Evidence map›Paper›PMID 20219734›Full record

ArticleProceedings. Biological sciences2010

How fast could HIV change gene frequencies in the human population?

Deborah Cromer, Steven M Wolinsky, Angela R McLean

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Antiretroviral therapy blocks natural selection on protective and disease-susceptible HLA-B alleles in HIV-1 infection.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. The global spread of HIV-1 subtype B epidemic.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2016
    Article
  3. Article
  4. Article
  5. Article
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

3 authors.

Deborah CromerZoology Department, Institute for Emerging Infections, James Martin 21st Century School, University of Oxford, Oxford, UK. deborahcromer@yahoo.com
Steven M Wolinsky
Angela R McLean

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Infectious diseases have the potential to act as strong forces for genetic selection on the populations they affect. Human immunodeficiency virus (HIV) is a prime candidate to impose such genetic selection owing to the vast number of people it infects and the varying susceptibility of different human leucocyte antigen (HLA) types to HIV disease progression. We have constructed a model of HIV infection that differentiates between these HLA types, and have used reported estimates of the number of people infected with HIV and the different rates of progression to acquired immunodeficiency syndrome (AIDS) to provide a lower bound estimate on the length of time it would take for HIV to impose major genetic change in humans. We find that an HIV infection similar to that currently affecting sub-Saharan Africa could not yet have caused more than a 3 per cent decrease in the proportion of individuals who progress quickly to disease. Such an infection is unlikely to cause major genetic change (defined as a decrease in the proportion of quickly progressing individuals to under 50 per cent of their starting proportion) until 400 years have passed since HIV emergence. However, in very severely affected populations, there is a chance of observing such major genetic changes after another 50 years.

Indexed as

Gene FrequencyGenetics, PopulationHIV InfectionsModels, BiologicalSelection, GeneticDisease ProgressionHIVHumansPrevalenceTime Factors

Identifiers

PMID20219734
PMCPMC2880090

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.