ArticlePLoS computational biology2008
Dynamic correlation between intrahost HIV-1 quasispecies evolution and disease progression.
Article in PLoS computational biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 2 of them syntheses that pooled it.
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Who cites it
50 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Variation in Intra-individual Lentiviral Evolution Rates: a Systematic Review of Human, Nonhuman Primate, and Felid Species.Journal of virology · 2019Pooled it
- Designing a genome-based HIV incidence assay with high sensitivity and specificity.AIDS (London, England) · 2011Pooled it
- Variations and evolution of HIV-1 provirus in peripheral blood under the pressure of ART.Virus evolution · 2026Article
- wavess: An R package for simulation of adaptive within-host virus sequence evolution.PLoS computational biology · 2025Article
- A graph homomorphism approach for unraveling histories of metastatic cancers and viral outbreaks under evolutionary constraints.Nature communications · 2025Article
- Compartmental structure in the secondary lymphoid tissue can slow downJournal of the Royal Society, Interface · 2025Article
- Article
- Recombination smooths the time signal disrupted by latency in within-host HIV phylogenies.Virus evolution · 2023Article
- Deep-sequencing of viral genomes from a large and diverse cohort of treatment-naive HIV-infected persons shows associations between intrahost genetic diversity and viral load.PLoS computational biology · 2023Article
- In Depth Viral Diversity Analysis in Atypical Neurological and Neonatal Chikungunya Infections in Rio de Janeiro, Brazil.Viruses · 2022Article
- Article
- Dengue Virus Serotype 2 Intrahost Diversity in Patients with Different Clinical Outcomes.Viruses · 2021Article
- Machine Learning Based Clinical Decision Support System for Early COVID-19 Mortality Prediction.Frontiers in public health · 2021Article
- Classification of small ruminant lentivirus subtype A2, subgroups 1 and 2 based on whole genome comparisons and complex recombination patterns.F1000Research · 2020Article
- A new method for inferring timetrees from temporally sampled molecular sequences.PLoS computational biology · 2020Article
- Phylogenetics in HIV transmission: taking within-host diversity into account.Current opinion in HIV and AIDS · 2019Review
- Insight into treatment of HIV infection from viral dynamics models.Immunological reviews · 2018Review
- Intrahost Selection Pressures Drive Rapid Dengue Virus Microevolution in Acute Human Infections.Cell host & microbe · 2017Article
- Identifying predictors of time-inhomogeneous viral evolutionary processes.Virus evolution · 2016Article
- The effect of genetic structure on molecular dating and tests for temporal signal.Methods in ecology and evolution · 2016Article
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Authors and funding
4 authors.
Funding
Abstract
Quantifying the dynamics of intrahost HIV-1 sequence evolution is one means of uncovering information about the interaction between HIV-1 and the host immune system. In the chronic phase of infection, common dynamics of sequence divergence and diversity have been reported. We developed an HIV-1 sequence evolution model that simulated the effects of mutation and fitness of sequence variants. The amount of evolution was described by the distance from the founder strain, and fitness was described by the number of offspring a parent sequence produces. Analysis of the model suggested that the previously observed saturation of divergence and decrease of diversity in later stages of infection can be explained by a decrease in the proportion of offspring that are mutants as the distance from the founder strain increases rather than due to an increase of viral fitness. The prediction of the model was examined by performing phylogenetic analysis to estimate the change in the rate of evolution during infection. In agreement with our modeling, in 13 out of 15 patients (followed for 3-12 years) we found that the rate of intrahost HIV-1 evolution was not constant but rather slowed down at a rate correlated with the rate of CD4+ T-cell decline. The correlation between the dynamics of the evolutionary rate and the rate of CD4+ T-cell decline, coupled with our HIV-1 sequence evolution model, explains previously conflicting observations of the relationships between the rate of HIV-1 quasispecies evolution and disease progression.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.