Access to safe and effective antiretroviral therapy (ART) is a cornerstone in the global struggle against HIV/AIDS, which affects approximately 1 million individuals in the US and 34 million worldwide. There is marked interindividual variability in response to ART regarding drug toxicity, virologic efficacy, and immune recovery. Virtually every antiretroviral is affected by drug absorption, distribution, metabolism, and elimination (ADME), and genetic polymorphisms in ADME genes are known to have functional effects, as do off-target genes. Large effect sizes with ADME and off-target genes often reveal associations with small sample sizes. A challenge in quantifying the impact of human genetic variants on HIV treatment response is that associations are often context dependent. There is great opportunity to accelerate the pace and scope of pharmacogenomic discovery. An exciting new high impact strategy is the phenome-wide association study (PheWAS), which asks whether genetic polymorphisms are associated with one or more clinical traits (i.e. phenotypes) across the entire phenome . PheWAS is largely unbiased regarding phenotypes, and is ideal for interrogating large numbers of context-dependent associations. Large, prospective, randomized clinical trials data offer a unique window to genotype-phenotype associations. This proposal will, for the first time, apply PheWAS to data from prospective clinical trials, and will emphasize context- dependent associations. This will be involve >5,500 individuals who initiated ART in prospective, randomized trials of the AIDS Clinical Trials Group. We will apply a phenome-wide strategy to discover novel associations between genetic polymorphisms, particularly in known ADME genes, and HIV treatment response phenotypes in data from prospective, randomized clinical trials. We will refine and replicate associations, both within and beyond HIV treatment trials datasets. We will also apply simulation modeling and cost-effectiveness analysis to assess the clinical utility of upfront genetic tests to inform antiretroviral prescribing. Our vision is t identify associations that are sufficiently robust to translate into clinical care, and to impact HIV/AIDS worldwide.

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 34 million worldwide living with HIV/AIDS. Understanding how human genetic differences predict treatment response to HIV medications many 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 #
5R01AI077505-09
Application #
9197600
Study Section
AIDS Clinical Studies and Epidemiology Study Section (ACE)
Program Officer
Zhang, Hao
Project Start
2008-07-08
Project End
2019-12-31
Budget Start
2017-01-01
Budget End
2017-12-31
Support Year
9
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Vanderbilt University Medical Center
Department
Type
DUNS #
079917897
City
Nashville
State
TN
Country
United States
Zip Code
37232
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