The use of warfarin, although widely accepted for ischemic stroke prevention, is hindered by factors influencing its efficacy and toxicity. Warfarin is metabolized by Cytochrome P4502C9 (CYP2C9). There are several CYP2C9 alleles, which encode for enzymes with different catalytic activity. These have been documented for CYP2C9*1, CYP2C9*2, and CYP2C9*3. Recently three additional alleles have been identified: CYP2C9*4, CYP2C9*5, and CYP2C9*6 the latter two in African -Americans. The primary hypothesis of the study is that the CYP2C9 genotype influences the dose of warfarin required to maintain anticoagulation and the variability in INR control. The secondary hypothesis is that patients carrying variant alleles are at a higher risk for hemorrhagic complications. Conversely the patients who carry the normal allele may be at a higher risk of recurrent thromboembolic events. These hypotheses will be tested in a cohort of 500 stroke patients, including African-Americans. Patients will be identified prior to initiation of therapy and followed for 2 years. The study will establish the association between genotype and warfarin dose and the association between genotype and the frequency of INRs outside target range and the risk of associated complications both hemorrhagic and thromboembolic. Multivariate analysis will evaluate the association of CYP2C9 genotype-warfarin dose and genotype-INRs outside target range and associated complications both hemorrhagic and thromboembolic. Confounding variables - drug interactions, co-morbid conditions, and compliance will be statistically controlled. The advantage of defining CYP2C9 genotype will increase precision of warfarin dosing, achieve therapeutic anticoagulation earlier, minimize variability in INR, decrease the risk of thromboembolic/hemorrhagic events and reduce health care costs. My career goals are to investigate the influence of genetics on drug response. With the award of the K23 grant, structured training, guidance of mentors, environment and institutional support provided by the University, I will develop the skills necessary for a productive career in pharmacogenetics research.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Mentored Patient-Oriented Research Career Development Award (K23)
Project #
5K23NS045598-03
Application #
6855108
Study Section
NST-2 Subcommittee (NST)
Program Officer
Gwinn, Katrina
Project Start
2003-05-01
Project End
2008-02-28
Budget Start
2005-03-01
Budget End
2006-02-28
Support Year
3
Fiscal Year
2005
Total Cost
$158,958
Indirect Cost
Name
University of Alabama Birmingham
Department
Neurology
Type
Schools of Medicine
DUNS #
063690705
City
Birmingham
State
AL
Country
United States
Zip Code
35294
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
Shendre, Aditi; Beasley, Timothy Mark; Brown, Todd M et al. (2014) Influence of regular physical activity on warfarin dose and risk of hemorrhagic complications. Pharmacotherapy 34:545-54
Daneshjou, Roxana; Tatonetti, Nicholas P; Karczewski, Konrad J et al. (2013) Pathway analysis of genome-wide data improves warfarin dose prediction. BMC Genomics 14 Suppl 3:S11
Perera, Minoli A; Cavallari, Larisa H; Limdi, Nita A et al. (2013) Genetic variants associated with warfarin dose in African-American individuals: a genome-wide association study. Lancet 382:790-6
Limdi, Mohit A; Crowley, Michael R; Beasley, T Mark et al. (2013) Influence of kidney function on risk of hemorrhage among patients taking warfarin: a cohort study. Am J Kidney Dis 61:354-7
Limdi, Nita A (2012) Warfarin pharmacogenetics: challenges and opportunities for clinical translation. Front Pharmacol 3:183
Horne, Benjamin D; Lenzini, Petra A; Wadelius, Mia et al. (2012) Pharmacogenetic warfarin dose refinements remain significantly influenced by genetic factors after one week of therapy. Thromb Haemost 107:232-40
Liu, Nianjun; Zhao, Hongyu; Patki, Amit et al. (2011) Controlling Population Structure in Human Genetic Association Studies with Samples of Unrelated Individuals. Stat Interface 4:317-326
Cosgun, Erdal; Limdi, Nita A; Duarte, Christine W (2011) High-dimensional pharmacogenetic prediction of a continuous trait using machine learning techniques with application to warfarin dose prediction in African Americans. Bioinformatics 27:1384-9
Zhang, Boshao; Zhi, Degui; Zhang, Kui et al. (2011) Practical Consideration of Genotype Imputation: Sample Size, Window Size, Reference Choice, and Untyped Rate. Stat Interface 4:339-352

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