Evidence map›Paper›PMID 39255323›Full record

ArticlePLoS computational biology2024

Antiviral capacity of the early CD8 T-cell response is predictive of natural control of SIV infection: Learning in vivo dynamics using ex vivo data.

Bharadwaj Vemparala, Vincent Madelain, Caroline Passaes, Antoine Millet, Véronique Avettand-Fenoel, Ramsès Djidjou-Demasse, Nathalie Dereuddre-Bosquet, Roger Le Grand, Christine Rouzioux, Bruno Vaslin and 3 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Modelling HIV-1 control and remission.NPJ systems biology and applications · 2024
    Review
  6. Article
  7. 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

13 authors.

Bharadwaj VemparalaDepartment of Chemical Engineering, Indian Institute of Science, Bengaluru, India.ORCID 0000-0002-9469-1847
Vincent MadelainUniversité Paris Cité, IAME, INSERM, Paris, France.
Caroline PassaesInstitut Pasteur, Université Paris Cité, Viral Reservoirs and Immune Control Unit, Paris, France.
Antoine MilletINSERM U1016, CNRS UMR8104, Université Paris Cité Institut Cochin, Paris, France.
Véronique Avettand-FenoelINSERM U1016, CNRS UMR8104, Université Paris Cité Institut Cochin, Paris, France.ORCID 0000-0002-7022-2990
Ramsès Djidjou-DemasseMIVEGEC, University of Montpellier, CNRS, IRD, Montpellier, France.
Nathalie Dereuddre-BosquetCEA, Université Paris-Saclay, INSERM U1184, Immunology of Viral, Autoimmune, Hematologic and Bacterial Diseases (IMVAHB), IDMIT Department/ IBFJ, Fontenay-aux-Roses, France.
Roger Le GrandCEA, Université Paris-Saclay, INSERM U1184, Immunology of Viral, Autoimmune, Hematologic and Bacterial Diseases (IMVAHB), IDMIT Department/ IBFJ, Fontenay-aux-Roses, France.
Christine RouziouxINSERM U1016, CNRS UMR8104, Université Paris Cité Institut Cochin, Paris, France.
Bruno VaslinCEA, Université Paris-Saclay, INSERM U1184, Immunology of Viral, Autoimmune, Hematologic and Bacterial Diseases (IMVAHB), IDMIT Department/ IBFJ, Fontenay-aux-Roses, France.
Asier Sáez-CiriónInstitut Pasteur, Université Paris Cité, Viral Reservoirs and Immune Control Unit, Paris, France.
Jérémie GuedjUniversité Paris Cité, IAME, INSERM, Paris, France.
Narendra M DixitDepartment of Chemical Engineering, Indian Institute of Science, Bengaluru, India.ORCID 0000-0002-2145-9828

Funding

FCPAR/CEFIPRA Project 64T4-2French National Agency of AIDS and Viral Hepatitis Research (ANRS)MSDAvenir
6 · The paper itself

Abstract

While most individuals suffer progressive disease following HIV infection, a small fraction spontaneously controls the infection. Although CD8 T-cells have been implicated in this natural control, their mechanistic roles are yet to be established. Here, we combined mathematical modeling and analysis of previously published data from 16 SIV-infected macaques, of which 12 were natural controllers, to elucidate the role of CD8 T-cells in natural control. For each macaque, we considered, in addition to the canonical in vivo plasma viral load and SIV DNA data, longitudinal ex vivo measurements of the virus suppressive capacity of CD8 T-cells. Available mathematical models do not allow analysis of such combined in vivo-ex vivo datasets. We explicitly modeled the ex vivo assay, derived analytical approximations that link the ex vivo measurements with the in vivo effector function of CD8-T cells, and integrated them with an in vivo model of virus dynamics, thus developing a new learning framework that enabled the analysis. Our model fit the data well and estimated the recruitment rate and/or maximal killing rate of CD8 T-cells to be up to 2-fold higher in controllers than non-controllers (p = 0.013). Importantly, the cumulative suppressive capacity of CD8 T-cells over the first 4-6 weeks of infection was associated with virus control (Spearman's ρ = -0.51; p = 0.05). Thus, our analysis identified the early cumulative suppressive capacity of CD8 T-cells as a predictor of natural control. Furthermore, simulating a large virtual population, our model quantified the minimum capacity of this early CD8 T-cell response necessary for long-term control. Our study presents new, quantitative insights into the role of CD8 T-cells in the natural control of HIV infection and has implications for remission strategies.

Indexed as

CD8-Positive T-LymphocytesSimian Acquired Immunodeficiency SyndromeSimian Immunodeficiency VirusViral LoadAnimalsComputational BiologyMacaca mulattaModels, Immunological

Identifiers

PMID39255323
PMCPMC11414924

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.