Evidence map›Paper›PMID 20659934›Full record

ArticleProceedings. Biological sciences2011

Evolutionary demography and quantitative genetics: age-specific survival as a threshold trait.

Jacob A Moorad, Daniel E L Promislow

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Intrinsic emergence and modulation of sex-specific dominance reversals in threshold traits.Evolution; international journal of organic evolution · 2022
    Article
  4. The Biology of Aging in Insects: FromAnnual review of entomology · 2022
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. 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

2 authors.

Jacob A MooradDepartment of Genetics, University of Georgia, Athens, GA, USA. jmoorad@uga.edu
Daniel E L Promislow

Funding

Research DevelopmentP30AG013283 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MILLER, RICHARD A · 1995 to 2014
$12.3M
T32 Administrative Supplement for Increase in Postdoc StipendsT32AG000139 · NIA · DUKE UNIVERSITY · PI LYNCH, SCOTT M. · 1987 to 2017
$4.0M
Explanations of Racial Disparities in Active LifeR03HD050374 · NICHD · PRINCETON UNIVERSITY · PI LYNCH, SCOTT M · 2005 to 2006
$156k
NIA NIH HHS P30 AG013283NIA NIH HHS P30-AG013283NIA NIH HHS T32 AG000139NICHD NIH HHS R03 HD050374
6 · The paper itself

Abstract

Researchers must understand how mutations affect survival at various ages to understand how ageing evolves. Many models linking mutation to age-specific survival have been proposed but there is little evidence to indicate which model is most appropriate. This is a serious problem because the predicted evolutionary endpoints of ageing depend upon the details of the specific model. We apply an explicitly quantitative genetic perspective to the problem. To determine the inheritance of dichotomous traits (such as survival), quantitative genetics has long employed a threshold model. Beginning from first principles, we show how this is the most defensible mutational model for age-specific survival and how this, relative to the standard model, predicts delayed senescence and mortality deceleration at late age. These are commonly observed patterns of ageing that heretofore have required more complicated survival models. We also show how this model can be developed further to unify quantitative genetics and evolutionary demography into a more complete conceptual framework for understanding the evolution of ageing.

Indexed as

Biological EvolutionModels, GeneticAge FactorsAgingComputer SimulationHumansMutationSelection, GeneticSurvival Rate

Identifiers

PMID20659934
PMCPMC2992720

What OpenQuestion holds

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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.