Evidence map›Paper›PMID 24629526›Full record

ReviewTrends in genetics : TIG2014

Explaining additional genetic variation in complex traits.

Matthew R Robinson, Naomi R Wray, Peter M Visscher

Abstract readReview
In one paragraph

Review in Trends in genetics : TIG, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Darwinian genomics and diversity in the tree of life.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  10. Article
  11. Article
  12. Review
  13. De novo variation in bipolar disorder.Molecular psychiatry · 2021
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

8 more citing papers are in PubMed but not listed here.

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

3 authors.

Matthew R RobinsonThe Queensland Brain Institute, The University of Queensland, St Lucia, QLD 4072, Australia.
Naomi R WrayThe Queensland Brain Institute, The University of Queensland, St Lucia, QLD 4072, Australia.
Peter M VisscherThe Queensland Brain Institute, The University of Queensland, St Lucia, QLD 4072, Australia; The University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute, Brisbane, QLD 4102, Australia. Electronic address: peter.visscher@uq.edu.au.

Funding

Statistical Methods for X-Chromosome Genetic DataP01GM099568 · NIGMS · UNIVERSITY OF WASHINGTON · PI WEIR, BRUCE S. · 2012 to 2016
$7.3M
Estimating the genetic and environmental architecture of psychiatric disordersR01MH100141 · NIMH · UNIVERSITY OF COLORADO · PI KELLER, MATTHEW CHARLES · 2013 to 2022
$5.3M
Theoretical Population Genetics SupplementR01GM075091 · NIGMS · UNIVERSITY OF WASHINGTON · PI WEIR, BRUCE S. · 2006 to 2020
$4.7M
NIGMS NIH HHS GM075091NIGMS NIH HHS GM099568NIGMS NIH HHS P01 GM099568NIGMS NIH HHS R01 GM075091NIMH NIH HHS MH100141NIMH NIH HHS R01 MH100141
6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of complex traits, discovering >6000 variants associated with >500 quantitative traits and common complex diseases in humans. The associations identified so far represent only a fraction of those that influence phenotype, because there are likely to be many variants across the entire frequency spectrum, each of which influences multiple traits, with only a small average contribution to the phenotypic variance. This presents a considerable challenge to further dissection of the remaining unexplained genetic variance within populations, which limits our ability to predict disease risk, identify new drug targets, improve and maintain food sources, and understand natural diversity. This challenge will be met within the current framework through larger sample size, better phenotyping, including recording of nongenetic risk factors, focused study designs, and an integration of multiple sources of phenotypic and genetic information. The current evidence supports the application of quantitative genetic approaches, and we argue that one should retain simpler theories until simplicity can be traded for greater explanatory power.

Indexed as

Genetic VariationQuantitative Trait, HeritableAnimalsGenomeHumansPhenotype

Identifiers

PMID24629526
PMCPMC4639398

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.