It has been hypothesized that HIV-1 viral load set-point is a surrogate measure of HIV-1 viral virulence, and that it may be subject to natural selection in the human host population. A key test of this hypothesis is whether viral load set-points are correlated between transmitting individuals and those acquiring infection. We retrospectively identified 112 heterosexual HIV-discordant couples enrolled in a cohort in Rakai, Uganda, in which HIV transmission was suspected and viral load set-point was established. In addition, sequence data was available to establish transmission by genetic linkage for 57 of these couples. Sex, age, viral subtype, index partner, and self-reported genital ulcer disease status (GUD) were known. Using ANOVA, we estimated the proportion of variance in viral load set-points which was explained by the similarity within couples (the ‘couple effect’). Individuals with suspected intra-couple transmission (97 couples) had similar viral load set-points (p = 0.054 single factor model, p = 0.0057 adjusted) and the couple effect explained 16% of variance in viral loads (23% adjusted). The analysis was repeated for a subset of 29 couples with strong genetic support for transmission. The couple effect was the major determinant of viral load set-point (p = 0.067 single factor, and p = 0.036 adjusted) and the size of the effect was 27% (37% adjusted). Individuals within epidemiologically linked couples with genetic support for transmission had similar viral load set-points. The most parsimonious explanation is that this is due to shared characteristics of the transmitted virus, a finding which sheds light on both the role of viral factors in HIV-1 pathogenesis and on the evolution of the virus.

These findings suggest that sexual transmission constrains viral diversity at the population level, partially because of the preferential transmission of ancestral as opposed to contemporary strains circulating in the transmitting partner. Future successful vaccine strategies may need to target these transmitted ancestral strains.

HIV superinfection, which occurs when a previously infected individual acquires a new distinct HIV strain, has been described in a number of populations. Previous methods to detect superinfection have involved a combination of labor-intensive assays with various rates of success. We designed and tested a next-generation sequencing (NGS) protocol to identify HIV superinfection by targeting two regions of the HIV viral genome, p24 and gp41. The method was validated by mixing control samples infected with HIV subtype A or D at different ratios to determine the inter-and intrasubtype sensitivity by NGS. This amplicon-based NGS protocol was able to consistently identify distinct intersubtype strains at ratios of 1% and intrasubtype variants at ratios of 5%. By using stored samples from the Rakai Community Cohort Study (RCCS) in Uganda, 11 individuals who were HIV seroconcordant but virally unlinked from their spouses were then tested by this method to detect superinfection between 2002 and 2005. Two female cases of HIV intersubtype superinfection (18.2%) were identified. These results are consistent with other African studies and support the hypothesis that HIV superinfection occurs at a relatively high rate. Our results indicate that NGS can be used for detection of HIV superinfection within large cohorts, which could assist in determining the incidence and the epidemiologic, virologic, and immunological correlates of this phenomenon.