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Synonymous Substitution Rates Predict HIV Disease Progression as a Result of Underlying Replication Dynamics

Overview of attention for article published in PLoS Computational Biology, February 2007
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Title
Synonymous Substitution Rates Predict HIV Disease Progression as a Result of Underlying Replication Dynamics
Published in
PLoS Computational Biology, February 2007
DOI 10.1371/journal.pcbi.0030029
Pubmed ID
Authors

Philippe Lemey, Sergei L Kosakovsky Pond, Alexei J Drummond, Oliver G Pybus, Beth Shapiro, Helena Barroso, Nuno Taveira, Andrew Rambaut

Abstract

Upon HIV transmission, some patients develop AIDS in only a few months, while others remain disease free for 20 or more years. This variation in the rate of disease progression is poorly understood and has been attributed to host genetics, host immune responses, co-infection, viral genetics, and adaptation. Here, we develop a new "relaxed-clock" phylogenetic method to estimate absolute rates of synonymous and nonsynonymous substitution through time. We identify an unexpected association between the synonymous substitution rate of HIV and disease progression parameters. Since immune activation is the major determinant of HIV disease progression, we propose that this process can also determine viral generation times, by creating favourable conditions for HIV replication. These conclusions may apply more generally to HIV evolution, since we also observed an overall low synonymous substitution rate for HIV-2, which is known to be less pathogenic than HIV-1 and capable of tempering the detrimental effects of immune activation. Humoral immune responses, on the other hand, are the major determinant of nonsynonymous rate changes through time in the envelope gene, and our relaxed-clock estimates support a decrease in selective pressure as a consequence of immune system collapse.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
United Kingdom 3 2%
Chile 2 1%
Brazil 2 1%
France 1 <1%
Sweden 1 <1%
South Africa 1 <1%
India 1 <1%
Kenya 1 <1%
Other 4 2%
Unknown 159 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 50 28%
Student > Ph. D. Student 47 26%
Student > Master 17 9%
Professor 14 8%
Professor > Associate Professor 13 7%
Other 28 16%
Unknown 11 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 94 52%
Biochemistry, Genetics and Molecular Biology 24 13%
Medicine and Dentistry 9 5%
Immunology and Microbiology 8 4%
Computer Science 7 4%
Other 17 9%
Unknown 21 12%