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The contribution of viral genotype to plasma viral set-point in HIV infection.

ABSTRACT: Disease progression in HIV-infected individuals varies greatly, and while the environmental and host factors influencing this variation have been widely investigated, the viral contribution to variation in set-point viral load, a predictor of disease progression, is less clear. Previous studies, using transmission-pairs and analysis of phylogenetic signal in small numbers of individuals, have produced a wide range of viral genetic effect estimates. Here we present a novel application of a population-scale method based in quantitative genetics to estimate the viral genetic effect on set-point viral load in the UK subtype B HIV-1 epidemic, based on a very large data set. Analyzing the initial viral load and associated pol sequence, both taken before anti-retroviral therapy, of 8,483 patients, we estimate the proportion of variance in viral load explained by viral genetic effects to be 5.7% (CI 2.8-8.6%). We also estimated the change in viral load over time due to selection on the virus and environmental effects to be a decline of 0.05 log10 copies/mL/year, in contrast to recent studies which suggested a reported small increase in viral load over the last 20 years might be due to evolutionary changes in the virus. Our results suggest that in the UK epidemic, subtype B has a small but significant viral genetic effect on viral load. By allowing the analysis of large sample sizes, we expect our approach to be applicable to the estimation of the genetic contribution to traits in many organisms.

SUBMITTER: Hodcroft E

PROVIDER: S-EPMC4006911 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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The contribution of viral genotype to plasma viral set-point in HIV infection.

Hodcroft Emma E Hadfield Jarrod D JD Fearnhill Esther E Phillips Andrew A Dunn David D O'Shea Siobhan S Pillay Deenan D Leigh Brown Andrew J AJ

PLoS pathogens 20140501 5

Disease progression in HIV-infected individuals varies greatly, and while the environmental and host factors influencing this variation have been widely investigated, the viral contribution to variation in set-point viral load, a predictor of disease progression, is less clear. Previous studies, using transmission-pairs and analysis of phylogenetic signal in small numbers of individuals, have produced a wide range of viral genetic effect estimates. Here we present a novel application of a popula ...[more]

PMID: 24789308

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Project description:HIV viral load (VL) predicts both transmission potential and rate of disease progression. For reasons that are still not fully understood, the set point viral load (SPVL) established after acute infection varies across individuals and populations. Previous studies have suggested that population mean SPVL (MSPVL) has evolved near an optimum that reflects a trade-off between transmissibility and host survival. Sexual network structures affect rates of potential exposure during different within-host phases of infection marked by different transmission probabilities, and thus affect the number and timing of transmission events. These structures include relational concurrency, which has been argued to explain key differences in HIV burden across populations. We hypothesize that concurrency will alter the fitness landscape for SPVL in ways that differ from other network features whose impacts accrue at other times during infection. To quantitatively test this hypothesis, we developed a dynamic, stochastic, data-driven network model of HIV transmission, and evolution to assess the impact of key sexual network phenomena on MSPVL evolution. Experiments were repeated in sensitivity runs that made different assumptions about transmissibility during acute infection, SPVL heritability, and the functional form of the relationship between VL and transmissibility. For our main transmission model, scenarios yielded MSPVLs ranging from 4.4 to 4.75 log10 copies/ml, covering much of the observed empirical range. MSPVL evolved to be higher in populations with high concurrency and shorter relational durations, with values varying over a clinically significant range. In linear regression analyses on these and other predictors, main effects were significant (P < 0.05), as were interaction terms, indicating that effects are interdependent. We also noted a strong correlation between two key emergent properties measured at the end of the simulations-MSPVL and HIV prevalence-most clearly for phenomena that affect transmission networks early in infection. Controlling for prevalence, high concurrency yielded higher MSPVL than other network phenomena. Interestingly, we observed lower prevalence in runs in which SPVL heritability was zero, indicating the potential for viral evolution to exacerbate disease burden over time. Future efforts to understand empirical variation in MSPVL should consider local HIV burden and basic sexual behavioral and network structure.

Project description:T cell activation levels, viral load and CD4(+) T cell counts at early stages of HIV-1 infection are predictive of the rate of progression towards AIDS. We evaluated whether the inflammatory profile during primary HIV-1 infection is predictive of the virological and immunological set-points and of disease progression. We quantified 28 plasma proteins during acute and post-acute HIV-1 infection in individuals with known disease progression profiles. Forty-six untreated patients, enrolled during primary HIV-1 infection, were categorized into rapid progressors, progressors and slow progressors according to their spontaneous progression profile over 42 months of follow-up. Already during primary infection, rapid progressors showed a higher number of increased plasma proteins than progressors or slow progressors. The plasma levels of TGF-?1 and IL-18 in primary HIV-1 infection were both positively associated with T cell activation level at set-point (6 months after acute infection) and together able to predict 74% of the T cell activation variation at set-point. Plasma IP-10 was positively and negatively associated with, respectively, T cell activation and CD4(+) T cell counts at set-point and capable to predict 30% of the CD4(+) T cell count variation at set-point. Moreover, plasma IP-10 levels during primary infection were predictive of rapid progression. In primary infection, IP-10 was an even better predictor of rapid disease progression than viremia or CD4(+) T cell levels at this time point. The superior predictive capacity of IP-10 was confirmed in an independent group of 88 HIV-1 infected individuals. Altogether, this study shows that the inflammatory profile in primary HIV-1 infection is associated with T cell activation levels and CD4(+) T cell counts at set-point. Plasma IP-10 levels were of strong predictive value for rapid disease progression. The data suggest IP-10 being an earlier marker of disease progression than CD4(+) T cell counts or viremia levels.

Dataset Information

The contribution of viral genotype to plasma viral set-point in HIV infection.

Publications

The contribution of viral genotype to plasma viral set-point in HIV infection.

Similar Datasets

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