Clinical Significance of Human Immunodeficiency Virus Type 1 Replication Fitness

Infectious Diseases Division, Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA.
Clinical Microbiology Reviews (Impact Factor: 16). 11/2007; 20(4):550-78. DOI: 10.1128/CMR.00017-07
Source: PubMed

ABSTRACT The relative fitness of a variant, according to population genetics theory, is that variant's relative contribution to successive generations. Most drug-resistant human immunodeficiency virus type 1 (HIV-1) variants have reduced replication fitness, but at least some of these deficits can be compensated for by the accumulation of second-site mutations. HIV-1 replication fitness also appears to influence the likelihood of a drug-resistant mutant emerging during treatment failure and is postulated to influence clinical outcomes. A variety of assays are available to measure HIV-1 replication fitness in cell culture; however, there is no agreement regarding which assays best correlate with clinical outcomes. A major limitation is that there is no high-throughput assay that incorporates an internal reference strain as a control and utilizes intact virus isolates. Some retrospective studies have demonstrated statistically significant correlations between HIV-1 replication fitness and clinical outcomes in some patient populations. However, different studies disagree as to which clinical outcomes are most closely associated with fitness. This may be in part due to assay design, sample size limitations, and differences in patient populations. In addition, the strength of the correlations between fitness and clinical outcomes is modest, suggesting that, at present, it would be difficult to utilize these assays for clinical management.

Download full-text


Available from: Carrie Dykes, Jul 02, 2015
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A common approach to understand and analyze complex biological systems is to describe the dynamics in terms of a system of ordinary differential equations (ODE) depending on numerous biologically meaningful and descriptive parameters that are estimated using observed data. The ODE models are often based on the implicit assumption of well-mixed dynamics, i.e., the delay of interaction due to spatial distribution is not included in the model. In this article, we address the question how the heterogeneity of the underlying system affects the estimated parameter values of the ODE model, and on the other hand, what information about the microscopic system can be drawn from these values. The system we are considering is a pairwise growth competition assay used to quantify ex vivo replicative fitness of different HIV-1 isolates. To overcome the lack of ground truth, we generate data using a detailed microscopic spatially distributed hybrid stochastic-deterministic (HSD) infection model in which the dynamics is controlled by parameters directly related to cell level infection, virus production processes, and diffusion of virus particles. The synthetic data sets are then analyzed using an ODE based well-mixed model, in which the corresponding macroscopic parameter distributions are estimated using Markov chain Monte Carlo (MCMC) methods. This approach provides a comprehensive picture of the statistical dependencies of the model parameter across different scales.
    Bulletin of Mathematical Biology 02/2014; 76(2). DOI:10.1007/s11538-013-9926-2 · 1.29 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: More than 200 mutations are associated with antiretroviral resistance to drugs belonging to six licensed antiretroviral classes. More than 50 reverse transcriptase mutations are associated with nucleoside reverse transcriptase inhibitor resistance including M184V, thymidine analog mutations, mutations associated with non-thymidine analog containing regimens, multi-nucleoside resistance mutations, and several recently identified accessory mutations. More than 40 reverse transcriptase mutations are associated with nonnucleoside reverse transcriptase inhibitor resistance including major primary and secondary mutations, non-polymorphic minor mutations, and polymorphic accessory mutations. More than 60 mutations are associated with protease inhibitor resistance including major protease, accessory protease, and protease cleavage site mutations. More than 30 integrase mutations are associated with the licensed integrase inhibitor raltegravir and the investigational inhibitor elvitegravir. More than 15 gp41 mutations are associated with the fusion inhibitor enfuvirtide. CCR5 inhibitor resistance results from mutations that promote gp120 binding to an inhibitor-bound CCR5 receptor or CXCR4 tropism; however, the genotypic correlates of these processes are not yet well characterized.
    AIDS reviews 10(2):67-84. · 4.02 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We hypothesized that drug resistance mutations would impact clinical outcomes associated with HIV-1 infection. A matched case-control study of participants in AIDS Clinical Trials Group Longitudinal Linked Randomized Trials (ALLRT). Cases experienced an AIDS-defining event (ADE) or mortality, and controls did not. One hundred thirty-four cases were identified and matched to a total of 266 controls by age, sex, treatment regimen, and length of follow-up. Both cases and controls had HIV RNA levels of ≥ 500 copies/mL within 24 weeks of an event. Population-based genotyping at or near the time of the event was used to evaluate the impact of resistance mutations on incidence of ADE and/or death using conditional logistic regression models. One hundred four cases and 183 controls were analyzed. Median time to event was 99 weeks; 6 cases were deaths. At baseline, cases had lower CD4 (median 117 vs 235 cells/mm3; P < .0001) and higher HIV RNA levels (median 205,000 vs 57,000 copies/mL; P = .003). No significant differences in resistance were seen between cases and controls. In this rigorously designed case-control study, lower CD4 cell counts and higher virus loads, not antiretroviral drug resistance, were strongly associated with ADE and mortality.
    HIV Clinical Trials 03/2011; 12(2):79-88. DOI:10.1310/hct1202-79 · 2.14 Impact Factor