Evidence map›Paper›PMID 26405030›Full record

ArticleGenetics2015

A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission.

Osvaldo Anacleto, Luis Alberto Garcia-Cortés, Debby Lipschutz-Powell, John A Woolliams, Andrea B Doeschl-Wilson

Open access · bronzeAbstract readValidation Study
In one paragraph

Article in Genetics, 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
6.2field-weighted citation impact, top 4% 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
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review: Livestock disease resilience: from individual to herd level.Animal : an international journal of animal bioscience · 2021
    Review
  7. Article
  8. Article
  9. Article
  10. The economic value of RGenetics, selection, evolution : GSE · 2020
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Derivation of the economic value of RGenetics, selection, evolution : GSE · 2018
    Article
  16. Can We Breed Cattle for Lower Bovine TB Infectivity?Frontiers in veterinary science · 2018
    Article
  17. Article
  18. Article
  19. Article
  20. 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

5 authors at 4 institutions in 2 countries.

Osvaldo AnacletoThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, Midlothian EH25 9PS, United Kingdom osvaldo.anacleto@roslin.ed.ac.uk.
Luis Alberto Garcia-CortésDepartamento de Mejora Genética, Instituto Nacional de Investigación Agraria, Ctra. de La Coruña km. 7.5, Madrid 28040, Spain.
Debby Lipschutz-PowellDepartment of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom.
John A WoolliamsThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, Midlothian EH25 9PS, United Kingdom.
Andrea B Doeschl-WilsonThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, Midlothian EH25 9PS, United Kingdom.
University of Edinburgh · GBInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria · ESRoslin Institute · GBUniversity of Cambridge · GB

Funding

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

Abstract

There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations.

Indexed as

Disease Transmission, InfectiousGenetic Predisposition to DiseaseModels, GeneticModels, StatisticalAnimalsBayes TheoremComputer SimulationDisease OutbreaksHumansMultifactorial InheritanceBayesian statisticscomplex traitsdisease resistanceinfectivityquantitative genetics

Identifiers

PMID26405030
PMCPMC4649657
OpenAlexW2120932103

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.