Estimating the Respective Contributions of Human and Viral Genetic Variation to HIV Control

We evaluated the fraction of variation in HIV-1 set point viral load attributable to viral or human genetic factors by using joint host/pathogen genetic data from 541 HIV infected individuals. We show that viral genetic diversity explains 29% of the variation in viral load while host factors explain 8.4%. Using a joint model including both host and viral effects, we estimate a total of 30% heritability, indicating that most of the host effects are reflected in viral sequence variation

Human immunotypes impose selection on viral genotypes through viral epitope specificity

BACKGROUND: Understanding the genetic interplay between human hosts and infectious pathogens is crucial for how we interpret virulence factors. Here, we tested for associations between HIV and host genetics, and interactive genetic effects on viral load (VL) in HIV+ ART-naive clinical trial participants. METHODS: HIV genomes were sequenced and the encoded amino acid (AA) variants were associated with VL, human single nucleotide polymorphisms (SNPs) and imputed HLA alleles, using generalized linear models with Bonferroni correction. RESULTS: Human (388,501 SNPs) and HIV (3,010 variants) genetic data was available for 2,122 persons. Four HIV variants were associated with VL (p-values<1.66×10 -5). Twelve HIV variants were associated with a range of 1-512 human SNPs (p-value<4.28×10 -11). We found 46 associations between HLA alleles and HIV variants (p-values<1.29×10 -7). We found HIV variants and immunotypes when analyzed separately, were associated with lower VL, whereas the opposite was true when analyzed in concert. Epitope binding prediction showed HLA alleles to be weaker binders of associated HIV AA variants relative to alternative variants on the same position. CONCLUSIONS: Our results show the importance of immunotype specificity on viral antigenic determinants, and the identified genetic interplay puts emphasis that viral and human genetics should be studied in the context of each other

Interaction of the Host and Viral Genome and Their Influence on HIV Disease

The course of Human Immunodeficiency Virus type 1 (HIV) infection is a dynamic interplay in which both host and viral genetic variation, among other factors, influence disease susceptibility and rate of progression. HIV set-point viral load (spVL), a key indicator of HIV disease progression, has an estimated 30% of variance attributable to common heritable effects and roughly 70% attributable to environmental factors and/or additional non-genetic factors. Genome-wide genotyping and sequencing studies have allowed for large-scale association testing studying host and viral genetic variants associated with infection and disease progression. Host genomics of HIV infection has been studied predominantly in Caucasian populations consistently identifying human leukocyte antigen (HLA) genes and C-C motif chemokine receptor 5 as key factors of HIV susceptibility and progression. However, these studies don’t fully assess all classes of genetic variation (e.g., very rare polymorphisms, copy number variants etc.) and do not inform on non-European ancestry groups. Additionally, viral sequence variability has been demonstrated to influence disease progression independently of host genetic variation. Viral sequence variation can be attributed to the rapid evolution of the virus within the host due to the selective pressure of the host immune response. As the host immune system responds to the virus, e.g., through recognition of HIV antigens, the virus is able to mitigate this response by evolving HLA-specific escape mutations. Diversity of viral genotypes has also been correlated with moderate to strong effects on CD4+ T cell decline and some studies showing weak to no correlation with spVL. There is evidence to support these viral genetic factors being heritable between individuals and the evolution of these factors having important consequences in the genetic epidemiology of HIV infection on a population level. This review will discuss the host-pathogen interaction of HIV infection, explore the importance of host and viral genetics for a better understanding of pathogenesis and identify opportunities for additional genetic studies

Prevention of HIV-1 acquisition and determinants of disease progression.

Doctoral Degree. University of KwaZulu-Natal, Durban.Introduction HIV-1 infection can be managed using multiple strategies, including preventative approaches and therapeutic approaches. Current preventative and treatment strategies are suboptimal and there is a need to develop an effective prophylactic or therapeutic vaccine and to improve the public health approaches against the virus. This requires more detailed understanding of the infection, from prevention to natural disease progression. We performed several studies that cover a range of infection attributes, from understanding the mechanism of action of pre-exposure prophylaxis (PrEP) and determining the effectiveness of different compounds in blocking initial infection, to gaining further insight into potential mechanisms of natural control of HIV-1 disease progression in viraemic controllers (VC) with (VC+) and without (VC-) protective class I human leukocyte antigen (HLA-I) alleles. In order to cover this range of infection attributes we investigated two hypotheses: (i) initial low dose infection can be cleared with suboptimal drug inhibition, which allows ongoing viral replication, as long as the drug mechanism acts before the first cell is infected; and (ii) individuals without protective HLA-I alleles have CD8+ T cell-independent mechanisms of control. Methods To understand the mechanism of action of PrEP, the probability of extinction of new infections in the presence of two drug mechanisms (interference of initial infection with tenofovir (TFV), or reduction of burst size with atazanavir (ATV)), or with no drug, was modelled as a function of initial infected cells and viral replication ratio. The fraction of extinguished infections was experimentally determined with low viral input in the presence of either drug, or with no drug, in an in vitro model of PrEP. To gain insight into potential mechanisms of control, we studied immune cells in 12 VC+ and 9 VC- and, compared these 21 controllers with 5 rapid progressors (RP). Measurements included the magnitude and breadth of CTL responses using the ELISpot assay, as well as flow cytometry-based characterization of NK cell and T cell populations, which included the measurement of surface markers for activation, maturation, and exhaustion on these populations. Further, NK cell function was measured by intracellular cytokine staining following stimulation of these cells. Results Our study showed that TFV dramatically increased clearance while ATV did not, both for our mathematical model and our experimental study. We observed that both VC, in particular VC-, had a higher contribution of Gag CTL responses to the total CTL response than RP (p=0.04), however there was no significant difference in the magnitude and breadth of CTL responses between VC+ and VC-. In addition, VC- NK cells had higher levels of the activation markers HLA-DR (p=0.007) and co-expression of CD38 and HLA-DR (p=0.03) when compared to VC+ and uninfected individuals (UI), and lower cytokine expression (MIP-1β and TNF-α) than VC+ NK cells (p=0.05 and p=0.04, respectively). We found a negative correlation between the expression of MIP-1β and the co-expression of CD38 and HLA-DR (r =-0.45, p=0.05). Furthermore, VC- T cells had higher levels of CD38 and HLA-DR co-expression (p=0.05), and a trend of higher HLA-DR (p=0.07) as well as CD57 expression (p=0.09) when compared to VC+. Conclusions The ability of drugs to clear initial but not established infection depends only on the ability to target initial infection. This implies that in diseases which involve transmission of low pathogen numbers upon exposure, but have robust replication when established, such as HIV-1, a possibility to clear infection should exist even with relatively weak inhibition as long as the drug has the mechanism of targeting the initial infection. This finding is particularly relevant in scenarios of variable adherence that result in sub-optimal drug levels or possible future PrEP strategies with drugs that have long half-lives yet do not completely suppress viral replication. VC have a more Gag focused CTL response than RP, however this feature did not distinguish VC+ from VC-. NK and T cell profiles differ between VC+ and VC-. VC- have a more activated NK cell profile with lower cytokine expression, and a more active and terminally differentiated T cell profile than VC+. A possible explanation for our results is that the increased CD38+HLA-DR+ NK cells in VC- may represent NK cells acting as antigen presenting cells (APCs), which may then directly interact with a more activated and terminally differentiated population of T cells observed in VC-. Further work to test this hypothesis is necessary to better understand the mechanisms underlying control in these two groups of VC patients. It is also suggested that transcriptomic studies may contribute further to understanding the distinct NK and T cell profiles observed between VC+ and VC- and how these may result in differing mechanisms of control