Although the efficacy of warfarin in the treatment and prevention of thromboembolic disorders (TEDs) is proven, it is vastly underutilized with difficulties in management &risk of complications being the main deterrents. Recognition of genetic regulation of warfarin response has fueled efforts to quantify this influence, but the focus has been restricted to select genes and outcomes mainly in Caucasians. Our effort in understanding genetic influences on warfarin response began in 2003 with a K23 grant (NS045598): Pharmacogenetic Optimization of Anticoagulation Therapy (POAT). Although this training grant focused on evaluating the influence of a single gene;cytochrome P450 2C9 (CYP2C9) genotype on warfarin dose, frequency of International Normalized Ratio (INR) outside target range, and risk of complications, the cohort provides a valuable racially diverse resource to expand our pharmacogenetic effort. The POAT cohort is, to our knowledge the largest prospective cohort (n=578, 51% men, 273 African Americans (AA)) with a 2-year longitudinal follow-up from initiation of therapy. This proposal will further the aims of POAT using a comprehensive pharmacogenetic approach in a cohort of 1200 participants (50% AA) powered (>80%, alpha=0.001) to test three hypotheses. This proposal will incorporate 50 genes involved in the clotting cascade, vitamin K cycle, and warfarin pharmacodynamics and pharmacokinetics. Non-genetic covariates will include socio-demographics, lifestyle, diet, and medical characteristics.
Aim 1 will assess the relative effects of genetic and non-genetic covariates on warfarin dose.
Aim 2 will assess the contribution of candidate genes in determining attainment and maintenance of anticoagulation and risk of over- anticoagulation (INR >4).
Aim 3 will determine the association between candidate genes and risk of hemorrhage or thromboembolism. The study will also explore gene*gene and gene*non-genetic covariate interactions. We anticipate that the results of this study will further elucidate the genetic contributions of warfarin response, provide novel genetic associations of treatment response in a previously understudied population, namely, African Americans. This knowledge will provide an evidence base for future pre-prescription genotyping for accurate warfarin dosing and facilitate its use in qualifying patients.
|French, Benjamin; Wang, Le; Gage, Brian F et al. (2016) A systematic analysis and comparison of warfarin initiation strategies. Pharmacogenet Genomics 26:445-52|
|Limdi, Nita A; Howard, Virginia J; Higginbotham, John et al. (2016) US Mortality: Influence of Race, Geography and Cardiovascular Risk Among Participants in the Population-Based REGARDS Cohort. J Racial Ethn Health Disparities 3:599-607|
|Ather, Sameer; Shendre, Aditi; Beasley, T Mark et al. (2016) Effect of Left Ventricular Systolic Dysfunction on Response to Warfarin. Am J Cardiol 118:232-6|
|Shendre, Aditi; Brown, Todd M; Liu, Nianjun et al. (2016) Race-Specific Influence of CYP4F2 on Dose and Risk of Hemorrhage Among Warfarin Users. Pharmacotherapy 36:263-72|
|Boehme, Amelia K; Pamboukian, Salpy V; George, James F et al. (2015) Predictors of Thromboembolic Events in Patients with Ventricular Assist Device. ASAIO J 61:640-7|
|Yan, Qi; Weeks, Daniel E; CeledÃ³n, Juan C et al. (2015) Associating Multivariate Quantitative Phenotypes with Genetic Variants in Family Samples with a Novel Kernel Machine Regression Method. Genetics 201:1329-39|
|Liu, Nianjun (2015) QTL mapping - Current status and challenges: Comment on "Mapping complex traits as a dynamic system" by L. Sun and R. Wu. Phys Life Rev 13:194-5|
|Parra, Esteban J; Botton, Mariana R; Perini, Jamila A et al. (2015) Genome-wide association study of warfarin maintenance dose in a Brazilian sample. Pharmacogenomics 16:1253-63|
|Yan, Qi; Weeks, Daniel E; Tiwari, Hemant K et al. (2015) Rare-Variant Kernel Machine Test for Longitudinal Data from Population and Family Samples. Hum Hered 80:126-38|
|Thigpen, Jonathan L; Dillon, Chrisly; Forster, Kristen B et al. (2015) Validity of international classification of disease codes to identify ischemic stroke and intracranial hemorrhage among individuals with associated diagnosis of atrial fibrillation. Circ Cardiovasc Qual Outcomes 8:8-14|
Showing the most recent 10 out of 35 publications