Evidence map›Paper›PMID 25567972›Full record

ArticleEvolutionary applications2011

Ten questions for evolutionary studies of disease vulnerability.

Randolph M Nesse

Abstract read
In one paragraph

Article in Evolutionary applications, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Evolutionary psychiatry: foundations, progress and challenges.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2023
    Article
  6. Integrating evolutionary, developmental and physiological mismatch.Evolution, medicine, and public health · 2023
    Review
  7. Review
  8. Article
  9. Review
  10. Review
  11. Quantifying simultaneous innovations in evolutionary medicine.Theory in biosciences = Theorie in den Biowissenschaften · 2020
    Article
  12. Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Evolution and medicine in undergraduate education: a prescription for all biology students.Evolution; international journal of organic evolution · 2012
    Article
  19. Nothing in medicine makes sense, except in the light of evolution.Journal of molecular medicine (Berlin, Germany) · 2012
    Review
  20. Evolutionary molecular medicine.Journal of molecular medicine (Berlin, Germany) · 2012
    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

1 author.

Randolph M NesseDepartments of Psychiatry and Psychology, Institute for Social Research, The University of Michigan Ann Arbor, MI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many evolutionary applications in medicine rely on well-established methods, such as population genetics, phylogenetic analysis, and observing pathogen evolution. Approaches to evolutionary questions about traits that leave bodies vulnerable to disease are less well developed. Strategies for formulating questions and hypotheses remain unsettled, and methods for testing evolutionary hypotheses are unfamiliar to many in medicine. This article uses recent examples to illustrate successful strategies and some common challenges. Ten questions arise in the course of considering hypotheses about traits that leave bodies vulnerable to disease. Addressing them systematically can help minimize confusion and errors.

Indexed as

Darwinian medicinediseaseevolutionary medicinehypothesis testingmethodologyvulnerability

Identifiers

PMID25567972
PMCPMC3352562

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.