BACKGROUND: We aimed to characterize the molecular epidemiology of HIV type-1 (HIV-1) and the prevalence of drug-associated mutations prior to initiating highly active antiretroviral therapy (HAART) in the Free State province, South Africa. The Free State has a population of 3 million, an antenatal HIV prevalence of approximately 34% and a well established infrastucture for antiretroviral (ARV) provision. METHODS: HIV-1 polymerase genes were sequenced from 425 HAART-naive HIV-1-positive patients at voluntary primary healthcare HIV testing centres, who were subsequently attending district centres for assessment for commencing ARVs. Patients (>18 years) were sampled randomly with no exclusion for gender or clinical criteria. Sequences were analysed according to phylogeny and drug resistance. RESULTS: Phylogenetic clustering within the cohort was suggestive of multiple introductions of subtype C virus into the region. Drug resistance mutations (according to the International AIDS Society-USA classification) were distributed randomly across the cohort phylogeny with an overall prevalence of 2.3% in the sampled patients. When stratified according to CD4(+) T-cell count, the prevalence of resistance was 3.6%, 0.9% and 1.2% for CD4(+) T-cell counts <100, 200-350 and >500 cells/microl, respectively, and was most common for non-nucleoside reverse transcriptase inhibitor resistance (3.1% in patients with CD4(+) T-cell count <100 cells/microl). We surveyed all drug-selected mutations and found further significant clustering among patients with low CD4(+) T-cell counts (P=0.003), suggesting unrecognized exposure to ARVs. CONCLUSIONS: In the Free State population, there was a statistical association between low CD4(+) T-cell counts and drug-associated viral polymorphisms. Our data advocate the benefit of detailed history taking from patients starting HAART at low CD4(+) T-cell counts with close follow-up of the virological response.
BACKGROUND: We aimed to characterize the molecular epidemiology of HIV type-1 (HIV-1) and the prevalence of drug-associated mutations prior to initiating highly active antiretroviral therapy (HAART) in the Free State province, South Africa. The Free State has a population of 3 million, an antenatal HIV prevalence of approximately 34% and a well established infrastucture for antiretroviral (ARV) provision. METHODS:HIV-1 polymerase genes were sequenced from 425 HAART-naive HIV-1-positivepatients at voluntary primary healthcare HIV testing centres, who were subsequently attending district centres for assessment for commencing ARVs. Patients (>18 years) were sampled randomly with no exclusion for gender or clinical criteria. Sequences were analysed according to phylogeny and drug resistance. RESULTS: Phylogenetic clustering within the cohort was suggestive of multiple introductions of subtype C virus into the region. Drug resistance mutations (according to the International AIDS Society-USA classification) were distributed randomly across the cohort phylogeny with an overall prevalence of 2.3% in the sampled patients. When stratified according to CD4(+) T-cell count, the prevalence of resistance was 3.6%, 0.9% and 1.2% for CD4(+) T-cell counts <100, 200-350 and >500 cells/microl, respectively, and was most common for non-nucleoside reverse transcriptase inhibitor resistance (3.1% in patients with CD4(+) T-cell count <100 cells/microl). We surveyed all drug-selected mutations and found further significant clustering among patients with low CD4(+) T-cell counts (P=0.003), suggesting unrecognized exposure to ARVs. CONCLUSIONS: In the Free State population, there was a statistical association between low CD4(+) T-cell counts and drug-associated viral polymorphisms. Our data advocate the benefit of detailed history taking from patients starting HAART at low CD4(+) T-cell counts with close follow-up of the virological response.
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Authors: Jonathan M Carlson; Victor Y Du; Nico Pfeifer; Anju Bansal; Vincent Y F Tan; Karen Power; Chanson J Brumme; Anat Kreimer; Charles E DeZiel; Nicolo Fusi; Malinda Schaefer; Mark A Brockman; Jill Gilmour; Matt A Price; William Kilembe; Richard Haubrich; Mina John; Simon Mallal; Roger Shapiro; John Frater; P Richard Harrigan; Thumbi Ndung'u; Susan Allen; David Heckerman; John Sidney; Todd M Allen; Philip J R Goulder; Zabrina L Brumme; Eric Hunter; Paul A Goepfert Journal: Nat Med Date: 2016-05-16 Impact factor: 53.440