Pharmacogenomics: current status and future perspectives

Nkhoma, E. T., Poole, C., Vannappagari, V., Hall, S. A. & Beutler, E. The global prevalence of glucose-6-phosphate dehydrogenase deficiency: a systematic review and meta-analysis. Blood Cell Mol. Dis. 42, 267–278 (2009).

CAS  Google Scholar 

Pirmohamed, M. Pharmacogenetics and pharmacogenomics. Br. J. Clin. Pharmacol. 52, 345–347 (2001).

CAS  Google Scholar 

Spear, B. B., Heath-Chiozzi, M. & Huff, J. Clinical application of pharmacogenetics. Trends Mol. Med. 7, 201–204 (2001).

CAS  Google Scholar 

Connor, S. Glaxo chief: Our drugs do not work on most patients. Independent (Lond.) https://www.independent.co.uk/news/science/glaxo-chief-our-drugs-do-not-work-on-most-patients-5508670.html (8 December 2003).

Schork, N. J. Personalized medicine: time for one-person trials. Nature 520, 609–611 (2015).

CAS  Google Scholar 

Michel, M. C. & Staskin, D. Study designs for evaluation of combination treatment: focus on individual patient benefit. Biomedicines 10, 270 (2022).

CAS  Google Scholar 

Snapinn, S. M. & Jiang, Q. Responder analyses and the assessment of a clinically relevant treatment effect. Trials 8, 31 (2007).

Google Scholar 

Senn, S. Individual response to treatment: is it a valid assumption? BMJ 329, 966–968 (2004).

Google Scholar 

Lonergan, M. et al. Defining drug response for stratified medicine. Drug Discov. Today 22, 173–179 (2017).

Google Scholar 

Pirmohamed, M. et al. Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients. BMJ 329, 15–19 (2004). The largest epidemiological study of ADRs causing hospital admission.

Google Scholar 

Osanlou, R., Walker, L., Hughes, D. A., Burnside, G. & Pirmohamed, M. Adverse drug reactions, multimorbidity and polypharmacy: a prospective analysis of 1 month of medical admissions. BMJ Open 12, e055551 (2022).

Google Scholar 

Davies, E. C. et al. Adverse drug reactions in hospital in-patients: a prospective analysis of 3695 patient-episodes. PLoS ONE 4, e4439 (2009).

Google Scholar 

Alhawassi, T. M., Krass, I., Bajorek, B. V. & Pont, L. G. A systematic review of the prevalence and risk factors for adverse drug reactions in the elderly in the acute care setting. Clin. Interv. Aging 9, 2079–2086 (2014).

Google Scholar 

Soiza, R. L. Global pandemic — the true incidence of adverse drug reactions. Age Ageing 49, 934–935 (2020).

Google Scholar 

Mostafa, S., Kirkpatrick, C. M. J., Byron, K. & Sheffield, L. An analysis of allele, genotype and phenotype frequencies, actionable pharmacogenomic (PGx) variants and phenoconversion in 5408 Australian patients genotyped for CYP2D6, CYP2C19, CYP2C9 and VKORC1 genes. J. Neural Transm. 126, 5–18 (2019).

CAS  Google Scholar 

Cohn, I. et al. Genome sequencing as a platform for pharmacogenetic genotyping: a pediatric cohort study. NPJ Genom. Med. 2, 19 (2017).

Google Scholar 

Reisberg, S. et al. Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions. Genet. Med. 21, 1345–1354 (2019).

Google Scholar 

Alshabeeb, M. A., Deneer, V. H. M., Khan, A. & Asselbergs, F. W. Use of pharmacogenetic drugs by the Dutch population. Front. Genet. 10, 567 (2019).

CAS  Google Scholar 

Jithesh, P. V. et al. A population study of clinically actionable genetic variation affecting drug response from the Middle East. NPJ Genom. Med. 7, 10 (2022).

CAS  Google Scholar 

McInnes, G. et al. Pharmacogenetics at scale: an analysis of the UK Biobank. Clin. Pharmacol. Ther. 109, 1528–1537 (2021).

Google Scholar 

Turner, R. M., de Koning, E. M., Fontana, V., Thompson, A. & Pirmohamed, M. Multimorbidity, polypharmacy, and drug-drug-gene interactions following a non-ST elevation acute coronary syndrome: analysis of a multicentre observational study. BMC Med. 18, 367 (2020).

CAS  Google Scholar 

Van Driest, S. L. et al. Clinically actionable genotypes among 10,000 patients with preemptive pharmacogenomic testing. Clin. Pharmacol. Ther. 95, 423–431 (2014).

Google Scholar 

Ji, Y. et al. Preemptive pharmacogenomic testing for precision medicine: a comprehensive analysis of five actionable pharmacogenomic genes using next-generation DNA sequencing and a customized CYP2D6 genotyping cascade. J. Mol. Diagn. 18, 438–445 (2016).

Google Scholar 

Dunnenberger, H. M. et al. Preemptive clinical pharmacogenetics implementation: current programs in five US medical centers. Annu. Rev. Pharmacol. Toxicol. 55, 89–106 (2015).

CAS  Google Scholar 

Kimpton, J. E. et al. Longitudinal exposure of English primary care patients to pharmacogenomic drugs: an analysis to inform design of pre-emptive pharmacogenomic testing. Br. J. Clin. Pharmacol. 85, 2734–2746 (2019). A large database analysis showing exposure to drugs with pharmacogenomic guidance over a lifetime.

Google Scholar 

Whirl-Carrillo, M. et al. Pharmacogenomics knowledge for personalized medicine. Clin. Pharmacol. Ther. 92, 414–417 (2012).

CAS  Google Scholar 

Whirl-Carrillo, M. et al. An evidence-based framework for evaluating pharmacogenomics knowledge for personalized medicine. Clin. Pharmacol. Ther. 110, 563–572 (2021).

Google Scholar 

Gaedigk, A., Whirl-Carrillo, M., Pratt, V. M., Miller, N. A. & Klein, T. E. PharmVar and the landscape of pharmacogenetic resources. Clin. Pharmacol. Ther. 107, 43–46 (2020).

Google Scholar 

FDA. Table of Pharmacogenomic Biomarkers in Drug Labeling. https://www.fda.gov/drugs/science-and-research-drugs/table-pharmacogenomic-biomarkers-drug-labeling (2022).

FDA. Table of Pharmacogenetic Associations. https://www.fda.gov/medical-devices/precision-medicine/table-pharmacogenetic-associations (2022).

Electronic Medicines Compendium. Tamoxifen 20mg film-coated tablets. https://www.medicines.org.uk/emc/product/2248/smpc#gref (2022).

Koopmans, A. B., Braakman, M. H., Vinkers, D. J., Hoek, H. W. & van Harten, P. N. Meta-analysis of probability estimates of worldwide variation of CYP2D6 and CYP2C19. Transl. Psychiatry 11, 141 (2021). Meta-analysis detailing the global variation in frequencies of variants in two important cytochrome P450 genes.

Google Scholar 

Meyer, U. A. Pharmacogenetics — five decades of therapeutic lessons from genetic diversity. Nat. Rev. Genet. 5, 669–676 (2004).

CAS  Google Scholar 

Matthaei, J. et al. Heritability of metoprolol and torsemide pharmacokinetics. Clin. Pharmacol. Ther. 98, 611–621 (2015).

CAS  Google Scholar 

Arnett, D. K. et al. Pharmacogenetic approaches to hypertension therapy: design and rationale for the Genetics of Hypertension Associated Treatment (GenHAT) study. Pharmacogenomics J. 2, 309–317 (2002).

CAS  Google Scholar 

Hawcutt, D. B. et al. Susceptibility to corticosteroid-induced adrenal suppression: a genome-wide association study. Lancet Respir. Med. 6, 442–450 (2018).

CAS  Google Scholar 

Bourgeois, S. et al. Genome-wide association between EYA1 and aspirin-induced peptic ulceration. EBioMedicine 74, 103728 (2021).

CAS  Google Scholar 

McInnes, G., Yee, S. W., Pershad, Y. & Altman, R. B. Genomewide association studies in pharmacogenomics. Clin. Pharmacol. Ther. 110, 637–648 (2021). The successes and challenges of undertaking GWAS for pharmacogenomic phenotypes.

Google Scholar 

Maranville, J. C. & Cox, N. J. Pharmacogenomic variants have larger effect sizes than genetic variants associated with other dichotomous complex traits. Pharmacogenomics J. 16, 388–392 (2016).

CAS  Google Scholar 

Bourgeois, S. et al. A multi-factorial analysis of response to warfarin in a UK prospective cohort. Genome Med. 8, 2 (2016).

Google Scholar 

Relling, M. V. et al. Clinical pharmacogenetics implementation consortium guideline for thiopurine dosing based on TPMT and NUDT15 genotypes: 2018 update. Clin. Pharmacol. Ther. 105, 1095–1105 (2019).

CAS  Google Scholar 

Henricks, L. M. et al. DPYD genotype-guided dose individualisation of fluoropyrimidine therapy in patients with cancer: a prospective safety analysis. Lancet Oncol. 19, 1459–1467 (2018). Evaluation of four variants in the DPYD gene in patients of European descent, and how changes in dose can modulate the occurrence of toxicity.

CAS  Google Scholar 

Hulshof, E. C. et al. UGT1A1 genotype-guided dosing of irinotecan: a prospective safety and cost analysis in poor metaboliser patients. Eur. J. Cancer 162, 148–157 (2022).

CAS  Google Scholar 

Rawlins, M. D. & Thompson, J. W. in Textbook of Adverse Drug Reactions (ed. Davies, D. M.) 18–45 (Oxford University Press, Oxford, 1991).

Kuruvilla, R., Scott, K. & Pirmohamed, S. M. Pharmacogenomics of drug hypersensitivity: technology and translation. Immunol. Allergy Clin. North. Am. 42, 335–355 (2022).

Google Scholar 

Daly, A. K. et al. HLA-B*5701 genotype is a major determinant of drug-induced liver injury due to flucloxacillin. Nat. Genet. 41, 816–819 (2009).

CAS  Google Scholar 

McCormack, M. et al. HLA-A*3101 and carbamazepine-induced hypersensitivity reactions in Europeans. N. Engl. J. Med. 364, 1134–1143 (2011).

CAS  Google Scholar 

Phillips, E. & Mallal, S. Successful translation of pharmacogenetics into the clinic: the abacavir example. Mol. Diagn. Ther. 13, 1–9 (2009).

Google Scholar 

Mallal, S. et al. HLA-B*5701 screening for hypersensitivity to abacavir. N. Engl. J. Med. 358, 568–579 (2008). Randomized controlled trial showing the utility of pre-prescription genotyping for HLA-B*57:01 in preventing abacavir hypersensitivity.

Google Scholar 

Illing, P. T. et al. Immune self-reactivity triggered by drug-modified HLA-peptide repertoire. Nature 486, 554–558 (2012). Paper detailing the mechanisms by which abacavir binds to HLA-B*57:01 and alters the repertoire of endogenous peptides leading to immune self-reactivity.

CAS  Google Scholar 

White, K. D., Chung, W. H., Hung, S. I., Mallal, S. & Phillips, E. J. Evolving models of the immunopathogenesis of T cell-mediated drug allergy: the role of host, pathogens, and drug response. J. Allergy Clin. Immunol. 136, 219–234 (2015). quiz 235.

CAS  Google Scholar 

Jaruthamsophon, K., Thomson, P. J., Sukasem, C., Naisbitt, D. J. & Pirmohamed, M. HLA allele-restricted immune-mediated adverse drug reactions: framework for genetic prediction. Annu. Rev. Pharmacol. Toxicol. 62, 509–529 (2021).

Google Scholar 

Nelson, M. R. et al. The genetics of drug efficacy: opportunities and challenges. Nat. Rev. Genet. 17, 197–206 (2016).

CAS  Google Scholar 

Holmes, R. D., Tiwari, A. K. & Kennedy, J. L. Mechanisms of the placebo effect in pain and psychiatric disorders. Pharmacogenomics J. 16, 491–500 (2016).

CAS  Google Scholar 

Jorgensen, A. L. et al. Adherence and variability in warfarin dose requirements: assessment in a prospective cohort. Pharmacogenomics 14, 151–163 (2013).

CAS  Google Scholar 

Agache, I. & Akdis, C. A. Precision medicine and phenotypes, endotypes, genotypes, regiotypes, and theratypes of allergic diseases. J. Clin. Invest. 129, 1493–1503 (2019).

Google Scholar 

Brown, L. C. et al. Pharmacogenomic testing and depressive symptom remission: a systematic review and meta-analysis of prospective, controlled clinical trials. Clin. Pharmacol. Ther. https://doi.org/10.1002/cpt.2748 (2022).

Article  Google Scholar 

Pereira, N. L. et al. Clopidogrel pharmacogenetics. Circ. Cardiovasc. Interv. 12, e007811 (2019).

CAS  Google Scholar 

Shuldiner, A. R. et al. Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. JAMA 302, 849–857 (2009).

CAS  Google Scholar 

Beitelshees, A. L. et al. CYP2C19 genotype-guided antiplatelet therapy after percutaneous coronary intervention in diverse clinical settings. J. Am. Heart Assoc. 11, e024159 (2022).

Google Scholar 

Minderhoud, C., Otten, L. S., Hilkens, P. H. E., van den Broek, M. P. H. & Harmsze, A. M. Increased frequency of CYP2C19 loss-of-function alleles in clopidogrel-treated patients with recurrent cerebral ischemia. Br. J. Clin. Pharmacol. 88, 3335–3340 (2022).

CAS  Google Scholar 

Wang, Y. et al. Ticagrelor versus clopidogrel in CYP2C19 loss-of-function carriers with stroke or TIA. N. Engl. J. Med. 385, 2520–2530 (2021).

CAS  Google Scholar 

Nofziger, C. et al. PharmVar GeneFocus: CYP2D6. Clin. Pharmacol. Ther. 107, 154–170 (2020).

CAS  Google Scholar 

留言 (0)

沒有登入
gif