Evidence map›Paper›PMID 26582028›Full record

ArticleProceedings. Biological sciences2015

Health trajectories reveal the dynamic contributions of host genetic resistance and tolerance to infection outcome.

Graham Lough, Ilias Kyriazakis, Silke Bergmann, Andreas Lengeling, Andrea B Doeschl-Wilson

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings. Biological sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
7.2field-weighted citation impact, top 3% 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

20 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
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  5. Article
  6. Review
  7. Potential of genomic technologies to improve disease resistance in molluscan aquaculture.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Review
  8. Article
  9. Why breed disease-resilient livestock, and how?Genetics, selection, evolution : GSE · 2020
    Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
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  17. Review
  18. Article
  19. Article
  20. Beyond killing: Can we find new ways to manage infection?Evolution, medicine, and public health · 2016
    Review
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

5 authors at 4 institutions in 2 countries.

Graham LoughGenetics and Genomics Division, The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, UK.
Ilias KyriazakisSchool of Agriculture, Food and Rural Development, Newcastle University, Newcastle upon Tyne, UK.
Silke BergmannDepartment of Infection Genetics, Helmholtz Centre for Infection Research, Braunschweig, Germany.
Andreas LengelingInfection and Immunity Division, The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, UK.
Andrea B Doeschl-WilsonGenetics and Genomics Division, The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, UK andrea.wilson@roslin.ed.ac.uk.
Genomics (United Kingdom) · GBHelmholtz Centre for Infection Research · DENewcastle University · GBRoslin Institute · GB

Funding

Biotechnology and Biological Sciences Research Council BBS/E/D/20211554
6 · The paper itself

Abstract

Resistance and tolerance are two alternative strategies hosts can adopt to survive infections. Both strategies may be genetically controlled. To date, the relative contribution of resistance and tolerance to infection outcome is poorly understood. Here, we use a bioluminescent Listeria monocytogenes (Lm) infection challenge model to study the genetic determination and dynamic contributions of host resistance and tolerance to listeriosis in four genetically diverse mouse strains. Using conventional statistical analyses, we detect significant genetic variation in both resistance and tolerance, but cannot capture the time-dependent relative importance of either host strategy. We overcome these limitations through the development of novel statistical tools to analyse individual infection trajectories portraying simultaneous changes in infection severity and health. Based on these tools, early expression of resistance followed by expression of tolerance emerge as important hallmarks for surviving Lm infections. Our trajectory analysis further reveals that survivors and non-survivors follow distinct infection paths (which are also genetically determined) and provides new survival thresholds as objective endpoints in infection experiments. Future studies may use trajectories as novel traits for mapping and identifying genes that control infection dynamics and outcome. A Matlab script for user-friendly trajectory analysis is provided.

Indexed as

Genetic VariationImmune ToleranceMiceAnimalsFemaleListeria monocytogenesListeriosisMice, Inbred StrainsRodent Diseasescomplex traits geneticshost response strategiesinfection dynamicsresistancetolerancetrajectories

Identifiers

PMID26582028
PMCPMC4685823
OpenAlexW2345985659

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.