This K01 aims to achieve Dr. Casey Dorr?s objective to become an independent scientist while improving clinical outcomes via genetic epidemiology. Dr. Dorr will: A) Develop genetic epidemiology skills for pharmacogenomics research B) Develop skills in bioinformatics and statistical modeling through formal education and C) Validate epidemiologically identified genetic variants. In the future, these skills will be used to analyze large genetic epidemiology data sets, translate them into dosing models for other drugs, and for cell culture validation studies. Dr. Dorr?s advisory committee is led by his primary, epidemiology and nephrology, mentor, Dr. Ajay Israni, the Deputy Director of the Scientific Registry of Transplant Recipients (SRTR). Co- mentor Dr. Pamala Jacobson will advise on dosing models, pharmacogenomics and precision medicine. Other committee members include: Dr. Bertram Kasiske, Chief of Nephrology at Hennepin County Medical Center, SRTR Director with clinical trials and outcomes research expertise, and Drs. Claudia Neuhauser and Baolin Wu, with statistical modeling and bioinformatics expertise. African Americans (AAs) have worse allograft survival than Caucasians. For narrow therapeutic index drugs, like tacrolimus (Tac), the primary immune suppressant used in solid organ transplantation, inadequate dosing results in allograft rejection and overdosing results in toxicity. Also, intrapatient variability (IPV) of Tac blood concentrations leads to poor outcomes. By identifying and validating the genetic variants that alter drug metabolism, clinicians can select optimal doses to reduce the risk for adverse drug reactions and IPV. Three common CYP3A (drug metabolism enzyme family) variants that alter function were recently identified in our large genome-wide association study of AA kidney transplant patients but only able to explained ~50% of the total variation in Tac metabolism even after accounting for clinical factors. This project aims to understand the variation in Tac metabolism, a model CYP3A substrate, in an AA kidney transplant population. I hypothesize that low-frequency variants in the CYP3A genes (Aim 1), or in non-CYP3A genes associated with Tac (Aim 2), are critical for determining the appropriate Tac dosage. Tac is a model CYP3A drug for developing personalized dosing in precision medicine as blood concentrations are routinely monitored in kidney transplant recipients. Using an extreme phenotype sampling model of AA renal recipients with the highest and lowest Tac blood concentrations (accounting for common genetic variants and clinical factors) we will identify low-frequency variants in the CYP3A gene locus, and genes that influence Tac transport, CYP3A expression or activity using next generation sequencing. Identified variants will be analyzed in silico to identify functional variants. Variants, associated with Tac metabolism, will be validated by engineering into cultured cells via CRISPR technology. We will use cell culture assays to functionally validate variants. Identification and validation of genetic variants associated with Tac metabolism will lead to better Tac dosing models aimed at improving transplant outcomes.
The goal of this genetic epidemiology proposal is to identify and validate genetic variants associated with metabolism of Tacrolimus which is the primary immune suppressant used in transplantation. Since African Americans have worse kidney allograft survival, in part due to increased Tacrolimus metabolism, this project will determine these genetic variants in African American kidney transplant patients using an extreme phenotype sampling model and next generation sequencing, then validate the variants in cell culture assays. The data from this project will lead to personalized dosing models that account for clinical factors, aimed at improving disparities in clinical outcomes.
