Evidence map›Paper›PMID 17616974›Full record

ArticlePLoS pathogens2007

Evidence of differential HLA class I-mediated viral evolution in functional and accessory/regulatory genes of HIV-1.

Zabrina L Brumme, Chanson J Brumme, David Heckerman, Bette T Korber, Marcus Daniels, Jonathan Carlson, Carl Kadie, Tanmoy Bhattacharya, Celia Chui, James Szinger and 7 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PLoS pathogens, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 113 papers.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed
8.2field-weighted citation impact, top 1% of its field
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

113 citing papers in PubMed, 166 citations in OpenAlex.

  1. Trial
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  3. Quantification of heterogeneity in human CD8Frontiers in immunology · 2024
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53 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

17 authors at 9 institutions in 2 countries.

Zabrina L BrummePartners AIDS Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
Chanson J Brumme
David Heckerman
Bette T Korber
Marcus Daniels
Jonathan Carlson
Carl Kadie
Tanmoy Bhattacharya
Celia Chui
James Szinger
Theresa Mo
Robert S Hogg
Julio S G Montaner
Nicole Frahm
Christian Brander
Bruce D Walker
P Richard Harrigan
AIDS Vancouver · CAHarvard University · USLos Alamos National Laboratory · USMicrosoft (United States) · USMassachusetts General Hospital · USSanta Fe Institute · USSimon Fraser University · CAUniversity of British Columbia · CAUniversity of Washington · US

Funding

PHS HHS N01-AL-15422
6 · The paper itself

Abstract

Despite the formidable mutational capacity and sequence diversity of HIV-1, evidence suggests that viral evolution in response to specific selective pressures follows generally predictable mutational pathways. Population-based analyses of clinically derived HIV sequences may be used to identify immune escape mutations in viral genes; however, prior attempts to identify such mutations have been complicated by the inability to discriminate active immune selection from virus founder effects. Furthermore, the association between mutations arising under in vivo immune selection and disease progression for highly variable pathogens such as HIV-1 remains incompletely understood. We applied a viral lineage-corrected analytical method to investigate HLA class I-associated sequence imprinting in HIV protease, reverse transcriptase (RT), Vpr, and Nef in a large cohort of chronically infected, antiretrovirally naïve individuals. A total of 478 unique HLA-associated polymorphisms were observed and organized into a series of "escape maps," which identify known and putative cytotoxic T lymphocyte (CTL) epitopes under selection pressure in vivo. Our data indicate that pathways to immune escape are predictable based on host HLA class I profile, and that epitope anchor residues are not the preferred sites of CTL escape. Results reveal differential contributions of immune imprinting to viral gene diversity, with Nef exhibiting far greater evidence for HLA class I-mediated selection compared to other genes. Moreover, these data reveal a significant, dose-dependent inverse correlation between HLA-associated polymorphisms and HIV disease stage as estimated by CD4(+) T cell count. Identification of specific sites and patterns of HLA-associated polymorphisms across HIV protease, RT, Vpr, and Nef illuminates regions of the genes encoding these products under active immune selection pressure in vivo. The high density of HLA-associated polymorphisms in Nef compared to other genes investigated indicates differential HLA class I-driven evolution in different viral genes. The relationship between HLA class I-associated polymorphisms and lower CD4(+) cell count suggests that immune escape correlates with disease status, supporting an essential role of maintenance of effective CTL responses in immune control of HIV-1. The design of preventative and therapeutic CTL-based vaccine approaches could incorporate information on predictable escape pathways.

Indexed as

Gene Expression Regulation, ViralSelection, GeneticAmino Acid SequenceCD4 Lymphocyte CountCD4-Positive T-LymphocytesEpitopes, T-LymphocyteEvolution, MolecularGenes, MHC Class IHistocompatibility Antigens Class IHIV-1Human Immunodeficiency Virus ProteinsHumansMinor Histocompatibility AntigensMolecular Sequence DataMutationnef Gene Products, Human Immunodeficiency VirusEpitopes, T-LymphocyteHistocompatibility Antigens Class IHuman Immunodeficiency Virus ProteinsMinor Histocompatibility AntigensMR1 protein, humannef Gene Products, Human Immunodeficiency VirusViral Regulatory and Accessory Proteinsvpr Gene Products, Human Immunodeficiency Virus

Identifiers

PMID17616974
PMCPMC1904471
OpenAlexW2107666854

What OpenQuestion holds

Textmetadata
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.