There is marked variability in drug response among individuals. This variability poses a major clinical problem by causing decreased drug efficacy or unexpected toxicity. The ability to incorporate predictors of drug efficacy or toxicity into clinical practice would be a major advance. Well-defined genetic variations in drug metabolizing enzymes or drug targets contribute to variability in drug concentration and therefore response. These pharmacogenetic findings define a predictable component of variability in drug response among individuals. However, despite intensive research and robust findings, there has been almost no translation of pharmacogenetic findings into clinical practice. A critical barrier is that the importance of pharmacogenetics has not been demonstrated for important patient outcomes in clinical practice. It is not feasible perform a randomized clinical trial to test the clinical importance of every pharmacogenetic question. We propose a novel approach: to use an electronic medical record (EMR) with de-identified information linked to a DNA biobank to test the clinical importance of pharmacogenetic findings for important outcomes of drug therapy in clinical practice. We will implement this novel approach, demonstrating proof-of-principle for three distinct pharmacogenetic findings. These have been chosen for study because there is already overwhelming evidence of an effect on drug metabolism, and consequently pharmacokinetic or pharmacodynamic measures, but genotyping is not yet routine in clinical care. We will test the hypotheses that: 1) CYP2C9 and VKORC1 variants associated with reduced warfarin dose-requirements are associated with greater fluctuation in INR after the warfarin dose-titration phase;2) CYP2C9 variants with reduced function are associated with more frequent hypoglycemia with sulfonylureas;3) CYP2D6 poor- and intermediate-metabolizer patients have reduced analgesic effects after receiving codeine for pain. Our approach is to define clinically important pharmacogenetic questions and to test their clinical importance using a combination of bioinformatic, epidemiologic and genetic expertise in a large EMR of more than 1.5 million patients linked to a DNA bank of >157,719 DNA samples. These studies will have high public health impact, not only in translating pharmacogenetic findings to improved patient care for the drugs studied, but also in developing new approaches to testing the importance of future pharmacogenetic observations in clinical practice.

Public Health Relevance

Genetic factors are a critical component of differences among individuals in how they respond to drugs - a major cause of morbidity and mortality in the United States. The proposed research is of great public health importance because identifying individuals with particular genetic variants, and altering their drug therapy accordingly, could markedly increase drug efficacy and reduce toxicity. Thus, the work is highly relevant to NIH's mission of applying innovative research strategies for protecting and improving health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM109145-01
Application #
8621350
Study Section
Xenobiotic and Nutrient Disposition and Action Study Section (XNDA)
Program Officer
Okita, Richard T
Project Start
2014-01-01
Project End
2017-12-31
Budget Start
2014-01-01
Budget End
2014-12-31
Support Year
1
Fiscal Year
2014
Total Cost
$281,700
Indirect Cost
$101,700
Name
Vanderbilt University Medical Center
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212
Chaugai, Sandip; Dickson, Alyson L; Shuey, Megan M et al. (2018) Co-Prescription of Strong CYP1A2 Inhibitors and the Risk of Tizanidine-Associated Hypotension: A Retrospective Cohort Study. Clin Pharmacol Ther :
Feng, QiPing; Wei, Wei-Qi; Levinson, Rebecca T et al. (2017) Replication and fine-mapping of genetic predictors of lipid traits in African-Americans. J Hum Genet 62:895-901
Johnson, J A; Caudle, K E; Gong, L et al. (2017) Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Pharmacogenetics-Guided Warfarin Dosing: 2017 Update. Clin Pharmacol Ther 102:397-404
Feng, Q; Wei, W Q; Chung, C P et al. (2017) The effect of genetic variation in PCSK9 on the LDL-cholesterol response to statin therapy. Pharmacogenomics J 17:204-208
Choi, Leena; Ferrell, Benjamin A; Vasilevskis, Eduard E et al. (2016) Population Pharmacokinetics of Fentanyl in the Critically Ill. Crit Care Med 44:64-72
Iwuchukwu, Otito F; Ramirez, Andrea H; Shi, Yaping et al. (2016) Genetic determinants of variability in warfarin response after the dose-titration phase. Pharmacogenet Genomics 26:510-516
Mosley, Jonathan D; Witte, John S; Larkin, Emma K et al. (2016) Identifying genetically driven clinical phenotypes using linear mixed models. Nat Commun 7:11433
Birdwell, K A; Decker, B; Barbarino, J M et al. (2015) Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines for CYP3A5 Genotype and Tacrolimus Dosing. Clin Pharmacol Ther 98:19-24
Vear, Susan I; Ayers, Gregory D; Van Driest, Sara L et al. (2014) The impact of age and CYP2C9 and VKORC1 variants on stable warfarin dose in the paediatric population. Br J Haematol 165:832-5
Kawai, Vivian K; Cunningham, Andrew; Vear, Susan I et al. (2014) Genotype and risk of major bleeding during warfarin treatment. Pharmacogenomics 15:1973-83

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