Skip to main content

Advertisement

SpringerLink
Log in

Integrating pharmacogenomics into precision pain management

  • Review Article
  • Published:
Supportive Care in Cancer Aims and scope Submit manuscript

Abstract

Studies suggest wide heterogeneity in pain management response. Improved methods of pain pharmacotherapy are urgently needed to improve clinical response and safety profile of analgesics. The study or application of how genetics influence response to medications is called pharmacogenomics (PGx). PGx testing is a tool that may support more precise selection and dosing of pain medicines. PGx guidelines exist for drug–gene interactions with high levels of evidence and can be applied in clinical practice for more precise care in patients with cancer. The Clinical Pharmacogenetics Implementation Consortium (CPIC) is a publicly funded international consortium of experts who curate published PGx data and create peer-reviewed guidelines on how to translate PGx results into actionable prescribing decisions. Given the immense need to improve pain management, it is important to increase awareness and consider application of CPIC guidelines to pain management strategies. This commentary concisely describes how PGx can be used to aid in more precise applications of pain pharmacotherapy based on the CPIC guidelines.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Dahlhamer J, Lucas J, Zelaya, C et al (2018) Prevalence of chronic pain and high-impact chronic pain among adults — United States, 2016. MMWR Morb Mortal Wkly Rep 67:1001–1006. https://doi.org/10.15585/mmwr.mm6736a2

  2. Jiang C, Wang H, Wang Q, Luo Y, Sidlow R, Han X (2019) Prevalence of chronic pain and high-impact chronic pain in cancer survivors in the United States. JAMA Oncol 5:1224–1226. https://doi.org/10.1001/jamaoncol.2019.1439

    Article  PubMed  PubMed Central  Google Scholar 

  3. van den Beuken-van Everdingen MH, Hochstenbach LM, Joosten EA, Tjan-Heijnen VC, Janssen DJ (2016) Update on prevalence of pain in patients with cancer: systematic review and meta-analysis. J Pain Symptom Manage 51(1070–1090):e1079. https://doi.org/10.1016/j.jpainsymman.2015.12.340

    Article  Google Scholar 

  4. Institute of Medicine (2011) Relieving pain in America: a blueprint for transforming prevention, care, education, and research. National Academies Press. https://doi.org/10.17226/13172

  5. Noble M, Treadwell JR, Tregear SJ et al (2010) Long-term opioid management for chronic noncancer pain. Cochrane Database Syst Rev 2010(1):CD006605. https://doi.org/10.1002/14651858.CD006605.pub2

  6. Centers for Disease Control and Prevention (2018) Annual surveillance report of drug-related risks and outcomes - United States. https://www.cdc.gov/drugoverdose/pdf/pubs/2018-cdcdrug-surveillance-report.pdf. Accessed 12 Dec 2020

  7. Corli O, Roberto A, Corsi N, Galli F, Pizzuto M (2019) Opioid switching and variability in response in pain cancer patients. Support Care Cancer 27:2321–2327. https://doi.org/10.1007/s00520-018-4485-6

    Article  CAS  PubMed  Google Scholar 

  8. Chou R, Turner JA, Devine EB et al (2015) The effectiveness and risks of long-term opioid therapy for chronic pain: a systematic review for a National Institutes of Health Pathways to Prevention Workshop. Ann Intern Med 162:276–286. https://doi.org/10.7326/M14-2559

    Article  PubMed  Google Scholar 

  9. Busse JW, Wang L, Kamaleldin M et al (2018) Opioids for chronic noncancer pain: a systematic review and meta-analysis. JAMA 320:2448–2460. https://doi.org/10.1001/jama.2018.18472

    Article  PubMed  PubMed Central  Google Scholar 

  10. Kertesz SG (2017) Turning the tide or riptide? The changing opioid epidemic. Subst Abus 38:3–8. https://doi.org/10.1080/08897077.2016.1261070

    Article  PubMed  Google Scholar 

  11. Darnall BD, Juurlink D, Kerns RD et al (2019) International stakeholder community of pain experts and leaders call for an urgent action on forced opioid tapering. Pain Med 20:429–433. https://doi.org/10.1093/pm/pny228

    Article  PubMed  Google Scholar 

  12. Center for Behavioral Health Statistics and Quality (2017) 2016 National Survey on Drug Use and Health: Detailed Tables. Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/data/sites/default/files/NSDUH-DetTabs-2016/NSDUH-DetTabs-2016.pdf. Accessed 12 Dec 2020

  13. Anekar AA, Cascella M (2022) WHO Analgesic Ladder. StatPearls Treasure Island (FL): StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK554435/. Accessed 12 Dec 2020

  14. Sexton JE, Cox JJ, Zhao J, Wood JN (2018) The genetics of pain: implications for therapeutics. Annu Rev Pharmacol Toxicol 58:123–142. https://doi.org/10.1146/annurev-pharmtox-010617-052554

    Article  CAS  PubMed  Google Scholar 

  15. Evans WE, McLeod HL (2003) Pharmacogenomics–drug disposition, drug targets, and side effects. N Engl J Med 348:538–549. https://doi.org/10.1056/NEJMra020526

    Article  CAS  PubMed  Google Scholar 

  16. Relling MV, Klein TE (2011) CPIC: Clinical Pharmacogenetics Implementation Consortium of the pharmacogenomics research network. Clin Pharmacol Ther 89:464–467. https://doi.org/10.1038/clpt.2010.279

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Relling MV, Klein TE, Gammal RS, Whirl-Carrillo M, Hoffman JM, Caudle KE (2020) The Clinical Pharmacogenetics Implementation Consortium: 10 years later. Clin Pharmacol Ther 107:171–175. https://doi.org/10.1002/cpt.1651

    Article  PubMed  Google Scholar 

  18. Crews KR, Monte AA, Huddart R et al (2021) Clinical Pharmacogenetics Implementation Consortium guideline for CYP2D6, OPRM1, and COMT genotypes and select opioid therapy. Clin Pharmacol Ther 110(4):888–896. https://doi.org/10.1002/cpt.2149

    Article  CAS  PubMed  Google Scholar 

  19. Brandl E, Halford Z, Clark MD, Herndon C (2021) Pharmacogenomics in pain management: a review of relevant gene-drug associations and clinical considerations. Ann Pharmacother 55:1486–1501. https://doi.org/10.1177/10600280211003875

    Article  PubMed  Google Scholar 

  20. Theken KN, Lee CR, Gong L et al (2020) Clinical Pharmacogenetics Implementation Consortium guideline (CPIC) for CYP2C9 and nonsteroidal anti-inflammatory drugs. Clin Pharmacol Ther 108:191–200. https://doi.org/10.1002/cpt.1830

    Article  PubMed  Google Scholar 

  21. Hicks JK, Sangkuhl K, Swen JJ et al (2017) Clinical Pharmacogenetics Implementation Consortium guideline (CPIC) for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants: 2016 update. Clin Pharmacol Ther 102:37–44. https://doi.org/10.1002/cpt.597

    Article  CAS  PubMed  Google Scholar 

  22. Grosser T, Theken KN, FitzGerald GA (2017) Cyclooxygenase inhibition: pain, inflammation, and the cardiovascular system. Clin Pharmacol Ther 102:611–622. https://doi.org/10.1002/cpt.794

    Article  PubMed  Google Scholar 

  23. Grosser T, Fries S, FitzGerald GA (2006) Biological basis for the cardiovascular consequences of COX-2 inhibition: therapeutic challenges and opportunities. J Clin Invest 116:4–15. https://doi.org/10.1172/JCI27291

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Herndon CM, Hutchison RW, Berdine HJ et al (2008) Management of chronic nonmalignant pain with nonsteroidal antiinflammatory drugs. Joint opinion statement of the Ambulatory Care, Cardiology, and Pain and Palliative Care Practice and Research Networks of the American College of Clinical Pharmacy. Pharmacotherapy 28:788–805. https://doi.org/10.1592/phco.28.6.788

    Article  CAS  PubMed  Google Scholar 

  25. Warner TD, Mitchell JA (2004) Cyclooxygenases: new forms, new inhibitors, and lessons from the clinic. FASEB J 18:790–804. https://doi.org/10.1096/fj.03-0645rev

    Article  CAS  PubMed  Google Scholar 

  26. Lin JH, Lu AY (1998) Inhibition and induction of cytochrome P450 and the clinical implications. Clin Pharmacokinet 35:361–390. https://doi.org/10.2165/00003088-199835050-00003

    Article  CAS  PubMed  Google Scholar 

  27. Coxib, traditional NTC, Bhala N, et al (2013) Vascular and upper gastrointestinal effects of non-steroidal anti-inflammatory drugs: meta-analyses of individual participant data from randomised trials. Lancet 382:769–779. https://doi.org/10.1016/S0140-6736(13)60900-9

    Article  CAS  Google Scholar 

  28. Trescot A, Datta S, Lee M, Hansen H (2008) Opioid pharmacology. Pain Physician 11:S133–S153

    Article  PubMed  Google Scholar 

  29. Pathan H, Williams J (2012) Basic opioid pharmacology: an update. Br J Pain 6:11–16. https://doi.org/10.1177/2049463712438493

    Article  PubMed  PubMed Central  Google Scholar 

  30. Fudin J (2020) Chemical classes of opioids. Available from URL: https://paindr.com/wp-content/uploads/2020/11/Opioid-Structural-Classes-Figure_-updated-2020Nov.pdf. Accessed 22 Jan 2020

  31. Owusu Obeng A, Hamadeh I, Smith M (2017) Review of opioid pharmacogenetics and considerations for pain management. Pharmacotherapy 37:1105–1121. https://doi.org/10.1002/phar.1986

    Article  CAS  PubMed  Google Scholar 

  32. Patel JN, Hamadeh IS (2020) Pharmacogenomics-guided opioid management. BMJ Support Palliat Care 10:374–378. https://doi.org/10.1136/bmjspcare-2020-002589

    Article  PubMed  Google Scholar 

  33. Stauble ME, Moore AW, Langman LJ et al (2014) Hydrocodone in postoperative personalized pain management: pro-drug or drug? Clin Chim Acta 429:26–29. https://doi.org/10.1016/j.cca.2013.11.015

    Article  CAS  PubMed  Google Scholar 

  34. Otton SV, Schadel M, Cheung SW, Kaplan HL, Busto UE, Sellers EM (1993) CYP2D6 phenotype determines the metabolic conversion of hydrocodone to hydromorphone. Clin Pharmacol Ther 54:463–472. https://doi.org/10.1038/clpt.1993.177

    Article  CAS  PubMed  Google Scholar 

  35. Klimas R, Witticke D, El Fallah S, Mikus G (2013) Contribution of oxycodone and its metabolites to the overall analgesic effect after oxycodone administration. Expert Opin Drug Metab Toxicol 9:517–528. https://doi.org/10.1517/17425255.2013.779669

    Article  CAS  PubMed  Google Scholar 

  36. Zwisler ST, Enggaard TP, Noehr-Jensen L et al (2009) The hypoalgesic effect of oxycodone in human experimental pain models in relation to the CYP2D6 oxidation polymorphism. Basic Clin Pharmacol Toxicol 104:335–344. https://doi.org/10.1111/j.1742-7843.2009.00378.x

    Article  CAS  PubMed  Google Scholar 

  37. Gillman PK (2007) Tricyclic antidepressant pharmacology and therapeutic drug interactions updated. Br J Pharmacol 151:737–748. https://doi.org/10.1038/sj.bjp.0707253

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Rudorfer MV, Potter WZ (1999) Metabolism of tricyclic antidepressants. Cell Mol Neurobiol 19:373–409. https://doi.org/10.1023/a:1006949816036

    Article  CAS  PubMed  Google Scholar 

  39. Potter WZ, Zavadil AP 3rd, Kopin IJ, Goodwin FK (1980) Single-dose kinetics predict steady-state concentrations on imipramine and desipramine. Arch Gen Psychiatry 37:314–320. https://doi.org/10.1001/archpsyc.1980.01780160084010

    Article  CAS  PubMed  Google Scholar 

  40. Hicks JK, Bishop JR, Sangkuhl K et al (2015) Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and dosing of selective serotonin reuptake inhibitors. Clin Pharmacol Ther 98:127–134. https://doi.org/10.1002/cpt.147

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Mango K, Kiss AF, Fekete F, Erdos R, Monostory K (2022) CYP2B6 allelic variants and non-genetic factors influence CYP2B6 enzyme function. Sci Rep 12:2984. https://doi.org/10.1038/s41598-022-07022-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Meshkat S, Rodrigues NB, Di Vincenzo JD et al (2021) Pharmacogenomics of ketamine: a systematic review. J Psychiatr Res 145:27–34. https://doi.org/10.1016/j.jpsychires.2021.11.036

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Veterans Affairs, Durham, NC, USA

    Jill Bates

  2. Remitigate Therapeutics, Delmar, NY, USA

    Jeffrey Fudin

  3. Department of Cancer Pharmacology and Pharmacogenomics, Levine Cancer Institute, Atrium Health, Charlotte, NC, USA

    Jai N. Patel

Authors
  1. Jill Bates
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jeffrey Fudin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jai N. Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jai N. Patel.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

This paper is dedicated to the memory of Jeffrey Fudin who passed away in the making of this manuscript.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bates, J., Fudin, J. & Patel, J.N. Integrating pharmacogenomics into precision pain management. Support Care Cancer 30, 10453–10459 (2022). https://doi.org/10.1007/s00520-022-07404-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00520-022-07404-9

Keywords

Search

Navigation