Evidence for Pharmacogenomics

Navigating the data that supports the use of pharmacogenomics (PGx) in patient care can be a daunting task, but resources to help exist. A multitude of variables have to be considered in order to parse out any association observed between drug response and a patient’s genetics. PGx specific study parameters should be carefully analyzed. To name a few, patient ethnicity needs to be considered in translating variants to phenotypes, variant frequency can affect the statistical power of the study, and substrate specificity may prevent applying PGx results across a pharmacological class. Even if an association is found, does the evidence show that the association will result in a clinically relevant outcome?

There are organizations that have done a lot of that work in translating this data into clinically actionable recommendations. CPIC (Clinical Pharmacogenetics Implementation Consortium) is at the forefront of creating pharmacogenomics guidelines by experts in the field and regularly publishes in peer-reviewed journals.1 DPWG (Dutch Pharmacogenetics Working Group) also provides PGx guidelines and have recently been involved in a ground-breaking clinical study on a multigene panel used across health systems in Europe, highlighting the reduction in adverse drug reactions.2 FDA intermittently includes PGx information in their labels, and in collaboration between the FDA’s Center for Devices and Radiological Health and the Center for Drug Evaluation and Research, a web-based resource was created to provide their own PGx evaluations in a table format.3 Several other disease-specific guidelines have followed suit (e.g., DHHS4 & NCCN5). These resources allow providers a quick reference to the summary of the evidence.

Occasionally, however, there are cases where either no or unclear consensus is shown across the resources mentioned above. For example, statin-associated myopathy has been studied with the SLCO1B1 gene variants. The most current CPIC guideline for a statin and SLCO1B1 poor function phenotype (any individual carrying two no function alleles, such as *5 or *15) recommends to “prescribe an alternative statin depending on the desired potency”.6 CPIC also provides guidelines on other genes such as ABCG2 and CYP2C9. DPWG provides recommendations only on the SLCO1B1 T521C SNP (rs4149056). This SNP is the defining SNP for *5 and *15 function, however, this information is not intuitive to most providers. DPWG recommends to “choose an alternative” for the 521 CC genotype.7 The FDA Table of Pharmacogenetic Associations also only provides information for the SLCO1B1 T521C SNP. Under Section 2 of the table where “data indicate a potential impact on safety or response”, the 521 TC or CC genotype “Results in higher systemic concentrations and higher adverse reaction risk (myopathy)…”; however, no recommendations are provided.3 Furthermore, the FDA labels do not mention SLCO1B1 at all. Two issues can be observed from this example: (1) it is not immediately clear if and what SNPs should be genotyped, (2) recommendations or the lack thereof do not agree across the major PGx resources.

There are efforts being made, however, to achieve standardization. AMP (Association for Molecular Pathology) Clinical Practice Committee’s Pharmacogenomics Working Group was created to publish recommendations for a minimal set of variants that should be included in clinical PGx genotyping assays.8 Additionally, PGx organizations regularly reach out to one another and to governing bodies to collaborate and standardize PGx practices. Genetic testing companies also offer that bridge from test result to interpretation taking into account existing guideline recommendations. PGx is still a rapidly growing field and is continuously fine-tuning its use as a tool for precision medicine.

Ellie H. Jhun, PharmD, PhD is currently the Principal Scientist at OneOme LLC, a med tech company in Minneapolis, MN. OneOme offers additional information and PGx education which can be found here or you may reach out to support@oneome.com 

You can find more information on Pharmacogenomics and its impact on patient care at this link.

REFERENCES

  1. Relling MV, Klein TE. Clin Pharmacol Ther. 2011 Mar;89(3):464-7.
  2. Swen JJ, van der Wouden CH, Manson LE, et al. Lancet. 2023 Feb 4;401(10374):347-356.
  3. https://www.fda.gov/medical-devices/precision-medicine/table-pharmacogenetic-associations
  4. Panel on Antiretroviral Therapy and Medical Management of Children Living with HIV. Guidelines for the Use of Antiretroviral Agents in Pediatric HIV Infection. Available at: https://clinicalinfo.hiv.gov/sites/default/files/guidelines/documents/PedARV_GL.pdf. Accessed (April 2021).
  5. NCCN. Referenced with permission from the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) for Pediatric Acute Lymphoblastic Leukemia V.2.2023.  ©National Comprehensive Cancer Network, Inc. 2023.  All rights reserved.  Accessed August 9, 2023.  To view the most recent and complete version of the guideline, go online to NCCN.org. 
  6. Cooper-DeHoff RM, Niemi M, Ramsey LB, et al. Clin Pharmacol Ther. 2022 May;111(5):1007-1021.
  7. Dutch Pharmacogenetics Working Group Guidelines. Available at: https://www.knmp.nl/dossiers/farmacogenetica.
  8. Pratt VM, Cavallari LH, Del Tredici AL, et al. J Mol Diagn. 2021 Sep;23(9):1047-1064.

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