Navigating Life’s Journey with the Right Topographical Map
Combining genetic sequencing, life-style modification, and personalized drug therapy will transform health care.
John Halamka, M.D., president, Mayo Clinic Platform, and Paul Cerrato, senior research analyst and communications specialist, Mayo Clinic Platform, wrote this article.
While still prevalent, the one-size-fits-all health care is slowly giving way to a more precise, personalized approach that takes into account each person’s unique environmental and genetic risk factors. For that transformation to reach its full potential, it will require the use of several emerging tools that give each patient a unique “topographical map” to navigate the journey. Most of the health care events in our lives involve a set of experiences determined by our phenotype, genotype, and exposome. Some diagnoses are determined by our family history; some are a function of lifestyle choices, while others result from random events like trauma or infectious disease. With the help of the right roadmap, we can all be better prepared for what’s ahead.
What should this road map consist of? A growing body of evidence suggests full genomic sequencing at birth should be included. It’s estimated that 5% to 7% of the population is born with a rare disease, and many of these individuals could be treated if they were aware of the disorder and if the treatment was started very early in life. But for many of these inherited disorders, there is no way of knowing they exist early on without genetic sequencing. Currently, newborns are screened for a very limited number of genetic disorders; casting a much wider net will save lives. According to Richard Scott, chief medical officer of Genomics England, a government-funded company: “Genome sequencing could help. The costs have come down so much that we’re now at a tipping point where it’s wrong not to.” The England Genomics project is enrolling 200,000 babies to look for these overlooked disorders, and to identify the risk of future adult diseases and help predict genetically induced sensitivities to specific medications.
The second component of the topographical map would address said medication sensitivities with the help of pharmacogenomic (PGx) testing. Unfortunately, such testing, part of the effort to embrace precision medicine, has yet to be implemented in most health care facilities because decision makers and regulators remain unconvinced that it’s cost effective. However, several future-minded clinicians and technologists are already building the infrastructure that will eventually make it a reality at the community level. The goal of that infrastructure is to give clinicians quick access to a patient’s gene/drug interactions in the EHR or through an EHR plug-in that will allow them to adjust medication dosage as needed.
One such project, spearheaded by R. H. Dolin and associates at Elimu Informatics, produced a prototype for a pharmacogenomics clinical decision support (PGx CDS) service and linked it to an existing commercially available EHR system. The PGx CDS system relies on Fast Health care Interoperability Resources (FHIR) and CDS Hooks.1 The system is triggered when a clinician
places a medication order in the EHR. Once that occurs, the system searches for relevant genetic data in a Genomic Archiving and Communication System (GACS) and then notifies the prescribing clinician about any relevant recommendations. If there are no pharmacogenomic test results in the patient’s records, the PGx CDS system recommends that a test be ordered when indicated.
Dolin and his colleagues believe: “PGx use cases are of particular interest because over half of all primary care patients are exposed to PGx relevant drugs. Studies have found that 7% of U.S. Food and Drug Administration (FDA)-approved medications and 18% of the 4 billion prescriptions written in the United States per year are affected by actionable PGx variants; that nearly all individuals (98%) have at least one known, actionable variant by current Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines; and that when 12 pharmacogenes with at least one known, actionable, inherited variant are considered, over 97% of the U.S. population has at least one high risk diplotype with an estimated impact on nearly 75 million prescriptions.”
Mayo Clinic is among a select group of provider organizations that are bringing PGx testing into clinical practice. For example, Michael Cutrer, M.D., with Mayo Clinic’s Department of Neurology, and his colleagues have identified well-characterized subpopulations of migraine patients who respond differently to medications based on their unique genetic profile and single nucleotide polymorphisms.2 "Our study is based on the assumption that the seven chemically and therapeutically very distinct types of medication that are used in migraine prevention exert a biological effect that stabilizes or compensates for the biological cause of a patient’s migraine attacks," explains Dr. Cutrer. "This study is the first step toward identifying and treating the biological cause in each individual patient."
Similarly, the Right 10K Study involved adding pharmacogenomics data from 10,000 Mayo Clinic patients into their EHRs so that it can be used to make more intelligent decisions about how to prescribe medication to individual patients. Richard Weinshilboum, M.D., Director of the Mayo Clinic’s Pharmacogenomics Program, has summed up the potential of using PGx data in patient care in a few choice words: “Medications today can be very effective, but they can also cause harmful, sometimes life-threatening side effects. That’s where pharmacogenomics can help physicians select the right drug and dose for every patient.”
1 Dolin, R. H., Boxwala, A., and Shalaby, J. (2018). “A Pharmacogenomics
Clinical Decision Support Service Based on FHIR and CDS Hooks.” Methods of
Information in Medicine, vol. 57, pp. e115–e123.
2 Cutrer FM, Moyer AM, Atkinson EJ et al. Genetic variants related to successful migraine prophylaxis with verapamil. Molecular Genetics & Genomic Medicine. April 7, 2021 https://onlinelibrary.wiley.com/doi/10.1002/mgg3.1680