The contribution of viral genotype to plasma viral set-point in HIV infection
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, usi...
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Published in: | PLoS pathogens Vol. 10; no. 5; p. e1004112 |
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Main Authors: | , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
United States
Public Library of Science
01-05-2014
Public Library of Science (PLoS) |
Subjects: | |
Online Access: | Get full text |
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Summary: | 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. |
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Bibliography: | Membership of the UK HIV Drug Resistance Database and the UK CHIC Study is provided at the end of this paper. Additional support for the UK HIV Resistance Database is provided by Boehringer Ingelheim, Bristol-Myers Squibb, Gilead, Tibotec (a division of Janssen-Cilag) and Roche. Although some authors have received funding from various commercial organizations for research, travel grants, speaking engagements or consultancy fees, neither those organizations nor the study funders had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript and this does not alter our adherence to all PLOS Pathogens policies on sharing data and materials. Conceived and designed the experiments: EH JDH AP AJLB. Performed the experiments: EF SO. Analyzed the data: EH JDH EF AJLB. Contributed reagents/materials/analysis tools: JDH SO DD DP. Wrote the paper: EH JDH AJLB. |
ISSN: | 1553-7374 1553-7366 1553-7374 |
DOI: | 10.1371/journal.ppat.1004112 |