The transition of both genomics and personalized medicine from the realms of research into mainstream clinical care has begun. As the concept of integrated personalized medicine becomes a reality, genomic and molecular tests that could potentially guide providers in making clinical decisions are being validated and approved for use by professional bodies and federal agencies. There are three major conceptual areas of personalized medicine translation characterized by different opportunities, challenges, and current progress: pharmacogenomics, common disease risk prediction, and rare diseases defined by a prevalence of less than 0.05%.
The first wave of clinically useful genomic variants that have started to gain acceptance are those associated with response to medication. Pharmacogenomics is the field of genomics that deals with how individual genetic variation may play a role in that individual’s response to a medication. This variability in response can range from complete lack of effect to reduced efficacy to serious adverse drug reactions. To date, there are more than 30 commonly prescribed drugs that have had their FDA-label modified to include information about pharmacogenomics, with new amendments to existing drugs being considered. Pharmacogenomic-guided prescribing has significant potential for reducing adverse drug reactions (ADRs) and increasing therapeutic efficacy. For example, it has been shown that loss-of-function polymorphisms in the hepatic cytochrome CYP2C19 enzyme, which metabolizes clopidogrel (Plavix) from its inactive prodrug to its active metabolite, are responsible for variations in rates of stent thrombosis following percutaneous interventions for obstructive coronary artery disease. Loss of function was associated with a greater than threefold increase in the risk of stent thrombosis and death at 1 year. In addition it has been demonstrated that genome-guided prescribing can reduce adverse events and save costs simultaneously. Abacavir, a commonly used HIV medication is known to cause severe hypersensitivity in 4% to 8% of patients. HLA B*5701 is a known genetic risk factor for abacavir hypersensitivity in Caucasians and in a cost-saving analysis, genotype-guided prescribing reduced the incidence of hypersensitivity reactions, offering cost savings of approximately $29,000 per patient.
Common Disease Risk Prediction and Personalized Preventive Medicine
Though pharmacogenomics represents the first-wave of genomic medicine that can be integrated into routine clinical care, reports evaluating the clinical utility of genomic risk prediction models for common diseases are just beginning to emerge. For example, a recent study that used a risk-weighted, multilocus genetic risk score based on a 13-SNP panel was able to identify individuals who were at an approximately 70% increased risk of a first coronary heart disease event. Perhaps most encouraging is the finding that the genetic risk score was able to improve risk reclassification in individuals who were at intermediate risk based on traditional risk assessed by Framingham risk score. The 13-SNP panel-based reclassification shifted 15% to 20% of individuals above or below treatment thresholds for lipid-lowering drugs recommended in current practice guidelines and thus potentially altered their treatment. Similar scores have been tested in type 2 diabetes. The major challenge for efforts to develop improved diagnostic and prognostic tools for common diseases lies in the modest effect sizes of the common variants so far discovered and therefore the limited proportion of heritable variance, which they explain. Thus, at the time of this writing, clinical application of genomic risk scores to predict incident diseases is still investigational. It is hoped and anticipated that with advances in genotyping technology and the discovery of rarer variants of larger effect, tests will emerge to estimate an individual’s risk for developing a disease, such as type 2 diabetes or heart disease. It is hoped that addition of validated genomic variant information will improve the ability of established risk prediction models to accurately assess the likelihood of onset of a common disease in an individual in the future. Anticipated personal and public health benefits will be more precise and effective allocation of primary prevention strategies and discovery and efficient evaluation of new preventive interventions. This will usher in the promise of true preventive medicine.
The application of genomics in rare diseases, defined by a population prevalence of <0.05%, will be driven by the increasingly affordable ability to interrogate the sequence of all coding regions (exons) or the entire genome of individuals for mutations that can plausibly underlie manifestations of a rare disease. Thus, with the anticipated rapid spread of whole exome and whole genome sequence information, genomics will likely dramatically redefine the identification and management of thousands of rare diseases.