Evidence map›Paper›PMID 22665443›Full record

ReviewGenome research2012

Human genomic disease variants: a neutral evolutionary explanation.

Joel T Dudley, Yuseob Kim, Li Liu, Glenn J Markov, Kristyn Gerold, Rong Chen, Atul J Butte, Sudhir Kumar

Abstract readReview
In one paragraph

Review in Genome research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Neutral Theory, Disease Mutations, and Personal Exomes.Molecular biology and evolution · 2018
    Article
  12. γ2 GABAFrontiers in cellular neuroscience · 2018
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. A Molecular Evolutionary Reference for the Human Variome.Molecular biology and evolution · 2016
    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

8 authors.

Joel T DudleyProgram in Biomedical Informatics, Stanford University School of Medicine, Stanford, California 94305, USA.
Yuseob Kim
Li Liu
Glenn J Markov
Kristyn Gerold
Rong Chen
Atul J Butte
Sudhir Kumar

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
COMPARATIVE MOLECULAR SEQUENCE ANALYSISR01HG002096 · NHGRI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI KUMAR, SUDHIR · 2000 to 2013
$3.0M
Evolutionary Bioinformatics of Human MutationsR01LM010834 · NLM · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI KUMAR, SUDHIR · 2010 to 2012
$1.1M
Integrating Microarray and Proteomic Data by Ontology-based AnnotationR01LM009719 · NLM · STANFORD UNIVERSITY · PI BUTTE, ATUL J · 2008 to 2011
$1.1M
NHGRI NIH HHS R01 HG002096NLM NIH HHS R01 LM009719NLM NIH HHS R01 LM010834NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

Many perspectives on the role of evolution in human health include nonempirical assumptions concerning the adaptive evolutionary origins of human diseases. Evolutionary analyses of the increasing wealth of clinical and population genomic data have begun to challenge these presumptions. In order to systematically evaluate such claims, the time has come to build a common framework for an empirical and intellectual unification of evolution and modern medicine. We review the emerging evidence and provide a supporting conceptual framework that establishes the classical neutral theory of molecular evolution (NTME) as the basis for evaluating disease- associated genomic variations in health and medicine. For over a decade, the NTME has already explained the origins and distribution of variants implicated in diseases and has illuminated the power of evolutionary thinking in genomic medicine. We suggest that a majority of disease variants in modern populations will have neutral evolutionary origins (previously neutral), with a relatively smaller fraction exhibiting adaptive evolutionary origins (previously adaptive). This pattern is expected to hold true for common as well as rare disease variants. Ultimately, a neutral evolutionary perspective will provide medicine with an informative and actionable framework that enables objective clinical assessment beyond convenient tendencies to invoke past adaptive events in human history as a root cause of human disease.

Indexed as

Evolution, MolecularGenetic VariationGenome, HumanAdaptation, BiologicalAllelesGene FrequencyGenetic Diseases, InbornGenetic Predisposition to DiseaseGenetics, PopulationHumansMolecular MedicineSelection, Genetic

Identifiers

PMID22665443
PMCPMC3409252

What OpenQuestion holds

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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.