Access to potent antiretroviral drugs markedly reduces acquired immunodeficiency syndrome (AIDS) morbidity and mortality. However, there is considerable interindividual variability in response to human immunodeficiency virus type 1 (HIV-1) therapy regarding both efficacy and toxicity. Variable responses to medications are influenced, at least in part, by frequent human genetic variants that affect drug metabolism and drug disposition. Because suboptimal response can have devastating consequences for individuals and populations, defining the predictive value of human genetics for HIV treatment response has far-reaching implications. The pace of genomic discovery relevant to HIV therapeutics has been relatively slow and fragmented. Efficiently moving HIV pharmacogenomics from bench to bedside to community will be greatly facilitated by an approach that spans antiretroviral drugs and drug classes so that persons affected by HIV worldwide may benefit from the human genomic revolution. The proposed studies will determine the utility of human pharmacogenomic testing for clinical HIV care. The overarching hypothesis is that knowledge of associations between human genetic variants and HIV treatment responses will improve HIV treatment outcomes. This proposal will focus on genes relevant to drug absorption, distribution, metabolism, and elimination (ADME), complemented by selected non-ADME polymorphisms. This will be accomplished through analyses of data and DNA from over 5,000 participants from prospective clinical trials. Predictive models for responses to antiretroviral therapies will be developed based on knowledge of human genetic variants. Results of these analyses may also inform the design of a prospective randomized clinical trial to test whether HIV treatment responses will improve when human genetic testing informs prescribing. This work may ultimately result in better individualized therapy (personalized medicine), and improved antiretroviral treatment guidelines for persons living in resource-limited countries worldwide. To maximize impact and value added, this project will be a platform for collaboration with other investigators.

Public Health Relevance

The AIDS pandemic is one of the greatest public health infectious diseases challenges in history. There are approximately 1 million individuals in the US and 40 million worldwide living with HIV/AIDS. Understanding how human genetic differences predict treatment response to HIV medications may help inform public health policy decisions about the safest and most effective use of antiretroviral regimens in the US and worldwide.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI077505-03
Application #
7885540
Study Section
Special Emphasis Panel (ZRG1-AARR-D (03))
Program Officer
Zhang, Hao
Project Start
2008-07-08
Project End
2013-06-30
Budget Start
2010-07-01
Budget End
2011-06-30
Support Year
3
Fiscal Year
2010
Total Cost
$791,158
Indirect Cost
Name
Vanderbilt University Medical Center
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212
Verma, Shefali Setia; Ritchie, Marylyn D (2018) Another Round of ""Clue"" to Uncover the Mystery of Complex Traits. Genes (Basel) 9:
Martin, Maureen P; Naranbhai, Vivek; Shea, Patrick R et al. (2018) Killer cell immunoglobulin-like receptor 3DL1 variation modifies HLA-B*57 protection against HIV-1. J Clin Invest 128:1903-1912
Verma, Anurag; Bradford, Yuki; Dudek, Scott et al. (2018) A simulation study investigating power estimates in phenome-wide association studies. BMC Bioinformatics 19:120
Haas, David W; Bradford, Yuki; Verma, Anurag et al. (2018) Brain neurotransmitter transporter/receptor genomics and efavirenz central nervous system adverse events. Pharmacogenet Genomics 28:179-187
Hulgan, Todd; Dash, Chandravanu; Haas, David W et al. (2018) Precision HIV care: responding to old questions and meeting new challenges. Pharmacogenomics 19:1299-1302
Li, Binglan; Verma, Shefali S; Veturi, Yogasudha C et al. (2018) Evaluation of PrediXcan for prioritizing GWAS associations and predicting gene expression. Pac Symp Biocomput 23:448-459
Leger, Paul; Chirwa, Sanika; Nwogu, Jacinta N et al. (2018) Race/ethnicity difference in the pharmacogenetics of bilirubin-related atazanavir discontinuation. Pharmacogenet Genomics 28:1-6
Pavlos, Rebecca; McKinnon, Elizabeth J; Ostrov, David A et al. (2017) Shared peptide binding of HLA Class I and II alleles associate with cutaneous nevirapine hypersensitivity and identify novel risk alleles. Sci Rep 7:8653
Verma, Anurag; Ritchie, Marylyn D (2017) Current Scope and Challenges in Phenome-Wide Association Studies. Curr Epidemiol Rep 4:321-329
Leitman, Ellen M; Willberg, Christian B; Tsai, Ming-Han et al. (2017) HLA-B*14:02-Restricted Env-Specific CD8+ T-Cell Activity Has Highly Potent Antiviral Efficacy Associated with Immune Control of HIV Infection. J Virol 91:

Showing the most recent 10 out of 65 publications