Host Genetic and Viral Determinants of HIV-1 RNA Set Point among HIV-1 Seroconverters from Sub-Saharan Africa

Abstract

We quantified the collective impact of source partner HIV-1 RNA levels, human leukocyte antigen (HLA) alleles, and innate responses through Toll-like receptor (TLR) alleles on the HIV-1 set point. Data came from HIV-1 seroconverters in African HIV-1 serodiscordant couple cohorts. Linear regression was used to determine associations with set point and R 2 to estimate variation explained by covariates. The strongest predictors of set point were HLA alleles (B*53:01, B*14:01, and B*27:03) and plasma HIV-1 levels of the transmitting partner, which explained 13% and 10% of variation in set point, respectively. HLA-A concordance between partners and TLR polymorphisms (TLR2 rs3804100 and TLR7 rs179012) also were associated with set point, explaining 6% and 5% of the variation, respectively. Overall, these factors and genital factors of the transmitter (i.e., male circumcision, bacterial vaginosis, and use of acyclovir) explained 46% of variation in set point. We found that both innate and adaptive immune responses, together with plasma HIV-1 levels of the transmitting partner, explain almost half of the variation in viral load set point. IMPORTANCEAfter HIV-1 infection, uncontrolled virus replication leads to a rapid increase in HIV-1 concentrations. Once host immune responses develop, however, HIV-1 levels reach a peak and subsequently decline until they reach a stable level that may persist for years. This stable HIV-1 set point represents an equilibrium between the virus and host responses and is predictive of later disease progression and transmission potential. Understanding how host and virus factors interact to determine HIV-1 set point may elucidate novel mechanisms or biological pathways for treating HIV-1 infection. We identified host and virus factors that predict HIV-1 set point in people who recently acquired HIV-1, finding that both innate and adaptive immune responses, along with factors that likely influence HIV-1 virulence and inoculum, explain ϳ46% of the variation in HIV-1 set point. Following HIV-1 acquisition, plasma HIV-1 concentrations reach a peak level and then decline to a stable set point within 3 to 4 months after infection. This HIV-1 set point level is a critical determinant of later disease progression and infectivity (1-4) and is thought to be a measure of the balance between the replicative fitness of the transmitted virus and the antiviral responses of the new host. The importance of viral characteristics in determining set point is supported by multiple studies reporting a strong correlation between plasma HIV-1 RNA levels in HIV-1-transmitting (source) partners with the HIV-1 set point of their seroconverting partner (5-10). The host contribution is exemplified by the importance of variation in the human leukocyte antigen (HLA) class I (HLA-A, HLA-B, and HLA-C) genes, which are strongly associated with set point by virtue of the essential role for HLA in presenting HIV-1 peptides to CD8 ϩ T cells (11). Furthermore, HLA allele sharing within an HIV-1 transmission pair may lead...

Estimating the respective contributions of human and viral genetic variation to HIV control

“…Measured during the chronic phase of infection, the viral load (referred to as setpoint viral load, spVL) exhibits large variation in a population. Several studies have been carried out to elucidate whether this variation is primarily driven by host genetics [1][2][3][4] , viral genetics [5][6][7][8][9] , or environmental effects 7 . Genome-wide association studies consistently show that amino acid polymorphisms in the peptide binding groove of the HLA-A and HLA-B proteins are associated with the viral load of an individual.…”

Changing Antiretroviral Eligibility Criteria

“…The association between VL and CD4 + count in untreated adults in a population will vary depending on the incidence rate in recent years, the age of the epidemic, the predominant viral subtype, and the viral set point in the population. 26 , 27 Thus, the results from Swaziland, which has a mature generalized epidemic with one of the highest HIV incidence rates in the world, may not apply to all settings. Additionally, we were unable to verify ART treatment status beyond self-report for one-third of the participants, as they did not have their ART clinic record available at the time of interview, and we considered all those reporting being on ART as having been eligible per prevailing eligibility requirements at the time of their ART initiation but did not have clinical verification of their eligibility status at that time.…”

Longitudinal Antigenic Sequences and Sites from Intra-Host Evolution (LASSIE) Identifies Immune-Selected HIV Variants

“…The virus population grows exponentially, with random mutations that initially accumulate following a Poisson distribution of inter-sequence distances [ 5 , 6 ]. The viral load eventually declines and resolves to a quasistationary set-point [ 7 ], influenced by both host and viral factors [ 8 ]. HIV-1 is maintained as a continuously evolving quasispecies population throughout chronic infection [ 9 ], with diversification driven by adaptive immune responses, including antibody [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ] and T cell responses [ 19 , 20 , 21 ].…”