Tacrolimus (Tac) pharmacogenomics studies have identified common genetic variants that alter Tac troughs and developed specific dosing strategies for specific populations. Known common variants and clinical factors explain ~50% of Tac trough variability (Oetting et al. 2016 AJT 16;2:574–582); this study sought to identify low-frequency variants to better explain this variability. Using well characterized subjects from the Deterioration of Kidney Allograft Function (DeKAF) Genomics cohort we developed an extreme phenotype sampling (EPS) model and targeted next-generation sequencing (NGS) to identify genetic variants associated with extreme Tac troughs. The NGS spanned >3 mB of 28 drug metabolism-associated genes including 20 kB of genomic sequence up and downstream of each gene. The study evaluated Tac troughs in the first 6 months post-kidney transplantation. The study included 12 subjects with the highest, and 12 subjects with the lowest, dose-normalized Tac troughs after accounting for clinical and common genetic variants, from European Americans (n=1442) and African Americans (AA, n=345), resulting in 48 total subjects. NGS identified 18,661 genetic variants. Using variant effect predictor (VEP) analysis we determined that 6,371 (34.1%) of the variants were unknown and 12,290 (65.9%) were known. We identified 125 variants that were deleterious to protein function by Sorting Intolerant from Tolerant (SIFT) and 110 as probably damaging by Polymorphism Phenotyping Tool (PolyPhen). Of these variants, 69 were deleterious on protein function according to both SIFT and PolyPhen prediction. A major finding was identifying a significant association of CYB5R2 with Tac troughs in the AA cohort by sequence kernel association test. The variant, rs61733057, in the CYB5R2 gene was identified and predicted to be deleterious by SIFT and probably damaging by PolyPhen. This study also identified novel variants in CYP3A4, CYP3A5, POR, and CYB3A. While these newly identified variants need validation in cell culture models or validation cohorts, identification of new variants may lead to improved understanding and preemptive prediction of Tac metabolism in transplant recipients and personalized dosing.

CITATION INFORMATION: Dorr C., Wu B., Remmel R., Muthusamy A., Schladt D., Abrahante J., Guan W., Mannon R., Matas A., Oetting W., Jacobson P., Israni A. Identification of Novel Genetic Variants Associated with Tacrolimus Metabolism in Kidney Transplant Recipients Using Next Generation Sequencing Am J Transplant. 2017;17 (suppl 3).

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