Title: Genetic markers for protease inhibitor drug resistance in regions outside of the protease gene
Authors: Giandhari J, Gordon M, van Vuuren C, Moodley P, de Oliveira T.
Journal: Virus Evolution,:doi: 10.1093/ve/vew036.018 (2017)


There are currently 6.8 million individuals infected with HIV-1 in South Africa. Nearly half of these individuals are on antiretroviral therapy. Protease inhibitors (PIs) form part of the South African national treatment guidelines as a first-line regimen for paediatric patients and a second-line regimen for adults. However, successful treatment is often hindered by the development of drug resistance.

Resistance to PIs is characterised by a stepwise accumulation of mutations in the protease gene. However, studies have shown a low frequency of mutations in patients failing PIs. Regions outside of the protease, such as gag and more recently env, have been associated with PI drug resistance in the absence of protease mutations.

We aim to identify genetic markers in the gag and envelope genes which are associated with PI treatment failure. Stored plasma samples from HIV-1-infected patients failing PI-based therapy (n =>500) will be collected from collaborators in South Africa and whole genome sequences from PI-naive patients will be downloaded from the Los Alamos Sequence Database. Failure will be defined as having two consecutive viral loads=>1,000 cpm after being on a PI-based regimen for > 6 months. The whole HIV-1 genome will be amplified from the PI failures and sequenced using Illumina Miseq. Sequences will be aligned to a reference and analysed for single nucleotide polymorphisms (SNPs) in all HIV genes using Geneious v 8.1.8 and GATK software application.

Genome wide association analysis using PLINK will be performed to identify SNPs in PI treated patients that are associated with treatment failure. Episodic directional selection model such as MEDS and IFEL will be used to identify mutations that occur at specific amino acid positions and confer resistance to PIs. The previously mentioned methods allow the identification of drug resistance mutations without the need of baseline samples. Preliminary data from GWAS analysis on 26 patients failing PI-based therapy has identified codons in envelope and gag which are significantly associated with PI failure. Further examination of these sites in the viral minority population has shown that they are present at?>2% of the viral population. By increasing our sample size we will obtain a more comprehensive and robust analysis of the role of regions outside the protease gene in PI resistance. Analysis of the control samples is currently being performed.

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Citation: Giandhari J, Gordon M, van Vuuren C, Moodley P, de Oliveira T. Genetic markers for protease inhibitor drug resistance in regions outside of the protease gene Virus Evolution,:doi: 10.1093/ve/vew036.018 (2017).

KRISP has been created by the coordinated effort of the University of KwaZulu-Natal (UKZN), the Technology Innovation Agency (TIA) and the South African Medical Research Countil (SAMRC).

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