Study Explores Prevalence of Drug-Gene Interactions, Offers Recommendations for Implementing Pharmacogenetics Services

A key focus of Precision Health, drug gene interactions (DGIs) occur when a patient’s genome impacts how their body processes a drug. 

“Reducing DGIs is important because it could help to decrease the likelihood that an individual experiences side effects to some medications or could help identify a medication that is more likely to work for an individual,” explains first author and Precision Health member Amy Pasternak, PharmD, clinical assistant professor of pharmacy and clinical pharmacist, Michigan Medicine. “Everyone has the possibility of experiencing a DGI and we are still learning the best way to identify these individuals and develop strategies for personalized treatment.” 

While there are an increasing number of resources to help clinicians apply pharmacogenetic information to personalize prescribing decisions, historically the number of patients who have pharmacogenetic testing is low, potentially due to a perception that drug-gene interactions are rare. 

“We wanted to evaluate how common it was for a patient to experience a drug-gene interaction and where in the healthcare system that drug-gene interaction was occurring,” says Dr. Pasternak. “Understanding this can help us to more effectively translate pharmacogenetic testing and recommendations into patient care.” 

The multidisciplinary team’s findings were published in the February 2023 edition of Clinical and Translational Science. 

Study: Identifying the prevalence of clinically actionable drug-gene interactions in a health system biorepository to guide pharmacogenetics implementation services.

Using Precision Health data, the researchers evaluated charts of Michigan Genomics Initiative (MGI) participants within the University of Michigan Health System between July 1, 2014, and December 21, 2020. They used the genetic information from MGI to estimate DGIs, which were observed in 30-60%of evaluated patients. 

“One of the exciting findings of this study was that one quarter of patients with a DGI actually had more than one DGI, which supports potential value for panel testing of multiple pharmacogenes at the same time and the need to document these results for use across a patient’s lifetime,” explains Dr. Pasternak. 

“Given the DGI patterns we observed, I think this study confirms the continued need for integration of available pharmacogenetic results into the electronic medical record,” says Co-author Jessica Virzi, MSN, CSSBB, Clinical Informaticist with Precision Health’s Health Implementation Workgroup. “When this information is consistently stored and interpreted, we can develop clinical decision support to efficiently apply these results to relevant prescribing decisions.”

“We have started this work with the implementation of Genomic Indicators into our medical record, which allows for real-time notifications of known pharmacogenetic risks and can also allow for patient education to improve clinician and patient awareness of these relationships,” adds Ms. Virzi. “As we continue to discuss where and when to implement pharmacogenetics at U-M, understanding where different DGI are occurring in our healthcare system can also help to identify clinical stakeholders for development of new clinical decision support and populations that may most benefit from testing.”

One limitation of the study is that the authors were not able to confirm how long patients received the CPIC guideline medications or whether they experienced the potential adverse event or treatment inefficacy that can be associated with their genetics. “These findings are needed to further demonstrate the clinical impact that pharmacogenetic guided treatment can have on patient care,” adds Dr. Pasternak.

The study authors hope that in the future this type of research will help demonstrate that applying pharmacogenomics improves patient care and testing becomes a standard consideration for medication prescribing. However, they note that additional research that evaluates the impact of pharmacogenetic testing on clinical outcomes is needed to move toward this goal.

Co-authors include: Kristen Ward, Madison Irwin, Carl Okerberg, David Hayes, Lars Fritsche, Sebastian Zoellner, Jessica Virzi, Hae Mi Choe, and Vicki Ellingrod.