Background Cohort studies and mathematical models have suggested that expanded coverage with highly active antiretroviral therapy (HAART) could decrease HIV transmission. This study focuses on the HIV epidemic, stratified by injection drug use, in the province of British Columbia, Canada, and seeks to estimate the association between plasma HIV-1-viral load, HAART coverage and number of new cases of HIV at the population-level. Methods HAART use, plasma HIV-1-viral level determinations, and rates of reportable sexually transmitted infections, including HIV, are all recorded in province-wide registries allowing for temporal comparisons of these parameters. Trends of new HIV positive tests and number of individuals on HAART were modeled using generalized additive models. Poisson log-linear regression models were used to estimate the association between the outcome new HIV positive tests (per 100 population) and the covariates viral load (log10 transformed), year, and number of individuals on HAART. Conclusions Our results demonstrate a strong association at the population-level between increasing levels of HAART coverage, decreased viral load and decreased new HIV diagnoses/year, against a background of increased HIV testing and increased rates of other STIs in the province. Our results support the proposed secondary benefit of HAART, used within current medical guidelines, on HIV transmission at a population level.

The rapid and extensive spread of the human immunodeficiency virus (HIV) epidemic provides a rare opportunity to witness host–pathogen co-evolution involving humans. A focal point is the interaction between genes encoding human leukocyte antigen (HLA) and those encoding HIV proteins. HLA molecules present fragments (epitopes) of HIV proteins on the surface of infected cells to enable immune recognition and killing by CD8+ T cells; particular HLA molecules, such as HLA-B*57, HLA-B*27 and HLA-B*51, are more likely to mediate successful control of HIV infection1. Mutation within these epitopes can allow viral escape from CD8+ T-cell recognition. Here we analysed viral sequences and HLA alleles from >2,800 subjects, drawn from 9 distinct study cohorts spanning 5 continents. Initial analysis of the HLA-B*51-restricted epitope, TAFTIPSI (reverse transcriptase residues 128–135), showed a strong correlation between the frequency of the escape mutation I135X and HLA-B*51 prevalence in the 9 study cohorts (P = 0.0001). Extending these analyses to incorporate other well-defined CD8+ T-cell epitopes, including those restricted by HLA-B*57 and HLA-B*27, showed that the frequency of these epitope variants (n = 14) was consistently correlated with the prevalence of the restricting HLA allele in the different cohorts (together, P < 0.0001), demonstrating strong evidence of HIV adaptation to HLA at a population level. This process of viral adaptation may dismantle the well-established HLA associations with control of HIV infection that are linked to the availability of key epitopes, and highlights the challenge for a vaccine to keep pace with the changing immunological landscape presented by HIV.

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High baseline pVLs and substantial but imperfect levels of adherence were major predictors of antiretroviral resistance.

i HLA class I-associated polymorphisms identified at the population level mark viral sites under immune pressure by individual HLA alleles. As such, analysis of their distribution, frequency, location, statistical strength, sequence conservation, and other properties offers a unique perspective from which to identify correlates of protective cellular immunity. We analyzed HLA-associated HIV-1 subtype B polymorphisms in 1,888 treatment-naïve, chronically infected individuals using phylogenetically informed methods and identified characteristics of HLA-associated immune pressures that differentiate protective and nonprotective alleles. Over 2,100 HLA-associated HIV-1 polymorphisms were identified, approximately one-third of which occurred inside or within 3 residues of an optimally defined cytotoxic T-lymphocyte (CTL) epitope. Differential CTL escape patterns between closely related HLA alleles were common and increased with greater evolutionary distance between allele group members. Among 9-mer epitopes, mutations at HLA-specific anchor residues represented the most frequently detected escape type: these occurred nearly 2-fold more frequently than expected by chance and were computationally predicted to reduce peptide-HLA binding nearly 10-fold on average. Characteristics associated with protective HLA alleles (defined using hazard ratios for progression to AIDS from natural history cohorts) included the potential to mount broad immune selection pressures across all HIV-1 proteins except Nef, the tendency to drive multisite and/or anchor residue escape mutations within known CTL epitopes, and the ability to strongly select mutations in conserved regions within HIV's structural and functional proteins. Thus, the factors defining protective cellular immune responses may be more complex than simply targeting conserved viral regions. The results provide new information to guide vaccine design and immunogenicity studies. HIV-1 is notorious for its genetic diversity and its ability to adapt to selection pressures (44,87,116). Despite this, within-host HIV-1 evolution in response to antiretroviral (61, 72), host cellular immune (15,50,71,94,95), antibody (46), and vaccine-induced (103) selection pressures occurs along generally predictable mutational pathways (3, 84). Studying these evolutionary pathways can offer insight into the immunopathogenesis of HIV-1 and may help inform the design of immune-based interventions and vaccines.Substantial progress has been made in our understanding of HIV-1's ability to evade human leukocyte antigen (HLA) class I-restricted CD8 ϩ cytotoxic T-lymphocytes (CTL). In particular, application of novel statistical methods (13,25,84) to large population-based data sets of linked host and viral genetic information has facilitated the systematic identification of HLA-associated immune escape and covarying mutations in 20,60,81,99,104), revealing important insights into HIV-1 adaptation to its host. We now appreciate that immune selection represents a major force shaping HIV-1 diversity (3,80,...

Objective To examine the relation between plasma HIV-1

BackgroundThe genetic differences among HIV-1 subtypes may be critical to clinical management and drug resistance surveillance as antiretroviral treatment is expanded to regions of the world where diverse non-subtype-B viruses predominate.Methods and FindingsTo assess the impact of HIV-1 subtype and antiretroviral treatment on the distribution of mutations in protease and reverse transcriptase, a binomial response model using subtype and treatment as explanatory variables was used to analyze a large compiled dataset of non-subtype-B HIV-1 sequences. Non-subtype-B sequences from 3,686 persons with well characterized antiretroviral treatment histories were analyzed in comparison to subtype B sequences from 4,769 persons. The non-subtype-B sequences included 461 with subtype A, 1,185 with C, 331 with D, 245 with F, 293 with G, 513 with CRF01_AE, and 618 with CRF02_AG. Each of the 55 known subtype B drug-resistance mutations occurred in at least one non-B isolate, and 44 (80%) of these mutations were significantly associated with antiretroviral treatment in at least one non-B subtype. Conversely, of 67 mutations found to be associated with antiretroviral therapy in at least one non-B subtype, 61 were also associated with antiretroviral therapy in subtype B isolates.ConclusionGlobal surveillance and genotypic assessment of drug resistance should focus primarily on the known subtype B drug-resistance mutations.

Delaying HAART until the CD4+ cell count falls to 0.200 x 109 cells/L does not increase the mortality rate in HIV-infected patients with good medication adherence. Mortality rates increase if HAART is initiated below 0.200 x 10(9) cells/L. Also, nonadherent patients have higher mortality rates than adherent patients with similar CD4+ cell counts. Above a CD4+ cell count of 0.200 x 10(9) cells/L, medication adherence is the critical determinant of survival, not the CD4+ cell count at which HAART is begun.