Evidence map›Paper›PMID 39116192›Full record

ArticlePLoS pathogens2024

Using viral diversity to identify HIV-1 variants under HLA-dependent selection in a systematic viral genome-wide screen.

Nadia Neuner-Jehle, Marius Zeeb, Christian W Thorball, Jacques Fellay, Karin J Metzner, Paul Frischknecht, Kathrin Neumann, Christine Leeman, Andri Rauch, Marcel Stöckle and 10 more

Abstract read
In one paragraph

Article in PLoS pathogens, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

20 authors.

Nadia Neuner-JehleDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.ORCID https://orcid.org/0009-0001-6829-6448
Marius ZeebDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Christian W ThorballPrecision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Jacques FellayPrecision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Karin J MetznerDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Paul FrischknechtDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Kathrin NeumannDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Christine LeemanDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Andri RauchDepartment of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland.
Marcel StöckleDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland.
Michael HuberInstitute of Medical Virology, University of Zurich, Zurich, Switzerland.
Matthieu PerreauDivisions of Immunology and Allergy, Lausanne University Hospital, Lausanne, Switzerland.
Enos BernasconiDivision of Infectious Diseases, Ente Ospedaliero Cantonale, Lugano, University of Geneva and University of Southern Switzerland, Lugano, Switzerland.
Julia NotterDivision of Infectious Diseases, Infection Prevention and Travel Medicine, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.
Matthias HoffmannDivision of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital Olten, Olten, Switzerland.
Karoline LeuzingerClinical Virology, University Hospital Basel, Basel, Switzerland.
Huldrych F GünthardDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Chloé PasinDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Roger D KouyosDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0002-9220-8348
Swiss HIV Cohort Study (SHCS)

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pathogenesis of HIV-1 infection is governed by a highly dynamic, time-dependent interaction between the host and the viral genome. In this study, we developed a novel systematic approach to assess the host-virus interaction, using average pairwise viral diversity as a proxy for time since infection, and applied this method to nearly whole viral genome sequences (n = 4,464), human leukocyte antigen (HLA) genotyping data (n = 1,044), and viral RNA load (VL) measurements during the untreated chronic phase (n = 829) of Swiss HIV Cohort Study participants. Our systematic genome-wide screen revealed for 98 HLA/viral-variant pairs a signature of immune-driven selection in the form of an HLA-dependent effect of infection time on the presence of HIV amino acid variants. Of these pairs, 12 were found to have an effect on VL. Furthermore, 28/58 pairs were validated by time-to-event analyses and 48/92 by computational HLA-epitope predictions. Our diversity-based approach allows a powerful and systematic investigation of the interaction between the virus and cellular immunity, revealing a notable subset of such interaction effects. From an evolutionary perspective, these observations underscore the complexity of HLA-mediated selection pressures on the virus that shape viral evolution and pathogenesis.

Indexed as

Genome, ViralHIV-1HIV InfectionsHLA AntigensCohort StudiesGenetic VariationHost-Pathogen InteractionsHumansSelection, GeneticViral LoadHLA Antigens

Identifiers

PMID39116192
PMCPMC11335148

What Socratic holds

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LicenceCC BY
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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 Socratic graph.