Limited evolution but increasing trends of primary non-nucleoside reverse transcriptase inhibitor resistance mutations in therapy-naive HIV-1-infected individuals in India.

BACKGROUND: After the rapid scale-up of antiretroviral therapy (ART) in resource-limited settings, surveillance of primary drug resistance mutations (DRMs) among ART-naive individuals has important public health benefits. Although a highly successful national ART programme initiated by the Government of India exists, data on the prevalence of primary DRMs is scarce. The objective of the study is to estimate the prevalence, pattern and spectrum of population-based primary DRMs in therapy-naive HIV-1-infected individuals using clinical strains and database sequences from seven HIV prevalent states of India. METHODS: Drug resistance genotyping was performed on either plasma RNA or whole-blood genomic DNA using a validated in-house method on 170 HIV-1-positive therapy-naive individuals. An additional 679 database-derived sequences from four other states were included in the analysis. The WHO-recommended list of mutations (SDRM_2009) for nucleoside reverse transcriptase inhibitors (NRTIs) and non-nucleoside reverse transcriptase inhibitors (NNRTIs) were used for interpretation of DRMs. Trends of primary DRMs before and after the ART rollout were studied. RESULTS: The overall prevalence of primary DRMs was 2.6% in the selected states of India when clinical isolates as well as database-derived sequences were combined. Common mutations included T69D and D67N (NRTI mutations), and L100I, K101E, K103N and Y181C (NNRTI mutations). There was a significant increase in NNRTI mutations over time. CONCLUSIONS: The overall DRM prevalence in this study was low. However, an increasing trend in primary NNRTI resistance has been observed during the past decade. Establishment of HIV drug resistance threshold surveillance will be useful in understanding further trends of transmitted resistance.

Molecular epidemiology of HIV-1 subtypes in India: origin and evolutionary history of the predominant subtype C.

BACKGROUND: India has the third largest HIV-1 epidemic with 2.4 million infected individuals. Molecular epidemiological analysis has identified the predominance of HIV-1 subtype C (HIV-1C). However, the previous reports have been limited by sample size, and uneven geographical distribution. The introduction of HIV-1C in India remains uncertain due to this lack of structured studies. To fill the gap, we characterised the distribution pattern of HIV-1 subtypes in India based on data collection from nationwide clinical cohorts between 2007 and 2011. We also reconstructed the time to the most recent common ancestor (tMRCA) of the predominant HIV-1C strains. METHODOLOGY/PRINCIPAL FINDINGS: Blood samples were collected from 168 HIV-1 seropositive subjects from 7 different states. HIV-1 subtypes were determined using two or three genes, gag, pol, and env using several methods. Bayesian coalescent-based approach was used to reconstruct the time of introduction and population growth patterns of the Indian HIV-1C. For the first time, a high prevalence (10%) of unique recombinant forms (BC and A1C) was observed when two or three genes were used instead of one gene (p<0.01; p = 0.02, respectively). The tMRCA of Indian HIV-1C was estimated using the three viral genes, ranged from 1967 (gag) to 1974 (env). Pol-gene analysis was considered to provide the most reliable estimate [1971, (95% CI: 1965-1976)]. The population growth pattern revealed an initial slow growth phase in the mid-1970s, an exponential phase through the 1980s, and a stationary phase since the early 1990s. CONCLUSIONS/SIGNIFICANCE: The Indian HIV-1C epidemic originated around 40 years ago from a single or few genetically related African lineages, and since then largely evolved independently. The effective population size in the country has been broadly stable since the 1990s. The evolving viral epidemic, as indicated by the increase of recombinant strains, warrants a need for continued molecular surveillance to guide efficient disease intervention strategies.