1932

Abstract

The association of an individual's genetic makeup with their response to drugs is referred to as pharmacogenomics. By understanding the relationship between genetic variants and drug efficacy or toxicity, we are able to optimize pharmacological therapy according to an individual's genotype. Pharmacogenomics research has historically suffered from bias and underrepresentation of people from certain ancestry groups and of the female sex. These biases can arise from factors such as drugs and indications studied, selection of study participants, and methods used to collect and analyze data. To examine the representation of biogeographical populations in pharmacogenomic data sets, we describe individuals involved in gene-drug response studies from PharmGKB, a leading repository of drug-gene annotations, and showcase, a gene that metabolizes approximately 25% of all prescribed drugs. We also show how the historical underrepresentation of females in clinical trials has led to significantly more adverse drug reactions in females than in males.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-pharmtox-030823-111731
2024-01-23
2024-04-27
Loading full text...

Full text loading...

/deliver/fulltext/pharmtox/64/1/annurev-pharmtox-030823-111731.html?itemId=/content/journals/10.1146/annurev-pharmtox-030823-111731&mimeType=html&fmt=ahah

Literature Cited

  1. 1.
    Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC et al. 2001. Initial sequencing and analysis of the human genome. Nature 409:6822860–921
    [Google Scholar]
  2. 2.
    Lauschke VM, Ingelman-Sundberg M. 2019. Prediction of drug response and adverse drug reactions: from twin studies to next generation sequencing. Eur. J. Pharm. Sci. 130:65–77
    [Google Scholar]
  3. 3.
    Malki MA, Pearson ER. 2020. Drug-drug-gene interactions and adverse drug reactions. Pharmacogenom. J. 20:3355–66
    [Google Scholar]
  4. 4.
    Pirmohamed M. 2014. Personalized pharmacogenomics: predicting efficacy and adverse drug reactions. Annu. Rev. Genom. Hum. Genet. 15:349–70
    [Google Scholar]
  5. 5.
    Wadelius M, Chen LY, Eriksson N, Bumpstead S, Ghori J et al. 2007. Association of warfarin dose with genes involved in its action and metabolism. Hum. Genet. 121:123–34
    [Google Scholar]
  6. 6.
    Zhang J, Wu T, Chen W, Fu J, Xia X, Chen L. 2019. Effect of gene-based warfarin dosing on anticoagulation control and clinical events in a real-world setting. Front. Pharmacol. 10:1527
    [Google Scholar]
  7. 7.
    Chan SL, Suo C, Lee SC, Goh BC, Chia KS, Teo YY. 2012. Translational aspects of genetic factors in the prediction of drug response variability: a case study of warfarin pharmacogenomics in a multi-ethnic cohort from Asia. Pharmacogenom. J. 12:4312–18
    [Google Scholar]
  8. 8.
    Agúndez JAG, Esguevillas G, Amo G, García-Martín E. 2014. Clinical practice guidelines for translating pharmacogenomic knowledge to bedside. Focus on anticancer drugs. Front. Pharmacol. 5:188
    [Google Scholar]
  9. 9.
    Huang RS, Ratain MJ. 2009. Pharmacogenetics and pharmacogenomics of anticancer agents. CA Cancer J. Clin. 59:142–55
    [Google Scholar]
  10. 10.
    Carr DF, Turner RM, Pirmohamed M. 2021. Pharmacogenomics of anticancer drugs: personalising the choice and dose to manage drug response. Br. J. Clin. Pharmacol. 87:2237–55
    [Google Scholar]
  11. 11.
    Jin X, Chandramouli C, Allocco B, Gong E, Lam CSP, Yan LL. 2020. Women's participation in cardiovascular clinical trials from 2010 to 2017. Circulation 141:7540–48
    [Google Scholar]
  12. 12.
    Yakerson A. 2019. Women in clinical trials: a review of policy development and health equity in the Canadian context. Int. J. Equity Health 18:156
    [Google Scholar]
  13. 13.
    Anaba U, Ishola A, Alabre A, Bui A, Prince M et al. 2022. Diversity in modern heart failure trials: Where are we, and where are we going. Int. J. Cardiol. 348:95–101
    [Google Scholar]
  14. 14.
    Need AC, Goldstein DB. 2009. Next generation disparities in human genomics: concerns and remedies. Trends Genet 25:11489–94
    [Google Scholar]
  15. 15.
    Bustamante CD, De la Vega FM, Burchard EG. 2011. Genomics for the world. Nature 475:7355163–65
    [Google Scholar]
  16. 16.
    Popejoy AB, Fullerton SM. 2016. Genomics is failing on diversity. Nature 538:161–64
    [Google Scholar]
  17. 17.
    Fatumo S, Chikowore T, Choudhury A, Ayub M, Martin AR, Kuchenbaecker K. 2022. A roadmap to increase diversity in genomic studies. Nat. Med. 28:2243–50
    [Google Scholar]
  18. 18.
    Kamiza AB, Toure SM, Vujkovic M, Machipisa T, Soremekun OS et al. 2022. Transferability of genetic risk scores in African populations. Nat. Med. 28:61163–66
    [Google Scholar]
  19. 19.
    Fatumo S, Inouye M. 2023. African genomes hold the key to accurate genetic risk prediction. Nat. Hum. Behav. 7:295–96
    [Google Scholar]
  20. 20.
    Fatumo S, Yakubu A, Oyedele O, Popoola J, Attipoe DA et al. 2022. Promoting the genomic revolution in Africa through the Nigerian 100K Genome Project. Nat. Genet. 54:5531–36
    [Google Scholar]
  21. 21.
    Hughes JH, Woo KH, Keizer RJ, Goswami S. 2022. Clinical decision support for precision dosing: opportunities for enhanced equity and inclusion in health care. Clin. Pharmacol. Ther. 113:565–74
    [Google Scholar]
  22. 22.
    Asiimwe IG, Zhang EJ, Osanlou R, Jorgensen AL, Pirmohamed M. 2021. Warfarin dosing algorithms: a systematic review. Br. J. Clin. Pharmacol. 87:41717–29
    [Google Scholar]
  23. 23.
    Whirl-Carrillo M, Huddart R, Gong L, Sangkuhl K, Thorn CF et al. 2021. An evidence-based framework for evaluating pharmacogenomics knowledge for personalized medicine. Clin. Pharmacol. Ther. 110:3563–72
    [Google Scholar]
  24. 24.
    Whirl-Carrillo M, McDonagh EM, Hebert JM, Gong L, Sangkuhl K et al. 2012. Pharmacogenomics knowledge for personalized medicine. Clin. Pharmacol. Ther. 92:4414–17
    [Google Scholar]
  25. 25.
    Huddart R, Fohner AE, Whirl-Carrillo M, Wojcik GL, Gignoux CR et al. 2019. Standardized biogeographic grouping system for annotating populations in pharmacogenetic research. Clin. Pharmacol. Ther. 105:51256–62
    [Google Scholar]
  26. 26.
    Taylor C, Crosby I, Yip V, Maguire P, Pirmohamed M, Turner RM. 2020. A review of the important role of CYP2D6 in pharmacogenomics. Genes 11:111295
    [Google Scholar]
  27. 27.
    Solovieff N, Hartley SW, Baldwin CT, Klings ES, Gladwin MT et al. 2011. Ancestry of African Americans with sickle cell disease. Blood Cells Mol. Dis. 47:141–45
    [Google Scholar]
  28. 28.
    Ahmed S, Zhou Z, Zhou J, Chen S-Q. 2016. Pharmacogenomics of drug metabolizing enzymes and transporters: relevance to precision medicine. Genom. Proteom. Bioinform. 14:5298–313
    [Google Scholar]
  29. 29.
    Del Tredici AL, Malhotra A, Dedek M, Espin F, Roach D et al. 2018. Frequency of CYP2D6 alleles including structural variants in the United States. Front. Pharmacol. 9:305
    [Google Scholar]
  30. 30.
    PharmGKB 2023. Gene-specific information tables for CYP2D6. Inf. Tables, PharmGKB https://www.pharmgkb.org/page/cyp2d6RefMaterials
    [Google Scholar]
  31. 31.
    Dean L, Kane M 2021. Codeine therapy and CYP2D6 genotype. Medical Genetics Summaries VM Pratt, SA Scott, M Pirmohamed Bethesda, MD: Natl. Cent. Biotechnol. Inf.
    [Google Scholar]
  32. 32.
    Deleted in proof
  33. 33.
    Twesigomwe D, Drögemöller BI, Wright GEB, Adebamowo C, Agongo G et al. 2023. Characterization of CYP2D6 pharmacogenetic variation in sub-Saharan African populations. Clin. Pharmacol. Ther. 113:3643–59
    [Google Scholar]
  34. 34.
    Rajman I, Knapp L, Morgan T, Masimirembwa C. 2017. African genetic diversity: implications for cytochrome P450-mediated drug metabolism and drug development. EBioMedicine 17:67–74
    [Google Scholar]
  35. 35.
    Ortega VE, Meyers DA. 2014. Pharmacogenetics: implications of race and ethnicity on defining genetic profiles for personalized medicine. J. Allergy Clin. Immunol. 133:116–26
    [Google Scholar]
  36. 36.
    Magavern EF, Gurdasani D, Ng FL, Lee SS-J. 2022. Health equality, race and pharmacogenomics. Br. J. Clin. Pharmacol. 88:127–33
    [Google Scholar]
  37. 37.
    Goodman CW, Brett AS. 2021. Race and pharmacogenomics–personalized medicine or misguided practice?. JAMA 325:7625–26
    [Google Scholar]
  38. 38.
    Viera de Lara D, Oliveira de Melo D, Araujo Silva LC, Gonçalves TS, Lima Santos PCJ. 2022. Pharmacogenetics of clopidogrel and warfarin in the treatment of cardiovascular diseases: an overview of reviews. Pharmacogenomics 23:7443–52
    [Google Scholar]
  39. 39.
    Scott SA, Khasawneh R, Peter I, Kornreich R, Desnick RJ. 2010. Combined CYP2C9, VKORC1 and CYP4F2 frequencies among racial and ethnic groups. Pharmacogenomics 11:6781–91
    [Google Scholar]
  40. 40.
    Ndadza A, Muyambo S, Mntla P, Wonkam A, Chimusa E et al. 2021. Profiling of warfarin pharmacokinetics-associated genetic variants: Black Africans portray unique genetic markers important for an African specific warfarin pharmacogenetics-dosing algorithm. J. Thromb. Haemost. 19:122957–73
    [Google Scholar]
  41. 41.
    Dean L 2012. Warfarin therapy and VKORC1 and CYP genotypes. Medical Genetics Summaries VM Pratt, SA Scott, M Pirmohamed Bethesda, MD: Natl. Cent. Biotechnol. Inf.
    [Google Scholar]
  42. 42.
    Kaye JB, Schultz LE, Steiner HE, Kittles RA, Cavallari LH, Karnes JH. 2017. Warfarin pharmacogenomics in diverse populations. Pharmacother. J. Hum. Pharmacol. Drug Ther. 37:91150–63
    [Google Scholar]
  43. 43.
    Asiimwe IG, Pirmohamed M. 2022. Ethnic diversity and warfarin pharmacogenomics. Front. Pharmacol. 13:866058
    [Google Scholar]
  44. 44.
    Sever P, Gouni-Berthold I, Keech A, Giugliano R, Pedersen TR et al. 2021. LDL-cholesterol lowering with evolocumab, and outcomes according to age and sex in patients in the FOURIER Trial. Eur. J. Prev. Cardiol. 28:8805–12
    [Google Scholar]
  45. 45.
    Planelles B, Margarit C, Inda M-D-M, Ballester P, Muriel J et al. 2020. Gender based differences, pharmacogenetics and adverse events in chronic pain management. Pharmacogenom. J. 20:2320–28
    [Google Scholar]
  46. 46.
    Knadler MP, Lobo E, Chappell J, Bergstrom R. 2011. Duloxetine: clinical pharmacokinetics and drug interactions. Clin. Pharmacokinet. 50:5281–94
    [Google Scholar]
  47. 47.
    Dawed AY, Mari A, Brown A, McDonald TJ, Li L et al. 2023. Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials. Lancet Diabetes Endocrinol 11:133–41
    [Google Scholar]
  48. 48.
    Pinho-Gomes A-C, Carcel C, Woodward M, Hockham C 2023. Women's representation in clinical trials of patients with chronic kidney disease. Clin. Kidney J. 16:91457–64
    [Google Scholar]
  49. 49.
    Lakoski SG, Lagace TA, Cohen JC, Horton JD, Hobbs HH. 2009. Genetic and metabolic determinants of plasma PCSK9 levels. J. Clin. Endocrinol. Metab. 94:72537–43
    [Google Scholar]
  50. 50.
    Cui Q, Ju X, Yang T, Zhang M, Tang W et al. 2010. Serum PCSK9 is associated with multiple metabolic factors in a large Han Chinese population. Atherosclerosis 213:2632–36
    [Google Scholar]
  51. 51.
    Sabatine MS, Giugliano RP, Keech AC, Honarpour N, Wiviott SD et al. 2017. Evolocumab and clinical outcomes in patients with cardiovascular disease. N. Engl. J. Med. 376:181713–22
    [Google Scholar]
  52. 52.
    Cordero A, Fernández Del Olmo MR, Cortez Quiroga GA, Romero-Menor C, Fácila L et al. 2022. Sex differences in low-density lipoprotein cholesterol reduction with PCSK9 inhibitors in real-world patients: the LIPID-REAL registry. J. Cardiovasc. Pharmacol. 79:4523–29
    [Google Scholar]
  53. 53.
    Myasoedova VA, Rimbert A, Camera M, Le May C, Capoulade R et al. 2023. LDL lowering effect of PCSK9 inhibition is reduced in women. Eur. Heart J. Cardiovasc. Pharmacother 9:4337–42
    [Google Scholar]
  54. 54.
    Zucker I, Prendergast BJ. 2020. Sex differences in pharmacokinetics predict adverse drug reactions in women. Biol. Sex Differ. 11:132
    [Google Scholar]
  55. 55.
    Pilote L, Raparelli V. 2018. Participation of women in clinical trials: not yet time to rest on our laurels. J. Am. Coll. Cardiol. 71:181970–72
    [Google Scholar]
  56. 56.
    Mauvais-Jarvis F, Bairey Merz N, Barnes PJ, Brinton RD, Carrero J-J et al. 2020. Sex and gender: modifiers of health, disease, and medicine. Lancet 396:10250565–82
    [Google Scholar]
  57. 57.
    Sarton E, Olofsen E, Romberg R, den Hartigh J, Kest B et al. 2000. Sex differences in morphine analgesia: an experimental study in healthy volunteers. Anesthesiology 93:51245–54
    [Google Scholar]
  58. 58.
    Dahan A, Sarton E, Teppema L, Olievier C. 1998. Sex-related differences in the influence of morphine on ventilatory control in humans. Anesthesiology 88:4903–13
    [Google Scholar]
  59. 59.
    Zun LS, Downey LVA, Gossman W, Rosenbaumdagger J, Sussman G. 2002. Gender differences in narcotic-induced emesis in the ED. Am. J. Emerg. Med. 20:3151–54
    [Google Scholar]
  60. 60.
    Cepeda MS, Farrar JT, Baumgarten M, Boston R, Carr DB, Strom BL. 2003. Side effects of opioids during short-term administration: effect of age, gender, and race. Clin. Pharmacol. Ther. 74:2102–12
    [Google Scholar]
  61. 61.
    Anthony M, Berg MJ. 2002. Biologic and molecular mechanisms for sex differences in pharmacokinetics, pharmacodynamics, and pharmacogenetics: part I. J. Women's Health Gend.-Based Med. 11:7601–15
    [Google Scholar]
  62. 62.
    Anthony M, Berg MJ. 2002. Biologic and molecular mechanisms for sex differences in pharmacokinetics, pharmacodynamics, and pharmacogenetics: Part II. J. Women's Health Gend.-Based Med. 11:7617–29
    [Google Scholar]
  63. 63.
    Bansal S, Mahendiratta S, Prakash A, Medhi B. 2021. Social pharmacology and its impact on clinics. Indian J. Pharmacol. 53:6437–39
    [Google Scholar]
  64. 64.
    Zarin DA, Tse T. 2008. Moving toward transparency of clinical trials. Science 319:58681340–42
    [Google Scholar]
/content/journals/10.1146/annurev-pharmtox-030823-111731
Loading
/content/journals/10.1146/annurev-pharmtox-030823-111731
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error