We often think of prescription medication as a simple, “one size fits all” solution – anyone can go to the doctor with a backache to get a bottle of ibuprofen. The reality, however, is that physicians must carefully consider our biology when prescribing medication: age, sex, weight, diet, and pre-existing conditions can all influence a patient’s response to drugs. With the expansion of personalized medicine and our understanding of the genome, researchers are becoming increasingly more aware of how our genetic makeup can impact drug therapy as well.
Pharmacogenomics (PGx) looks at how an individual’s response to drugs (pharmacology) is affected by their genetic information (genomics). It is the marriage of these fields which aims to predict how a patient will respond to medication, who will benefit, who will not respond, and who may experience an adverse drug reaction. This rapidly emerging field is on track to radically improve medicine, with more predictable side effects and screening for likely drug responses. Pharmacogenomics is used in research into cardiovascular disorders, oncology, respiratory and inflammatory diseases, neurological and psychiatric disorders, health management, and predictive medication . As we will see, utilizing PGx to provide more effective care is ultimately advantageous and cost-effective for patients, clinicians, laboratories, and the healthcare system overall.
PGx and Drug Metabolism
More than 80% of adults in the United States take at least one medication. But did you know that every year an estimated ~7% of hospitalized patients have a serious adverse drug reaction (ADR), potentially accounting for more than 100,000 deaths in the United States alone ? Costs associated with ADRs are estimated at $136 billion annually . Overall, ADR is one of the top 10 leading causes for illness and death in developed countries .
Genetic variation (in drug-metabolizing enzymes, drug receptors, and drug transporters) has been associated with variability in both the efficacy and toxicity of drugs . Mutations can affect drug metabolism, efficiency, and safety. Even small genetic differences may cause enzymes to degrade or oxidize a drug too quickly, making it ineffective or even harmful to patients. For example, the CYP450 genes, which are described further below, are polymorphic and can result in reduced, absent, or increased enzyme activity.
PGx provides a personalized genetic analysis that can support physicians selecting the most appropriate drug for the patient. To help educate and navigate the complexity of PGx, organizations such as the international Clinical Pharmacogenetics Implementation Consortium (CPIC) act as an important source for reputable PGx evidence and guidelines .
The Cytochrome P450 Superfamily (CYP450): CYP2D6, CYP2C9, and CYP2C19
Let’s illustrate the benefits of PGx with some examples. The cytochrome P450 superfamily (CYP450) is a large and diverse group of enzymes that form the major system for metabolizing or detoxifying lipids, hormones, toxins, and drugs in the liver . A well-known member of this group is CYP2D6, a drug-metabolizing enzyme found in the liver which acts on a quarter of all prescribed drugs, including codeine . Extensive metabolizers (75-85% of the population) have normal activity enzymes which convert codeine into its active metabolite, morphine. Intermediate (10-15% of the population) or poor (5-10% of the population) metabolizers have inactive copies of CYP2D6 and therefore decreased enzyme activity and reduced morphine levels. In contrast, the ultrarapid metabolizers (1-10% of the population) with more than 2 normal-function copies of the gene, metabolize codeine to morphine to the point where individuals may experience morphine overdose [3, 7].
Another important member of the P450 family is CYP2C9. This enzyme contributes to the metabolism of approximately 15% of all drugs that are subject to P450-catalyzed biotransformation . Genetic variation in the CYP2C9 gene is a well-known genetic factor that influences warfarin dosing . Warfarin, a common blood thinner worldwide, requires tailored doses (dose titration) for each patient to maintain a balance in the clotting system and to avoid side effects such as bleeding and stroke (10). CYP2C9 testing is routinely performed for warfarin dosing, utilizing pharmacogenomic algorithms. Nonsteroidal anti-inflammatory drugs (NSAIDs) such as diclofenac, flurbiprofen, and ibuprofen are also well established CYP2C9 substrates, which are used to reduce inflammation and pain but can also cause gastrointestinal, cardiovascular, and renal adverse effects. Several reports suggest certain CYP2C9 variants increase the risk of gastrointestinal bleeding to NSAIDs .
In cardiovascular medicine, individuals receiving the drug clopidogrel were genetically tested. Clopidogrel was used to prevent clots in patients with an implanted stent. CYP2C19 metabolization status was found to be a prognostic indicator for Major Adverse Cardiac Events (MACE) .
PGx in the Clinic
ADRs are difficult for patients to endure, but they can also be financial nightmares for healthcare systems. ADRs place an enormous burden on patients, payers and clinicians. Fortunately, many causes of adverse drug events (ineffective drug prescriptions, improper dosing, and negative drug-drug interactions) can be avoided through genetic testing. Better drug management can also reduce polypharmacy, which cuts costs across the board.
Overall, many PGx applications are found to be cost-effective or even cost-saving . Given that 91 to >99.9% of analyzed individual carried at least one actionable PGx variants , the potential savings to overall healthcare costs could be remarkable. As genomics becomes more central to healthcare infrastructure, it comes as no surprise that the global market for pharmacogenomics increased from $6.5 billion in 2019 to $7.1 billion in 2020  with no end in sight.
PGx in the Lab
The cost of genetic testing itself is an important factor in determining the cost-effectiveness of a PGx-guided treatment strategy . It is becoming more and more practical for laboratories to adopt genetic testing with improving technology and decreasing costs. Once genetic testing becomes mainstream in the clinic service, economies of scale will only lower the price further .
In the lab, technology selection is usually driven by target coverage, total targets, cost, coverage flexibility, and turn-around time. Research laboratories seeking to identify new variants by screening large numbers of variants are drawn to using next generation sequencing (NGS) for their PGx applications. Microarrays also serve as a suitable technology to cover a wide range of targets and are often used in predictive genomics applications, or other programs focused on discovery. However, both technologies require highly trained operators and relatively long turnaround times.
Utilizing the power of quantitative real time PCR (qPCR) technology for PGx applications streamlines the diagnostic and management pathway, making it efficient, accurate, and cost-effective. The technology is optimized to support single nucleotide polymorphisms (SNPs), insertion/deletion (indel) variants, and copy number variations (CNVs). Importantly, modern qPCR applications are highly scalable from single target/gene to large panel screening with over 100 targets. PGx testing can be performed on the same PCR infrastructure used for other diagnostic areas.
Personalized treatment regimens are the future of healthcare. Pharmacogenomics determines the patient’s genetic profile to determine the most appropriate treatment on a personal level. PGx helps protect patients from harmful side effects and reduces serious adverse drug reactions. It also helps improve treatment effectiveness and optimizes treatment outcomes. Economically, PGx has the potential to lower overall healthcare costs, and is supported using qPCR technology.