A growing number of geneticists are using genome-wide association studies (GWAS) to systematically search for and identify single nucleotide polymorphisms (SNPs), which are single base changes in the human DNA sequence that can cause differences in genetic characteristics. GWAS may also detect genes that are associated with a particular health condition, or with variation in patient response to prescribed drugs.
In this session, Ralph E. McGinnis, Ph.D., a Statistical Geneticist at the Wellcome Trust Sanger Institute (Cambridge, UK), will discuss the results of new research that that he and his colleagues have recently completed which extends this genome-wide association scan (GWAS) method to investigate the genetic aspects of drug response (pharmacogenetics) related to predicting appropriate warfarin dose.
Warfarin is the most widely prescribed drug used to reduce blood clotting in order to protect high-risk patients from experiencing a stroke, deep vein thrombosis, pulmonary embolism, heart attack, or other serious coronary malfunction. However, a combination of genetic and non-genetic factors can cause patients to exhibit 10- to 20-fold variation in the required dose (RD) of warfarin needed to achieve an adequate level of blood thinning, which means that initial prescribed doses may be too low (risking blood clots and/or failure to protect the patient from developing life-threatening health conditions, such as stroke or heart attack) or too high (risking over-anticoagulation and severe bleeding). Therefore, associated SNPs and genes that are related to dose variation requirements could be used to better estimate the proper warfarin dose based on a patient's genetic makeup, thereby reducing the risk of adverse events caused by inappropriate dosing.
McGinnis' research team were among the first to show that a polymorphism in the warfarin drug target VKORC1 accounts for a major portion (~30%) of the variance in RD, and they have recently evaluated 1,523 Swedish patients from the Warfarin Genetics (WARG) cohort in the largest study to date showing likely patient benefit from genetic forecasting of RD. In this study, the researchers found that the strongest signals were clustered around VKORC1 (the gene of the warfarin drug target), and the second strongest signals were located at SNPs clustering in the warfarin-metabolizing gene CYP2C9.
Mc Ginnis and colleagues conducted additional analyses that tested each GWAS SNP's influence on warfarin dose after adjusting for the influence of already known genetic (VKORC1, CYP2C9) and non-genetic (age, gender, etc.) factors. These analyses identified another statistical signal with genome-wide significance that corresponded to a SNP that changes the protein coding sequence of the CYP4F2 gene. This finding was confirmed in a study of 588 additional Swedish patients.
In summary, the current research results suggest that the proportion of dose variation explained by known genetic factors is approximately 29% (VKORC1), 11% (CYP2C9) and 1.5% (CYP4F2). Furthermore, by also taking into account the around 15% contribution of non-genetic factors such as age and gender, researchers can predict at least 50% of warfarin dose variation, making pre-treatment dose forecasting for individual patients a realistic possibility.
Ralph E. McGinnis, Ph.D., is a Statistical Geneticist at the Wellcome Trust Sanger Institute (Cambridge, UK) whose research focus is identifying genes and DNA variants that cause complex genetic disease or alter response to therapeutic drugs (pharmacogenetics). He has recently analyzed data for genome-wide or large-scale association studies of celiac disease, coronary artery disease, type 1 diabetes, and response to warfarin.
This research was presented at the 58th Annual Meeting of The American Society of Human Genetics (ASHG) in Philadelphia, Pennsylvania on November 11-15, 2008.
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