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Use of biological knowledge to inform the analysis of gene-gene interactions involved in modulating virologic failure with efavirenz-containing treatment regimens in ART-naive ACTG clinical trials participants.

ABSTRACT: Personalized medicine is a high priority for the future of health care. The idea of tailoring an individual's wellness plan to their unique genetic code is one which we hope to realize through the use of pharmacogenomics. There have been examples of tremendous success in pharmacogenomic associations however there are many such examples in which only a small proportion of trait variance has been explained by the genetic variation. Although the increased use of GWAS could help explain more of this variation, it is likely that a significant proportion of the genetic architecture of these pharmacogenomic traits are due to complex genetic effects such as epistasis, also known as gene-gene interactions, as well as gene-drug interactions. In this study, we utilize the Biofilter software package to look for candidate epistasis contributing to risk for virologic failure with efavirenz-containing antiretroviral therapy (ART) regimens in treatment-naïve participants of AIDS Clinical Trials Group (ACTG) randomized clinical trials. A total of 904 individuals from three ACTG trials with data on efavirenz treatment are analyzed after race-stratification into white, black, and Hispanic ethnic groups. Biofilter was run considering 245 candidate ADME (absorption, distribution, metabolism, and excretion) genes and using database knowledge of gene and protein interaction networks to produce approximately 2 million SNP-SNP interaction models within each ethnic group. These models were evaluated within the PLATO software package using pair wise logistic regression models. Although no interaction model remained significant after correction for multiple comparisons, an interaction between SNPs in the TAP1 and ABCC9 genes was one of the top models before correction. The TAP1 protein is responsible for intracellular transport of antigen to MHC class I molecules, while ABCC9 codes for a transporter which is part of the subfamily of ABC transporters associated with multi-drug resistance. This study demonstrates the utility of the Biofilter method to prioritize the search for gene-gene interactions in large-scale genomic datasets, although replication in a larger cohort is required to confirm the validity of this particular TAP1-ABCC9 finding.

SUBMITTER: Grady BJ

PROVIDER: S-EPMC3094912 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Use of biological knowledge to inform the analysis of gene-gene interactions involved in modulating virologic failure with efavirenz-containing treatment regimens in ART-naïve ACTG clinical trials participants.

Grady Benjamin J BJ Torstenson Eric S ES McLaren Paul J PJ DE Bakker Paul I W PI Haas David W DW Robbins Gregory K GK Gulick Roy M RM Haubrich Richard R Ribaudo Heather H Ritchie Marylyn D MD

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 20110101

Personalized medicine is a high priority for the future of health care. The idea of tailoring an individual's wellness plan to their unique genetic code is one which we hope to realize through the use of pharmacogenomics. There have been examples of tremendous success in pharmacogenomic associations however there are many such examples in which only a small proportion of trait variance has been explained by the genetic variation. Although the increased use of GWAS could help explain more of this ...[more]

PMID: 21121053

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Project description:Efavirenz, a non-nucleoside reverse-transcriptase inhibitor (NNRTI) is one of the most commonly prescribed antiretroviral drugs. The present article provides a systematic overview and meta-analysis of clinical trials comparing efavirenz and other active drugs currently recommended for treatment of HIV-infected, antiretroviral-naive patients. Electronic databases (Pubmed, Embase, the Cochrane Library, Trip Database) were searched up till 23 December 2013 for randomized controlled clinical trials published as a peer-reviewed papers, and concerning efavirenz-based regimens used as initial treatment for HIV infection. Thirty-four studies were included in the systematic review, while twenty-six trials were suitable for the meta-analysis. Efavirenz was compared with drugs from four different classes: NNRTIs other than efavirenz (nevirapine or rilpivirine), integrase strand transfer inhibitors (InSTIs), ritonavir-boosted protease inhibitors (bPI) and chemokine (C-C motif) receptor 5 (CCR5) antagonists (maraviroc), all of them were added to the background regimen. Results of the current meta-analysis showed that efavirenz-based regimens were equally effective as other recommended regimens based on NNRTI, ritonavir-boosted PI or CCR5 antagonist in terms of efficacy outcomes (disease progression and/or death, plasma viral HIV RNA <50 copies/ml) while statistically significant more patients treated with InSTI achieved plasma viral load <50 copies/ml at week 48. In comparison with both InSTI-based and CCR5-based therapy, efavirenz-based treatment was associated with a higher risk of therapy discontinuation due to adverse events. However, comparisons of efevirenz-based treatment with InSTI-based and CCR5-based therapy were based on a limited number of trials, therefore, conclusions from these two comparisons must be confirmed in further reliable randomized controlled studies. Results of our meta-analysis support the present clinical guidelines for antiretroviral-naive, HIV-infected patients, in which efavirenz is one of the most preferred regimens in the analyzed population. Beneficial safety profile of InSTI-based and CCR5-based therapy over efavirenz-based treatment needs further studies.

Dataset Information

Use of biological knowledge to inform the analysis of gene-gene interactions involved in modulating virologic failure with efavirenz-containing treatment regimens in ART-naive ACTG clinical trials participants.

Publications

Use of biological knowledge to inform the analysis of gene-gene interactions involved in modulating virologic failure with efavirenz-containing treatment regimens in ART-naïve ACTG clinical trials participants.

Similar Datasets

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