From Phenotype to Clinical Practice: Implementing Pharmacogenetic (PGx) Recommendations

Monika Opalek, PhD

June 6, 2024

Pharmacogenomics, the study of how genes affect a person's response to drugs, is crucial in the realm of personalized medicine. Pharmacogenes, the genes encoding factors directly involved in drug actions, can be broadly classified into two functional groups: metabolic enzymes and transporters/receptors. Enzyme pharmacogenes are responsible for converting substrates, such as drugs, into smaller molecules, thereby enabling their metabolism and clearance from the body. Transporter/receptor pharmacogenes are involved in moving substrates from the extracellular space to the intracellular space, affecting the absorption and distribution of the drug.

Both enzyme and transporter pharmacogenes can manifest the same phenotype, that is an individual's observable drug metabolism capabilities, determined by genotype. This classification helps predict a person's response to medications. Common phenotypes include:

  • Ultrarapid metabolizer
  • Normal metabolizer
  • Intermediate metabolizer
  • Poor metabolizer

These phenotypes affect individual drug response profiles in different ways, depending on both the role of the specific enzyme and the form of the drug administered. In particular, drugs can exist in two forms: active forms and prodrugs. Prodrugs require conversion into their active forms to exert their therapeutic effects. Drugs administered in their active forms act directly on the organism and must later be processed by enzymes to be neutralized and eliminated from the body. 

For example, the pharmacogene CYP2C19 catalyzes the bioactivation of the anticoagulant prodrug clopidogrel. The CYP2C19 phenotype affects the formation of an active form of clopidogrel, with intermediate and poor metabolizers experiencing reduced efficiency. This results in reduced inhibition of blood clotting and, because the drug is inefficient, the risk of major adverse cardiovascular and cerebrovascular events is also higher. CPIC recommends avoiding clopidogrel for intermediate and poor metabolizers, and administering prasugrel or ticagrelor instead [1]. 

Codeine is a prodrug that is used to treat acute and chronic pain. Its conversion to the active form, morphine, is mainly associated with the CYP2D6 activity. Poor metabolizers experience decreased pain relief due to greatly reduced morphine formation, while ultrarapid metabolizers convert codeine more efficiently, which in turn can result in toxic concentrations of morphine in the body even at low doses of codeine. For both poor and ultrarapid CYP2D6 metabolizers CPIC recommends avoiding codeine [2]. 

Statins, which are among the most widely prescribed drugs in the world, are administered in active form. They are used to lower cholesterol levels and prevent cardiovascular disease. Their metabolism is associated with several pharmacogenes that influence both the distribution and the conversion of statins. For example, the reduced function of the transporter SLCO1B1 (poor metabolizer) is linked to statin-associated musculoskeletal symptoms (SAMS). In this case, the drug accumulates in the body instead of being metabolized, leading to toxicity. CPIC recommendations for statins are drug- and gene-specific, with dosing guidelines adjusted for the metabolizer phenotype [3]. 

While these are just a few examples of the intricacies of PGx, they nevertheless illustrate the complexities and challenges of translating phenotypes into actionable clinical recommendations. Accurate phenotype translation requires a comprehensive evaluation of both, the drug profile of action and the specific roles of the involved pharmacogenes. 

At Intelliseq, we offer the ready-to-use GeneSpect PGx Reporter, where we compile gene-drug specific recommendations from the most reliable resources, including CPIC (Clinical Pharmacogenetics Implementation Consortium), FDA (Pharmacogenomic Biomarkers in Drug Labeling by FDA), DPWG (The Royal Dutch Association for the Advancement of Pharmacy-Pharmacogenetics Working Group), and PharmGKB (The Pharmacogenomics Knowledgebase). We use our proprietary Intelliseq’s Polygenic™ algorithm to assign genotypes which are later translated into metabolizer types. 

Our approach ensures that pharmacogenomic data can be effectively used to guide personalized medicine, optimizing drug dosage and minimizing adverse effects for individual patients.

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[1] Lee, C. R., Luzum, J. A., Sangkuhl, K., Gammal, R. S., Sabatine, M. S., Stein, C. M., Kisor, D. F., Limdi, N. A., Lee, Y. M., Scott, S. A., Hulot, J., Roden, D. M., Gaedigk, A., Caudle, K. E., Klein, T. E., Johnson, J. A., & Shuldiner, A. R. (2022). Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2C19 Genotype and clopidogrel Therapy: 2022 update. Clinical Pharmacology and Therapeutics/Clinical Pharmacology & Therapeutics, 112(5), 959–967. 

[2] Crews, K. R., Monte, A. A., Huddart, R., Caudle, K. E., Kharasch, E. D., Gaedigk, A., Dunnenberger, H. M., Leeder, J. S., Callaghan, J. T., Samer, C. F., Klein, T. E., Haidar, C. E., Van Driest, S. L., Ruano, G., Sangkuhl, K., Cavallari, L. H., Müller, D. J., Prows, C. A., Nagy, M., . . . Skaar, T. C. (2021). Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2D6, OPRM1, and COMT genotypes and select opioid therapy. Clinical Pharmacology and Therapeutics/Clinical Pharmacology & Therapeutics, 110(4), 888–896. 

[3] Cooper-DeHoff, R. M., Niemi, M., Ramsey, L. B., Luzum, J. A., Tarkiainen, E. K., Straka, R. J., Gong, L., Tuteja, S., Wilke, R. A., Wadelius, M., Larson, E. A., Roden, D. M., Klein, T. E., Yee, S. W., Krauss, R. M., Turner, R. M., Palaniappan, L., Gaedigk, A., Giacomini, K. M., . . . Voora, D. (2022). The Clinical Pharmacogenetics Implementation Consortium Guideline for SLCO1B1, ABCG2, and CYP2C9 genotypes and Statin‐Associated Musculoskeletal Symptoms. Clinical Pharmacology and Therapeutics/Clinical Pharmacology & Therapeutics, 111(5), 1007–1021. 

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