M., Satoh Y., Katoh R., Tagami M., Ide S., Kasai S., Nishizawa D., Ogai Y., Hasegawa J., Komatsu H., Sora I., Fukuda K., Koga H., Hanaoka K. i wsp.: Analgesic requirements after major abdominal surgery are associated with OPRM1 gene polymorphism genotype and haplotype. Pharmacogenomics, 2008; 9: 1605-1616
  Google Scholar
• 13. Holliday K.L., McBeth J., Macfarlane G., Huhtaniemi I.T., Bartfai G., Casanueva F.F., Forti G., Kula K., Punab M., Vanderschueren D., Wu F.C., Thomson W.: Investigating the role of pain-modulating pathway genes in musculoskeletal pain. Eur. J. Pain, 2013; 17: 28-34
  Google Scholar
• 14. Huang C.J., Liu H.F., Su N.Y., Hsu Y.W., Yang C.H., Chen C.C., Tsai P.S.: Association between human opioid receptor genes polymorphisms and pressure pain sensitivity in females. Anaesthesia, 2008; 63: 1288-1295
  Google Scholar
• 15. Ide S., Nishizawa D., Fukuda K., Kasai S., Hasegawa J., Hayashida M., Minami M., Ikeda K.: Haplotypes of P2RX7 gene polymorphisms are associated with both cold pain sensitivity and analgesic effect of fentanyl. Mol. Pain, 2014; 10: 75
  Google Scholar
• 16. Kim H., Clark D., Dionne R.A.: Genetic contributions to clinical pain and analgesia: Avoiding pitfalls in genetic research. J. Pain, 2009; 10: 663-693
  Google Scholar
• 17. Lee M.G., Kim H.J., Lee K.H., Choi Y.S.: The influence of genotype polymorphism on morphine analgesic effect for postoperative pain in children. Korean J. Pain, 2016; 29: 34-39
  Google Scholar
• 18. Moriyama A., Nishizawa D., Kasai S., Hasegawa J., Fukuda K., Nagashima M., Katoh R., Ikeda K.: Association between genetic polymorphisms of the β1-adrenergic receptor and sensitivity to pain and fentanyl in patients undergoing painful cosmetic surgery. J. Pharmacol. Sci., 2013; 121: 48-57
  Google Scholar
• 19. Mutschler E., Buczko W., Grotthus B.: Mutschler farmakologia i toksykologia. MedPharm Polska, Wrocław 2013
  Google Scholar
• 20. NCBI. OPRM1 opioid receptor mu 1 [Homo sapiens (human)]. https://www.ncbi.nlm.nih.gov/gene/4988 (25.11.2017)
  Google Scholar
• 21. NCBI. Reference SNP (refSNP) Cluster Report: rs419335. https://www.ncbi.nlm.nih.gov/SNP/snp_ref.cgi?rs=419335 (30.11.2017)
  Google Scholar
• 22. NCBI. Reference SNP (refSNP) Cluster Report: rs533123. https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=533123 (30.11.2017)
  Google Scholar
• 23. Nielsen L.M., Christrup L.L., Sato H., Drewes A.M., Olesen A.E.: Genetic influences of OPRM1, OPRD1 and COMT on morphine analgesia in a multi-modal, multi-tissue human experimental pain model. Basic Clin. Pharmacol. Toxicol., 2017; 121: 6-12
  Google Scholar
• 24. Nielsen L.M., Olesen A.E., Sato H., Christrup L.L., Drewes A.M.: Association between gene polymorphisms and pain sensitivity assessed in a multi-modal multi-tissue human experimental model – an explorative study. Basic Clin. Pharmacol. Toxicol., 2016; 119: 360-366
  Google Scholar
• 25. Ochroch E.A., Vachani A., Gottschalk A., Kanetsky P.A.: Natural variation in the μ-opioid gene OPRM1 predicts increased pain on third day after thoracotomy. Clin. J. Pain, 2012; 28: 747-754
  Google Scholar
• 26. Olesen A.E., Nielsen L.M., Feddersen S., Erlenwein J., Petzke F., Przemeck M., Christrup L.L., Drewes A.M.: Association between genetic polymorphisms and pain sensitivity in patients with hip osteoarthritis. Pain Pract., 2018; 18: 587-596
  Google Scholar
• 27. Olesen A.E., Sato H., Nielsen L.M., Staahl C., Droney J., Gretton S., Branford R., Drewes A.M., Arendt-Nielsen L., Riley J., Ross J.: The genetic influences on oxycodone response characteristics in human experimental pain. Fundam. Clin. Pharmacol., 2015; 29: 417-425
  Google Scholar
• 28. Olsen R., Foster D.J., Upton R.N., Olesen A.E., Ross J.R., Droney J., Sato H., Drewes A.M., Kreilgaard M.: Modelling the PKPD of oxycodone in experimental pain – Impact of opioid receptor polymorphisms. Eur. J. Pharm. Sci., 2016; 86: 41-49
  Google Scholar
• 29. OMIM. Online Mendelian Inheritance in Man. Beta-1-Adrenergic Receptor; ADRB1. http://omim.org/entry/109630 (09.12.2017)
  Google Scholar
• 30. Pan L., Xu J., Yu R., Xu M.M., Pan Y.X., Pasternak G.W.: Identification and characterization of six new alternatively spliced variants of the human μ opioid receptor gene, Oprm. Neuroscience, 2005; 133: 209-220
  Google Scholar
• 31. Ren Z.Y., Xu X.Q., Bao Y.P., He J., Shi L., Deng J.H., Gao X.J., Tang H.L., Wang Y.M., Lu L.: The impact of genetic variation on sensitivity to opioid analgesics in patients with postoperative pain: a systematic review and meta-analysis. Pain Physician, 2015; 18: 131-152
  Google Scholar
• 32. Reyes-Gibby C.C., Shete S., Rakvåg T., Bhat S.V., Skorpen F., Bruera E., Kaasa S., Klepstad P.: Exploring joint effects of genes and the clinical efficacy of morphine for cancer pain: OPRM1 and COMT gene. Pain, 2007; 130: 25-30
  Google Scholar
• 33. Sato H., Droney J., Ross J., Olesen A.E., Staahl C., Andresen T., Branford R., Riley J., Arendt-Nielsen L., Drewes A.M.: Gender, variation in opioid receptor genes and sensitivity to experimental pain. Mol. Pain, 2013; 9: 20
  Google Scholar
• 34. Schaffner W.: Enhancers, enhancers – from their discovery to today’s universe of transcription enhancers. Biol. Chem., 2015; 396: 311-327
  Google Scholar
• 35. Tashani O.A., Alabas O.A., Johnson M.I.: Cold pressor pain responses in healthy Libyans: effect of sex/gender, anxiety, and body size. Gend. Med., 2010; 7: 309-319
  Google Scholar
• 36. Wandner L.D., Scipio C.D., Hirsh A.T., Torres C.A., Robinson M.E.: The perception of pain in others: how gender, race, and age influence pain expectations. J. Pain, 2012; 13: 220-227
  Google Scholar
• 37. Wei W., Tian Y., Zhao C., Sui Z., Liu C., Wang C., Yang R.: Correlation of ADRB1 rs1801253 polymorphism with analgesic effect of fentanyl after cancer surgeries. Med. Sci. Monit., 2015; 21: 4000-4005
  Google Scholar
• 38. Zondervan K.T., Cardon L.R.: The complex interplay among factors that influence allelic association. Nat. Rev. Genet., 2004; 5: 89-100
  Google Scholar

Full text