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

Abstract

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 steady state with tacrolimus. The cohort was obtained from Vanderbilt's DNA biobank, BioVU, which contains linked, de-identified electronic medical record data. Genotyping included Affymetrix DMET 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 that adjusted for race and other clinical factors, we replicated the association of tacrolimus blood concentration-to-dose ratio with CYP3A5 rs776746 (p = 7.15 × 10−29), and identified associations with nine variants in linkage disequilibrium with rs776746, including eight CYP3A4 variants. No NR1/2 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.

Evidence for Extensive Pleiotropy Among Pharmacogenes

“…The coding definition excluded two ICD-9-CM groups: 'nephritis, nephrotic syndrome and nephrosis' (580-589) and 'other diseases of urinary system' (590-599). However, a substantial proportion (11.2%) of patients in this study had undergone a kidney transplant [45,56]. Because of the strong correlation between renal osteodystrophy diagnoses and kidney transplant in this dataset (r ϕ = 0.82, p > 10 -20 ), we retested the association between SLC15A2 rs1143672 and renal osteodystrophy after adjustment for kidney transplant status and found that the association was not significant (p = 0.22).…”

Clinical and Genetic Factors Associated With Cutaneous Squamous Cell Carcinoma in Kidney and Heart Transplant Recipients

“…The kidney transplant population was identified by searching the SD for ICD9 (V42.0 – kidney transplantation) and CPT (50360 and 50365 - renal allotransplantation) codes in those individuals with available DNA in BioVU (13–14) resulting in 859 adult individuals. This population was 41.9% female and 74.6% white, 18.7% African American, 2% Asian, 2% Hispanic (2.7% not racially classified).…”

Pharmacogenetic aspects of the use of tacrolimus in renal transplantation: recent developments and ethnic considerations

“…[31][32][33] However, whether the CYP3A4*1B allele is truly itself responsible for the altered Tac dose requirement remains a matter of debate as this SNP is in linkage disequilibrium with the CYP3A5*1 allele. [34] CYP3A4*22 (rs35599367) is located in intron 6 of CYP3A4 and is a C to T substitution at g.15389. Wang and Sadee [35] demonstrated that CYP3A4*22 increases the formation of the nonfunctional CYP3A4 splice variant with partial intron 6 retention, thereby reducing the production of functional fulllength CYP3A4 mRNA and reduced CYP3A4 enzymatic activity.…”