Evidence map›Paper›PMID 24789308›Full record

ArticlePLoS pathogens2014

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

Emma Hodcroft, Jarrod D Hadfield, Esther Fearnhill, Andrew Phillips, David Dunn, Siobhan O'Shea, Deenan Pillay, Andrew J Leigh Brown, UK HIV Drug Resistance Database, UK CHIC Study

Abstract read
In one paragraph

Article in PLoS pathogens, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

  1. Trial
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  11. TheFuture virology · 2020
    Review
  12. Article
  13. Automatic generation of evolutionary hypotheses using mixed Gaussian phylogenetic models.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Emma HodcroftInstitute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Edinburgh, United Kingdom.
Jarrod D HadfieldInstitute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Edinburgh, United Kingdom.
Esther FearnhillMRC Clinical Trials Unit Aviation House, London, United Kingdom.
Andrew PhillipsInfection and Population Health, University College London, Royal Free Hospital, London, United Kingdom.
David DunnMRC Clinical Trials Unit Aviation House, London, United Kingdom.
Siobhan O'SheaDepartment of Infectious Diseases, King's College London, London, United Kingdom.
Deenan PillayResearch Department of Infection, University College London, London, United Kingdom.
Andrew J Leigh BrownInstitute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Edinburgh, United Kingdom.
UK HIV Drug Resistance Database
UK CHIC Study

Funding

Biotechnology and Biological Sciences Research CouncilDepartment of HealthMedical Research Council G0900274Medical Research Council MC_UU_12023/15Wellcome Trust 095831Wellcome Trust 097410
6 · The paper itself

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.

Indexed as

AdolescentAdultAgedAged, 80 and overFemaleGenotypeHIV-1HIV InfectionsHumansMaleMiddle AgedMolecular Sequence DataPhylogenyViral LoadYoung Adult

Identifiers

PMID24789308
PMCPMC4006911

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Registered trials

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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.