HLA alleles that are common in a given population may also cause the increased frequency of corresponding CTL escape variants. In particular, mutations with slower reversion times might be most likely to have a greater frequency in a given population, Slow reversion times could be caused by the lack of a strong detrimental impact on viral replication capacity, the presence of compensatory mutations that partially stabilize the escape variant, or amino acid changes that require more than one nucleotide change. Thus, in a transmission chain including several individuals with common HLA alleles, escape mutations that are slow to revert may be maintained at high frequency. Because a large proportion of HIV transmission is thought to occur during the acute stage of infection¹³ when there is little adaptive immune response in the host, preexisting escape mutations can conceivably be transmitted to an individual without the corresponding HLA alleles, but not have sufficient time to revert before being transmitted again to another individual. In this way, CTL escape variants could be maintained in a transmission chain involving some individuals without the corresponding HLA alleles.

Individuals with rare HLA alleles are more likely to be infected by viral variants with preexisting escape mutations to discordant HLA alleles, compared to individuals with common HLA alleles. After infection, viral variants with optimal fitness will dominate the viral population within the host, resulting in the loss of some preexisting escape mutations. In addition, the virus population is likely to evolve additional escape mutations in response to cellular immunity mediated by the rare HLA allele or alleles. Thus, we hypothesized that a greater amount of viral evolution will be necessary for the virus to achieve an adapted state in an individual with rare HLA alleles compared to those with common alleles, possibly providing additional time for the immune response to be effective during the early stages of infection.

To determine if single alleles are driving these associations, the individual HLA-A alleles were evaluated for their relationship with external branch lengths in env, nef, and pol (Table 4). The impact of each allele on external branch length was evaluated in relation to allele frequency (Figure 1). Again, an inverse relationship was observed between HLA allele frequency and external branch length. Furthermore, two HLA-A alleles were found to be in linkage disequilibrium with HLA-B and HLA-C alleles (Table 4).

The distance to the most recent common ancestor of the entire population, likely encompassing evolution throughout the duration of the subtype C epidemic, was not predicted to be influenced by the HLA from the most recently infected individual. And as expected, no significant association was found with HLA frequency and distance to the MRCA for any of the trees generated from each HIV gene.

HLA alleles can be grouped into supertypes^24,25 based on the recognition of common motifs. HLA supertype frequency was not found to be associated with terminal branch length for any HIV gene, suggesting that this grouping, although increasing the power of the analysis by increasing sample size for each association evaluated, may have introduced misclassification bias by grouping HLA alleles with different impacts on HIV evolution, driving the association toward the null hypothesis.

Under the hypothesis of heterozygote advantage,²⁶ individuals with heterozygous HLA alleles would select for a greater amount of viral evolution than homozygous individuals. Indeed, homozygosity at HLA-B was associated with shorter branch lengths in gag (two-sided t-test p<0.0006), and homozygosity at HLA-A with shorter branch lengths in tat (two-sided t-test p<0.012).

In general, CD4 counts decrease as the disease progresses. Thus, it would be expected that branch lengths would be inversely associated with CD4 counts, because the virus continues to evolve throughout the course of infection. Indeed, we observed that CD4 counts were inversely associated with vif (p<0.008) and rev (p<0.031) external branch lengths. Similarly, CD4 disease stage categories were associated with vifand rev external branch lengths (Table 5). However, viral load demonstrated no association with viral evolution in any HIV gene.

One of the most daunting challenges in the design of an effective vaccine against HIV-1 is the enormous amount of genetic diversity observed among sequences identified worldwide. Developing a vaccine that targets elements common to all HIV-1 infections is a challenging task. One approach has been to identify sequences present in early infection with the hope that the factors selecting for the transmitted variants will result in common sequences or sequence patterns that can be incorporated into effective immunogens. An encouraging idea is that viruses undergo a procession toward an ancestral state of higher fitness prior to the evolution of escape mutations.³⁵ A vaccine targeting this ancestral state, theoretically common to all infections, could prevent the virus from achieving high replication capacity very early after transmission, possibly resulting in eradication of the virus or reduced disease progression. Our study suggests that individuals with rare HLA alleles will have a greater number of evolutionary events, possibly due to increased reversions toward this ancestral state. Thus, sequences from individuals with rare HLA alleles may optimally assist in the identification of this ancestral state.

Viruses infecting individuals with rare HLA alleles would likely have both reduced replication capacity due to preexisting escape mutations as well as susceptibility to the immune response because the preexisting escape mutations would not protect against the immune response mediated by the rare HLA allele. This could lead to reduced viral load among those with rare HLA alleles. Supporting this hypothesis, two recent studies have identified an indirect association of viral load with the presence of transmitted escape variants selected for by discordant HLA earlier in the transmission chain.^8,36 While we were able to detect an association between HLA frequency and viral evolution, no significant association was found in our analysis when HLA frequency was evaluated in relation to viral load. We may not have observed an association in this study because the difference in viral load among those with and without the escape variants may be most striking during the initial stages of infection. Because our study was cross-sectional, the majority of the study participants were likely to be in the asymptomatic stage of the infection. In addition, different HLA alleles have been shown to be associated both with increased and decreased disease progression,³⁷ suggesting that the HLA-mediated immune response may have a complex set of effects, preventing the observation of an overall association of HLA-driven evolution with disease outcome. These and other unidentified misclassifications could explain why the clinical impact of a putative advantage of rare HLA alleles, possibly detectable in prospective analyses, may have been obscured in this cross-sectional study.

Although we evaluated the full HIV proteome, including all nine genes, no correction for multiple comparisons was performed because these genes were not independent, complicating the identification of an appropriate test. Given a p-value cutoff of 0.05 and the conservative Bonferroni method of correction for multiple comparisons, one would expect ≤1 association due to chance. Because our results identified three of nine associations, we conclude that our analysis provides significant evidence that population HLA class I allelic frequency has a substantial impact on viral evolution. Furthermore, this analysis evaluated a linear relationship between HLA frequency and HIV evolution as a logical first-order approximation and not necessarily the best approximation of the true relationship between these variables.

The three genes identified in this study are likely to reflect those with the strongest associations, allowing their identification in this analysis. It is not surprising to find Env evolution associated with HLA frequency, because this highly variable protein may allow substantial epitope escape in response to HLA-mediated immunity without substantial loss of viral fitness. Because Nef may be most targeted by the CTL response³⁸ and may have the most amino acid variation driven by HLA selection pressure,¹⁹ it is also not surprising to find that Nef is likely to demonstrate differential evolution in response to varying CTL-based selection pressures. Finally, Pol, neither highly variable nor the most targeted protein, is an unanticipated result of this analysis. Pol is highly conserved and may not tolerate variation without loss of function, allowing variation only in the presence of strong CTL selection. In this case, a large proportion of the most recent evolution in Pol should be due to evolution toward a more fit form.

It remains unclear why we found associations with HLA-A only. However, this does not rule out the possibility that CTL responses mediated by HLA-B and HLA-C are not involved. Because the HLA genes are located in the same genomic region, they cosegregate, particularly HLA-A and HLA-B due to their proximity. In fact, two HLA alleles found to be associated with phylogenetic branch length also had significant linkage disequilibrium with HLA-B and HLA-C alleles (Table 4). Thus the associations with HLA-A may simply reflect linked associations with the other HLA genes.

There are several limitations to this study that may have prevented the identification of associations with some HIV-1 proteins. As mentioned earlier, this was a cross-sectional study and the precise time of infection was unknown. Longitudinal analysis including extensive viral sequencing during the acute stage of infection may be required to thoroughly evaluate viral evolution in response to HLA-mediated immunity. Because this ideal dataset is currently unavailable, our phylogenetic analysis was the best method to approximate those sequence changes. In addition, the external branch lengths we observed likely included evolutionary events that occurred in prior hosts, diluting our ability to identify an association between divergence and HLA frequency. Furthermore, HIV-1 evolves due to other factors, including other adaptive immune responses and protein function, possibly reducing associations evaluated with the CTL response. Finally, the sample size, although large for the extensive and high quality sequence data generated, may be too small to distinguish the impact of the CTL response on viral evolution in every HIV-1 gene when multiple factors are involved. These potential limitations are likely to bias our results toward the null hypothesis, making the identification of significant associations even less likely. Thus, our findings may be limited to only the strongest associations.