The within-host fitness of HIV-1 increases with age in ART-naïve HIV-1 subtype C infected children.

As the immune system develops with age, children combat infections better. HIV-1, however, targets an activated immune system, potentially rendering children increasingly permissive to HIV-1 infection as they grow. How HIV-1 fitness changes with age in children is unknown. Here, we estimated the within-host basic reproductive ratio, R0, a marker of viral fitness, in HIV-1 subtype C-infected children in India, aged between 84 days and 17 years. We measured serial viral load and CD4 T cell counts in 171 children who initiated first-line ART. For 25 children, regular and frequent measurements provided adequate data points for analysis using a mathematical model of viral dynamics to estimate R0. For the rest, we used CD4 counts for approximate estimation of R0. The viral load decline during therapy was biphasic. The mean lifespans of productively and long-lived infected cells were 1.4 and 27.8 days, respectively. The mean R0 was 1.5 in children aged < 5 years, increased with age, and approached 6.0 at 18 years, close to 5.8 estimated previously for adults. The tolerogenic immune environment thus compromises HIV-1 fitness in young children. Early treatment initiation, when the R0 is small, will likely improve viral control, in addition to suppressing the latent reservoir.

Viral Decay Dynamics and Mathematical Modeling of Treatment Response: Evidence of Lower in vivo Fitness of HIV-1 Subtype C.

BACKGROUND: Despite the high prevalence of HIV-1 subtype C (HIV-1C) worldwide, information on HIV-1C viral dynamics and response to antiretroviral therapy (ART) is limited. We sought to measure viral load decay dynamics during treatment and estimate the within-host basic reproductive ratio, R0, and the critical efficacy, εc, for successful treatment of HIV-1C infection. METHODS: Individuals initiated on first-line ART in India and monitored for 6 months of treatment were considered. Viral load, CD4 count, and adherence data were collected at baseline, 4, 12, 16 and 24 weeks after ART initiation. Drug resistance genotyping was performed at baseline. R0 and εc were estimated using a mathematical model. RESULTS: Among 257 patients with complete data, mean baseline viral load was 5.7 log10 copies per milliliter and median CD4 count was 165 cells per cubic millimeter. Primary drug resistance was present in 3.1% at baseline. At 6 months, 87.5% had undetectable viral load, indicating excellent response to ART despite high baseline viremia. After excluding those with transmitted resistance, suboptimal adherence and viral rebound, data from 112 patients were analyzed using a mathematical model. We estimated the median R0 to be 5.3. The corresponding εc was ∼0.8. CONCLUSIONS: These estimates of R0 and εc are smaller than current estimates for HIV-1B, suggesting that HIV-1C exhibits lower in vivo fitness compared with HIV-1B, which allows successful treatment despite high baseline viral loads. The lower fitness, and potentially lower virulence, together with high viral loads may underlie the heightened transmission potential of HIV-1C and its growing global spread.

Influence of recombination on acquisition and reversion of immune escape and compensatory mutations in HIV-1.

Following transmission, HIV-1 adapts in the new host by acquiring mutations that allow it to escape from the host immune response at multiple epitopes. It also reverts mutations associated with epitopes targeted in the transmitting host but not in the new host. Moreover, escape mutations are often associated with additional compensatory mutations that partially recover fitness costs. It is unclear whether recombination expedites this process of multi-locus adaptation. To elucidate the role of recombination, we constructed a detailed population dynamics model that integrates viral dynamics, host immune response at multiple epitopes through cytotoxic T lymphocytes, and viral evolution driven by mutation, recombination, and selection. Using this model, we compute the expected waiting time until the emergence of the strain that has gained escape and compensatory mutations against the new host's immune response, and reverted these mutations at epitopes no longer targeted. We find that depending on the underlying fitness landscape, shaped by both costs and benefits of mutations, adaptation proceeds via distinct dominant pathways with different effects of recombination, in particular distinguishing escape and reversion. When adaptation at a single epitope is involved, recombination can substantially accelerate immune escape but minimally affects reversion. When multiple epitopes are involved, recombination can accelerate or inhibit adaptation depending on the fitness landscape. Specifically, recombination tends to delay adaptation when a purely uphill fitness landscape is accessible at each epitope, and accelerate it when a fitness valley is associated with each epitope. Our study points to the importance of recombination in shaping the adaptation of HIV-1 following its transmission to new hosts, a process central to T cell-based vaccine strategies.