Mentored Scientist Award

Evaluating Genetic Factors Associated with Tenofovir Exposure in HIV-Infected Women Undergoing Intensive Pharmacokinetic Monitoring

Recipient
Award mentor
Award date
2013
Award cycle
Fall
Award amount - Direct
40,000.00

Abstract

Tenofovir disoproxil fumarate (TDF) is used commonly in HIV treatment and prevention settings, but factors that correlate with TDF exposure are unknown. Recent data have identified clinical factors that are associated with renal toxicity related to TDF and elevated TDF area-under-the-curve (AUC) concentrations. An elevated AUC, as a robust measure of drug exposure, is hypothesized to contribute to TDF-related kidney disease, but this has yet to be definitively shown. Furthermore, genetic factors underlying elevations in TDF AUC have not been delineated. This study will assess the genetic factors associated with elevated TDF AUC in 101 HIV infected women who underwent intensive pharmacokinetic studies of TDF over 24-hours at steady state. We will test the hypotheses that 1) genetic factors contribute to elevated TDF exposure, and 2) high TDF exposure during intensive PK sampling will be associated with kidney injury over time, when controlling for clinical factors that vary over time and influence exposure. Specimen collection is complete and TDF AUC has been determined; this study will identify genetic contributors to TDF AUC through analysis of single nucleotide polymorphisms (SNPs), identified by exhaustive literature review, that are associated with TDF metabolism. This study will be completed in one year and leverages the existing extensive research infrastructure of the NIH-funded Women?s Interagency HIV Study (WIHS) cohort, including mentorship by UCSF WIHS-associated investigators with expertise in antiretroviral pharmacokinetics, clinical research, pharmacogenetics, epidemiology and biostatistics. Analysis will include multivariate regression models estimating the association of TDF AUC with SNPs while controlling for clinical covariates with confirmation of linearity. Ultimately, this work will guide the development of a clinically relevant predictive model using clinical and genetic factors to identify patients at risk for TDF associated renal toxicity. The results of this research will provide preliminary data to support an NIH mentored K23 career development award.