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Precision medicine for rheumatologists: lessons from the pharmacogenomics of azathioprine
Laura L Daniel1, Alyson L Dickson1, Cecilia P Chung2,3,4
1Department of Medicine, Division of Rheumatology, Vanderbilt University Medical Center (LLD, ALD, CPC), Nashville, TN, 37232, USA.
Abstract:
Precision medicine aims to personalize treatment for both effectiveness and safety. As a critical component of this emerging initiative, pharmacogenomics seeks to guide drug treatment based on genetics. In this review article, we give an overview of pharmacogenomics in the setting of an immunosuppressant frequently prescribed by rheumatologists, azathioprine. Azathioprine has a narrow therapeutic index and a high risk of adverse events. By applying candidate gene analysis and unbiased approaches, researchers have identified multiple variants associated with an increased risk for adverse events associated with azathioprine, particularly bone marrow suppression. Variants in two genes, TPMT and NUDT15, are widely recognized, leading drug regulatory agencies and professional organizations to adopt recommendations for testing before initiation of azathioprine therapy. As more gene-drug interactions are discovered, our field will continue to face the challenge of balancing benefits and costs associated with genetic testing. However, novel approaches in genomics and the integration of clinical and genetic factors into risk scores offer unprecedented opportunities for the application of pharmacogenomics in routine practice. Key Points • Pharmacogenomics can help us understand how individuals' genetics may impact their response to medications. • Azathioprine is a success story for the clinical implementation of pharmacogenomics, particularly the effects of TPMT and NUDT15 variants on myelosuppression. • As our knowledge advances, testing and dosing recommendations will continue to evolve, with our field striving to balance costs and benefits to patients. • As we aim toward the goals of precision medicine, future research may integrate increasingly individualized traits-including clinical and genetic characteristics-to predict the safety and efficacy of particular medications for individual patients.
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