Skip to main content
Log in

The Role of Pharmacogenomics in Rare Diseases

  • Current Opinion
  • Published:
Drug Safety Aims and scope Submit manuscript

Abstract

Rare diseases have become an increasingly important public health priority due to their collective prevalence and often life-threatening nature. Incentive programs, such as the Orphan Drug Act have been introduced to increase the development of rare disease therapeutics. While the approval of these therapeutics requires supportive data from stringent pre-market studies, these data lack the ability to describe the causes of treatment response heterogeneity, leading to medications often being more harmful or less effective than predicted. If a Goal Line were to be used to describe the multifactorial continuum of phenotypic variations occurring in response to a medication, the ‘Goal Posts’, or the two defining points of this continuum, would be (1) Super-Response, or an extraordinary therapeutic effect; and (2) Serious Harm. Investigation of the pharmacogenomics behind these two extreme phenotypes can potentially lead to the development of new therapeutics, help inform rational use criteria in drug policy, and improve the understanding of underlying disease pathophysiology. In the context of rare diseases where cohort sizes are smaller than ideal, ‘small data’ and ‘big data’ approaches to data collection and analysis should be combined to produce the most robust results. This paper presents the importance of studying drug response in parallel to other research initiatives in rare diseases, as well as the need for international collaboration in the area of rare disease pharmacogenomics.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Nguengang Wakap S, Lambert DM, Olry A, Rodwell C, Gueydan C, Lanneau V, et al. Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database. Eur J Hum Genet. 2020;28:165–73. https://doi.org/10.1038/s41431-019-0508-0.

    Article  PubMed  Google Scholar 

  2. Fermaglich LJ, Miller KL. A comprehensive study of the rare diseases and conditions targeted by orphan drug designations and approvals over the forty years of the Orphan Drug Act. Orphanet J Rare Dis. 2023;18:163. https://doi.org/10.1186/s13023-023-02790-7.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Center for Drug Evaluation and Research. Development & approval process | drugs. FDA 2023. https://www.fda.gov/drugs/development-approval-process-drugs. Accessed 29 July 2023.

  4. Rosner AL. Evidence-based medicine: revisiting the pyramid of priorities. J Bodyw Mov Ther. 2012;16:42–9. https://doi.org/10.1016/j.jbmt.2011.05.003.

    Article  PubMed  Google Scholar 

  5. Makady A, de Boer A, Hillege H, Klungel O, Goettsch W. What is real-world data? A review of definitions based on literature and stakeholder interviews. Value Health. 2017;20:858–65. https://doi.org/10.1016/j.jval.2017.03.008.

    Article  PubMed  Google Scholar 

  6. Freemantle N, Strack T. Real-world effectiveness of new medicines should be evaluated by appropriately designed clinical trials. J Clin Epidemiol. 2010;63:1053–8. https://doi.org/10.1016/j.jclinepi.2009.07.013.

    Article  PubMed  Google Scholar 

  7. Schwartz D, Lellouch J. Explanatory and pragmatic attitudes in therapeutical trials. J Clin Epidemiol. 2009;62:499–505. https://doi.org/10.1016/j.jclinepi.2009.01.012.

    Article  PubMed  Google Scholar 

  8. Price D, Hillyer EV, van der Molen T. Efficacy versus effectiveness trials: informing guidelines for asthma management. Curr Opin Allergy Clin Immunol. 2013;13:50. https://doi.org/10.1097/ACI.0b013e32835ad059.

    Article  PubMed  Google Scholar 

  9. Kelman CW, Pearson S-A, Day RO, Holman CDJ, Kliewer EV, Henry DA. Evaluating medicines: let’s use all the evidence. Med J Aust. 2007;186:249–52. https://doi.org/10.5694/j.1326-5377.2007.tb00883.x.

    Article  PubMed  Google Scholar 

  10. Cherubini A, Signore SD, Ouslander J, Semla T, Michel J-P. Fighting against age discrimination in clinical trials. J Am Geriatr Soc. 2010;58:1791–6. https://doi.org/10.1111/j.1532-5415.2010.03032.x.

    Article  PubMed  Google Scholar 

  11. Juurlink DN, Mamdani MM, Lee DS, Kopp A, Austin PC, Laupacis A, et al. Rates of hyperkalemia after publication of the randomized aldactone evaluation study. N Engl J Med. 2004;351:543–51. https://doi.org/10.1056/NEJMoa040135.

    Article  CAS  PubMed  Google Scholar 

  12. Joseph PD, Craig JC, Caldwell PHY. Clinical trials in children. Br J Clin Pharmacol. 2015;79:357–69. https://doi.org/10.1111/bcp.12305.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Rodieux F, Gotta V, Pfister M, van den Anker JN. Causes and consequences of variability in drug transporter activity in pediatric drug therapy. J Clin Pharmacol. 2016;56:S173–92. https://doi.org/10.1002/jcph.721.

    Article  CAS  PubMed  Google Scholar 

  14. Carleton BC, Poole RI, Smith MA, Leeder JS, Ghannadan R, Ross CJD, et al. Adverse drug reaction active surveillance: developing a national network in Canada’s children’s hospitals. Pharmacoepidemiol Drug Saf. 2009;18:713–21. https://doi.org/10.1002/pds.1772.

    Article  PubMed  Google Scholar 

  15. Slater R, Cantarella A, Franck L, Meek J, Fitzgerald M. How well do clinical pain assessment tools reflect pain in infants? PLoS Med. 2008;5: e129. https://doi.org/10.1371/journal.pmed.0050129.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Tambuyzer E, Vandendriessche B, Austin CP, Brooks PJ, Larsson K, Miller Needleman KI, et al. Therapies for rare diseases: therapeutic modalities, progress and challenges ahead. Nat Rev Drug Discov. 2020;19:93–111. https://doi.org/10.1038/s41573-019-0049-9.

    Article  CAS  PubMed  Google Scholar 

  17. Korth-Bradley JM. Regulatory framework for drug development in rare diseases. J Clin Pharmacol. 2022;62:S15-26. https://doi.org/10.1002/jcph.2171.

    Article  CAS  PubMed  Google Scholar 

  18. Babolmorad G, Latif A, Domingo IK, Pollock NM, Delyea C, Rieger AM, et al. Toll-like receptor 4 is activated by platinum and contributes to cisplatin-induced ototoxicity. EMBO Rep. 2021;22:e51280. https://doi.org/10.15252/embr.202051280.

  19. Magdy T, Jiang Z, Jouni M, Fonoudi H, Lyra-Leite D, Jung G, et al. RARG variant predictive of doxorubicin-induced cardiotoxicity identifies a cardioprotective therapy. Cell Stem Cell. 2021;28:2076-2089.e7. https://doi.org/10.1016/j.stem.2021.08.006.

    Article  CAS  PubMed  Google Scholar 

  20. Magdy T, Jouni M, Kuo H-H, Weddle CJ, Lyra-Leite D, Fonoudi H, et al. Identification of drug transporter genomic variants and inhibitors that protect against doxorubicin-induced cardiotoxicity. Circulation. 2022;145:279–94. https://doi.org/10.1161/CIRCULATIONAHA.121.055801.

    Article  CAS  PubMed  Google Scholar 

  21. Hasbullah JS, Scott EN, Bhavsar AP, Gunaretnam EP, Miao F, Soliman H, et al. All-trans retinoic acid (ATRA) regulates key genes in the RARG-TOP2B pathway and reduces anthracycline-induced cardiotoxicity. PLoS ONE. 2022;17: e0276541. https://doi.org/10.1371/journal.pone.0276541.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Pereira NL, Rihal CS, So DYF, Rosenberg Y, Lennon RJ, Mathew V, et al. Clopidogrel pharmacogenetics. Circ Cardiovasc Interv. 2019;12: e007811. https://doi.org/10.1161/CIRCINTERVENTIONS.119.007811.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Lyon E, Gastier Foster J, Palomaki GE, Pratt VM, Reynolds K, Sábato MF, et al. Laboratory testing of CYP2D6 alleles in relation to tamoxifen therapy. Genet Med. 2012;14:990–1000. https://doi.org/10.1038/gim.2012.108.

    Article  CAS  PubMed  Google Scholar 

  24. Organization WH. How to develop and implement a national drug policy. Geneva: World Health Organization; 2001.

    Google Scholar 

  25. Almarsdóttir AB, Traulsen JM. Rational use of medicines—an important issue in pharmaceutical policy. Pharm World Sci. 2005;27:76–80. https://doi.org/10.1007/s11096-005-3303-7.

    Article  PubMed  Google Scholar 

  26. Hespanhol L, Vallio CS, Costa LM, Saragiotto BT. Understanding and interpreting confidence and credible intervals around effect estimates. Braz J Phys Ther. 2019;23:290–301. https://doi.org/10.1016/j.bjpt.2018.12.006.

    Article  PubMed  Google Scholar 

  27. Stone MB, Yaseen ZS, Miller BJ, Richardville K, Kalaria SN, Kirsch I. Response to acute monotherapy for major depressive disorder in randomized, placebo controlled trials submitted to the US Food and Drug Administration: individual participant data analysis. BMJ. 2022;378: e067606. https://doi.org/10.1136/bmj-2021-067606.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Bell SC, Mall MA, Gutierrez H, Macek M, Madge S, Davies JC, et al. The future of cystic fibrosis care: a global perspective. Lancet Respir Med. 2020;8:65–124. https://doi.org/10.1016/S2213-2600(19)30337-6.

    Article  CAS  PubMed  Google Scholar 

  29. Ramsey BW, Davies J, McElvaney NG, Tullis E, Bell SC, Dřevínek P, et al. A CFTR potentiator in patients with cystic fibrosis and the G551D mutation. N Engl J Med. 2011;365:1663–72. https://doi.org/10.1056/NEJMoa1105185.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Davies JC, Wainwright CE, Canny GJ, Chilvers MA, Howenstine MS, Munck A, et al. Efficacy and safety of ivacaftor in patients aged 6 to 11 years with cystic fibrosis with a G551D mutation. Am J Respir Crit Care Med. 2013;187:1219–25. https://doi.org/10.1164/rccm.201301-0153OC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Middleton PG, Mall MA, Dřevínek P, Lands LC, McKone EF, Polineni D, et al. Elexacaftor–tezacaftor–ivacaftor for cystic fibrosis with a single Phe508del Allele. N Engl J Med. 2019;381:1809–19. https://doi.org/10.1056/NEJMoa1908639.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Lassoued Ferjani H, Makhlouf Y, Maatallah K, Triki W, Ben Nessib D, Kaffel D, et al. Management of chronic recurrent multifocal osteomyelitis: review and update on the treatment protocol. Expert Opin Biol Ther. 2022;22:781–7. https://doi.org/10.1080/14712598.2022.2078161.

    Article  CAS  PubMed  Google Scholar 

  33. Girschick H, Finetti M, Orlando F, Schalm S, Insalaco A, Ganser G, et al. The multifaceted presentation of chronic recurrent multifocal osteomyelitis: a series of 486 cases from the Eurofever international registry. Rheumatology (Oxford). 2018;57:1203–11. https://doi.org/10.1093/rheumatology/key058.

    Article  CAS  PubMed  Google Scholar 

  34. Bhat CS, Anderson C, Harbinson A, McCann LJ, Roderick M, Finn A, et al. Chronic non bacterial osteitis: a multicentre study. Pediatr Rheumatol Online J. 2018;16:74. https://doi.org/10.1186/s12969-018-0290-5.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Chand AR, Xu H, Wells LG, Clair B, Neunert C, Spellman AE, et al. Are there true non-responders to hydroxyurea in sickle cell disease? A multiparameter analysis. Blood. 2014;124:4073. https://doi.org/10.1182/blood.V124.21.4073.4073.

    Article  Google Scholar 

  36. Ware RE. How I use hydroxyurea to treat young patients with sickle cell anemia. Blood. 2010;115:5300–11. https://doi.org/10.1182/blood-2009-04-146852.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Tsouana E, Ominu-Evbota K, Ghumran F, Tuffin N. 604 Hydroxycarbamide treatment failures in paediatric sickle cell disease; non-adherence, intolerance, or true non-response? Arch Dis Child. 2023;108:A379–80. https://doi.org/10.1136/archdischild-2023-rcpch.596.

    Article  Google Scholar 

  38. Vertex developed a CRISPR cure. It’s already on the hunt for something better. MIT technology review. https://www.technologyreview.com/2023/12/15/1085380/vertex-sickle-cell-pill-treatment/. Accessed 29 Jan 2024.

  39. Blau N. Sapropterin dihydrochloride for the treatment of hyperphenylalaninemias. Expert Opin Drug Metab Toxicol. 2013;9:1207–18. https://doi.org/10.1517/17425255.2013.804064.

    Article  CAS  PubMed  Google Scholar 

  40. Nutrients | Free Full-Text | Impact on diet quality and burden of care in sapropterin dihydrochloride use in children with phenylketonuria: a 6 month follow-up report. https://www.mdpi.com/2072-6643/15/16/3603. Accessed 29 Jan 2024.

  41. Downing NS, Shah ND, Aminawung JA, Pease AM, Zeitoun J-D, Krumholz HM, et al. Postmarket safety events among novel therapeutics approved by the US Food and Drug Administration between 2001 and 2010. JAMA. 2017;317:1854–63. https://doi.org/10.1001/jama.2017.5150.

    Article  PubMed  PubMed Central  Google Scholar 

  42. European Medicines Agency. Guidance on the format of the risk management plan (RMP) in the EU—in integrated format. Amsterdam: European Medicines Agency; 2018.

    Google Scholar 

  43. Mittmann N, Knowles SR, Gomez M, Fish JS, Cartotto R, Shear NH. Evaluation of the extent of under-reporting of serious adverse drug reactions. Drug Saf. 2004;27:477–87. https://doi.org/10.2165/00002018-200427070-00004.

    Article  PubMed  Google Scholar 

  44. Health Canada. Protecting Canadians from Unsafe Drugs Act (Vanessa’s Law) Amendments to the Food and Drugs Act (Bill C-17). 2013. https://www.canada.ca/en/health-canada/services/drugs-health-products/legislation-guidelines/protecting-canadians-unsafe-drugs-act-vanessa-law-amendments-food-drugs-act.html. Accessed 29 July 2023.

  45. Government of Canada PW and GSC. Canada Gazette, Part 2, volume 153, number 13: regulations amending the Food and Drug Regulations (serious adverse drug reaction reporting—hospitals). 2019.

  46. Wiktorowicz ME, Lexchin J, Paterson M, Mintzes B, Metge C, Light D, et al. Research networks involved in post-market pharmacosurveillance in the United States, United Kingdom, France, New Zealand, Australia, Norway and European Union: Lessons for Canada. Canadian Patient Safety Institute; 2000.

  47. van der Linden CMJ, Jansen PAF, van Marum RJ, Grouls RJE, Korsten EHM, Egberts ACG. Recurrence of adverse drug reactions following inappropriate re-prescription. Drug Saf. 2010;33:535–8. https://doi.org/10.2165/11532350-000000000-00000.

    Article  PubMed  Google Scholar 

  48. Layton D, Hazell L, Shakir SAW. Modified prescription-event monitoring studies. Drug Saf. 2011;34:e1-9. https://doi.org/10.2165/11593830-000000000-00000.

    Article  PubMed  Google Scholar 

  49. Bailey C, Peddie D, Wickham ME, Badke K, Small SS, Doyle-Waters MM, et al. Adverse drug event reporting systems: a systematic review. Br J Clin Pharmacol. 2016;82:17–29. https://doi.org/10.1111/bcp.12944.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Lazarou J, Pomeranz BH, Corey PN. Incidence of adverse drug reactions in hospitalized patients a meta-analysis of prospective studies. JAMA. 1998;279:1200–5. https://doi.org/10.1001/jama.279.15.1200.

    Article  CAS  PubMed  Google Scholar 

  51. Routledge PA, O’Mahony MS, Woodhouse KW. Adverse drug reactions in elderly patients. Br J Clin Pharmacol. 2004;57:121–6. https://doi.org/10.1046/j.1365-2125.2003.01875.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Kitchin R, Lauriault TP. Small data in the era of big data. GeoJournal. 2015;80:463–75. https://doi.org/10.1007/s10708-014-9601-7.

    Article  Google Scholar 

  53. Alyass A, Turcotte M, Meyre D. From big data analysis to personalized medicine for all: challenges and opportunities. BMC Med Genom. 2015;8:33. https://doi.org/10.1186/s12920-015-0108-y.

    Article  Google Scholar 

  54. Smith M, Hare ML. An overview of progress in childhood cancer survival. J Pediatr Oncol Nurs. 2004;21:160–4. https://doi.org/10.1177/1043454204264407.

    Article  PubMed  Google Scholar 

  55. Siegel DA, Li J, Henley SJ, Wilson RJ, Lunsford NB, Tai E, et al. Geographic variation in pediatric cancer incidence—United States, 2003–2014. MMWR Morb Mortal Wkly Rep. 2018;67:707–13. https://doi.org/10.15585/mmwr.mm6725a2.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Oeffinger KC, Mertens AC, Sklar CA, Kawashima T, Hudson MM, Meadows AT, et al. Chronic health conditions in adult survivors of childhood cancer. N Engl J Med. 2006;355:1572–82. https://doi.org/10.1056/NEJMsa060185.

    Article  CAS  PubMed  Google Scholar 

  57. Aminkeng F, Bhavsar AP, Visscher H, Rassekh SR, Li Y, Lee JW, et al. A coding variant in RARG confers susceptibility to anthracycline-induced cardiotoxicity in childhood cancer. Nat Genet. 2015;47:1079–84. https://doi.org/10.1038/ng.3374.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Visscher H, Ross CJD, Rassekh SR, Sandor GSS, Caron HN, van Dalen EC, et al. Validation of variants in SLC28A3 and UGT1A6 as genetic markers predictive of anthracycline-induced cardiotoxicity in children. Pediatr Blood Cancer. 2013;60:1375–81. https://doi.org/10.1002/pbc.24505.

    Article  CAS  PubMed  Google Scholar 

  59. Krishnaswamy S, Hao Q, Al-Rohaimi A, Hesse LM, Moltke LL von, Greenblatt DJ, et al. UDP Glucuronosyltransferase (UGT) 1A6 pharmacogenetics: II. Functional impact of the three most common nonsynonymous UGT1A6 polymorphisms (S7A, T181A, and R184S). J Pharmacol Exp Ther. 2005;313:1340–6. https://doi.org/10.1124/jpet.104.081968.

  60. Deng S, Yan T, Jendrny C, Nemecek A, Vincetic M, Gödtel-Armbrust U, et al. Dexrazoxane may prevent doxorubicin-induced DNA damage via depleting both Topoisomerase II isoforms. BMC Cancer. 2014;14:842. https://doi.org/10.1186/1471-2407-14-842.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Nagasawa K, Nagai K, Ohinishi N, Yokoyama T, Fujimoto S. Contribution of specific transport systems to anthracycline transport in tumor and normal cells. Curr Drug Metab. 2001;2:355–66. https://doi.org/10.2174/1389200013338243.

    Article  CAS  PubMed  Google Scholar 

  62. Aminkeng F, Ross CJD, Rassekh SR, Hwang S, Rieder MJ, Bhavsar AP, et al. Recommendations for genetic testing to reduce the incidence of anthracycline-induced cardiotoxicity. Br J Clin Pharmacol. 2016;82:683–95. https://doi.org/10.1111/bcp.13008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Thorn CF, Klein TE, Altman RB. PharmGKB: the pharmacogenomics knowledge base. Methods Mol Biol. 2013;1015:311–20. https://doi.org/10.1007/978-1-62703-435-7_20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Nelson MR, Bacanu S-A, Mosteller M, Li L, Bowman CE, Roses AD, et al. Genome-wide approaches to identify pharmacogenetic contributions to adverse drug reactions. Pharmacogenom J. 2009;9:23–33. https://doi.org/10.1038/tpj.2008.4.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bruce C. Carleton.

Ethics declarations

Funding

No funding was received for the preparation of this manuscript.

Conflicts of interest

Bruce C. Carleton and Colin J.D. Ross receive federal grant funds from the Canadian Institutes of Health Research, Genome Canada, and Genome BC, with additional support provided by the British Columbia Provincial Health Services Authority, BC Children's Hospital Foundation, and Health Canada. They have also previously received research funding from Dynacare Next Specialized Diagnostics as part of a Genome Canada federal grant. Gabriella S.S. Groeneweg provides program management of these research funds. Bruce C. Carleton also receives federal grant funds from the US Centers for Disease Control and Prevention, and in the past 3 years has provided consultation services to the Canadian Agency for Drugs and Technologies in Health and Dynacare. Alice Man declares no conflicts of interest.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and material

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Code availability

Not applicable.

Author contributions

AM contributed to the conceptualization, literature search, and writing of the original draft. BCC played a supervisory role and contributed to the conceptualization and writing of the original draft. AM, BCC, CJDR, and GSSG contributed to the review and editing of the manuscript. All authors read and approved the final manuscript.

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

Man, A., Groeneweg, G.S.S., Ross, C.J.D. et al. The Role of Pharmacogenomics in Rare Diseases. Drug Saf (2024). https://doi.org/10.1007/s40264-024-01416-6

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40264-024-01416-6

Navigation