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Pharmacological response relating to drug response and the adverse effect events varies greatly in different individuals. The importance of assessing the role of inherited variation in genes that affect pharmacokinetics (the absorption, distribution, metabolism and excretion [ADME] of a drug) and pharmacodynamics (the response of the organism to the drug) is becoming more widely recognised (Schwarz, Gulilat and Kim, 2019). Genes involved in the encoding of drug-metabolizing enzymes, drug transporters and drug targets are most commonly referred as pharmacogenes.


Among the most researched such genes are the ones belonging to the CYP gene superfamily, which is thought to cause up to 60% of drug-induced toxicity (Maggo, Savage and Kennedy, 2016). Next-generation sequencing (NGS) represents an efficient and reliable method to evaluate the contribution of both common and rare polymorphisms to the genetic variation in pharmacological research. Furthermore, recent studies that analysed NGS data on pharmacogenes indicated that the majority of all variants found in coding regions were rare and very rare (93% with minor allele frequency [MAF] <1% and 83% with MAF < 0.01% respectively), with 30-40% of the functional variability contributed to these variants (Fujikura, Ingelman-Sundberg and Lauschke, 2015; Kozyra, Ingelman-Sundberg and Lauschke, 2017). While sequencing technology has identified many rare and very rare variants, more comprehensive subsequent research must be done to assess their functional and clinical significance and further clarify their effects and relevance.
The current challenges for clinical use of NGS-based results include a high degree of homology among the pharmacogenes (leading to misalignment of sequence reads to the referent genome), the existence of highly polymorphic genes with complex structural variation (e.g. some CYP and HLA family genes) and limited prediction capability for the novel haplotype structures (Russell and Schwarz, 2020). Regardless, NGS has the potential to enable more precise prediction of drug phenotypes in patients and allow the implementation of genotype-based dose adjustments in clinical settings in the future (Schwarz, Gulilat and Kim, 2019).
Fujikura, K., Ingelman-Sundberg, M. and Lauschke, V. M. (2015) ‘Genetic variation in the human cytochrome P450 supergene family.’, Pharmacogenetics and genomics. United States, 25(12), pp. 584–594. doi: 10.1097/FPC.0000000000000172.
Kozyra, M., Ingelman-Sundberg, M. and Lauschke, V. M. (2017) ‘Rare genetic variants in cellular transporters, metabolic enzymes, and nuclear  receptors can be important determinants of interindividual differences in drug response.’, Genetics in medicine : official journal of the American College of Medical Genetics. United States, 19(1), pp. 20–29. doi: 10.1038/gim.2016.33.
Maggo, S. D. S., Savage, R. L. and Kennedy, M. A. (2016) ‘Impact of New Genomic Technologies on Understanding Adverse Drug Reactions’, Clinical pharmacokinetics. Springer International Publishing, 55(4), pp. 419–436. doi: 10.1007/s40262-015-0324-9.
Russell, L. E. and Schwarz, U. I. (2020) ‘Variant discovery using next-generation sequencing and its future role in pharmacogenetics’, Pharmacogenomics, 21(7), pp. 471–486. doi: 10.2217/pgs-2019-0190.
Schwarz, U. I., Gulilat, M. and Kim, R. B. (2019) ‘The role of next-generation sequencing in pharmacogenetics and pharmacogenomics’, Cold Spring Harbor Perspectives in Medicine, 9(2), pp. 1–15. doi: 10.1101/cshperspect.a033027.

Nina Fajs, Edinburgh Genetics

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