4.2 Article

The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients

Journal

PHARMACOGENETICS AND GENOMICS
Volume 22, Issue 1, Pages 32-42

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/FPC.0b013e32834e1641

Keywords

calcineurin inhibitor; cytochrome P4503A5; dosing; electronic medical records; genetic polymorphism; kidney transplant; pharmacogenomics; pharmacokinetics; tacrolimus

Funding

  1. National Center for Research Resources/National Institutes of Health [1UL1RR024975-01]
  2. Vanderbilt Ingram Cancer Center [P30 CA68485]
  3. Vanderbilt Digestive Disease Center [P30 DK58404]
  4. Vanderbilt Vision Center [P30 EY08126]
  5. Vanderbilt Clinical and Translational Science Award
  6. Vanderbilt Electronic Systems for Pharmacogenomic Assessment [RC2 GM092618]
  7. Vanderbilt Physician Scientist Development Program (Birdwell) [R21 AG034412]
  8. Boehringer-Ingelheim
  9. Bristol-Myers Squibb
  10. Gilead Sciences
  11. Merck
  12. [R01 AI077505]

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Objective Tacrolimus, an immunosuppressive drug widely prescribed in kidney transplantation, requires therapeutic drug monitoring due to its marked interindividual pharmacokinetic variability and narrow therapeutic index. Previous studies have established that CYP3A5 rs776746 is associated with tacrolimus clearance, blood concentration, and dose requirement. The importance of other drug absorption, distribution, metabolism, and elimination (ADME) gene variants has not been well characterized. Methods We used novel DNA biobank and electronic medical record resources to identify ADME variants associated with tacrolimus dose requirement. Broad ADME genotyping was performed on 446 kidney transplant recipients, who had been dosed to a steady state with tacrolimus. The cohort was obtained from Vanderbilt's DNA biobank, BioVU, which contains linked deidentified electronic medical record data. Genotyping included Affymetrix drug-metabolizing enzymes and transporters Plus (1936 polymorphisms), custom Sequenom Massarray iPLEX Gold assay (95 polymorphisms), and ancestry-informative markers. The primary outcome was tacrolimus dose requirement defined as blood concentration to dose ratio. Results In analyses, which adjusted for race and other clinical factors, we replicated the association of tacrolimus blood concentration to dose ratio with CYP3A5 rs776746 (P=7.15 x 10(-29)), and identified associations with nine variants in linkage disequilibrium with rs776746, including eight CYP3A4 variants. No NR1I2 variants were significantly associated. Age, weight, and hemoglobin were also significantly associated with the outcome. In final models, rs776746 explained 39% of variability in dose requirement and 46% was explained by the model containing clinical covariates. Conclusion This study highlights the utility of DNA biobanks and electronic medical records for tacrolimus pharmacogenomic research. Pharmacogenetics and Genomics 22: 32-42 (C) 2011 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins.

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