Evidence map›Paper›PMID 34868244›Full record

ReviewFrontiers in genetics2021

Maintenance of Complex Trait Variation: Classic Theory and Modern Data.

Evan M Koch, Shamil R Sunyaev

Abstract readReview
In one paragraph

Review in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Parameterizing the genetic architecture under stabilizing selection.bioRxiv : the preprint server for biology · 2026
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  10. Evolutionary psychiatry: foundations, progress and challenges.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2023
    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.

Evan M KochDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, United States.
Shamil R SunyaevDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, United States.

Funding

Statistical methods for studies of rare variantsR01MH101244 · NIMH · HARVARD MEDICAL SCHOOL · PI Benjamin Michael Neale, ALKES L PRICE · 2013 to 2026
$9.4M
The origin, the function and the phenotypic impact of human allelesR35GM127131 · NIGMS · HARVARD MEDICAL SCHOOL · PI SHAMIL SUNYAEV · 2018 to 2026
$8.1M
Statistical Methods for the Design and Interpretation of Deep Resequencing StudieR01MH084676 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI SUNYAEV, SHAMIL · 2008 to 2010
$1.7M
NIGMS NIH HHS R35 GM127131NIMH NIH HHS R01 MH084676NIMH NIH HHS R01 MH101244
6 · The paper itself

Abstract

Numerous studies have found evidence that GWAS loci experience negative selection, which increases in intensity with the effect size of identified variants. However, there is also accumulating evidence that this selection is not entirely mediated by the focal trait and contains a substantial pleiotropic component. Understanding how selective constraint shapes phenotypic variation requires advancing models capable of balancing these and other components of selection, as well as empirical analyses capable of inferring this balance and how it is generated by the underlying biology. We first review the classic theory connecting phenotypic selection to selection at individual loci as well as approaches and findings from recent analyses of negative selection in GWAS data. We then discuss geometric theories of pleiotropic selection with the potential to guide future modeling efforts. Recent findings revealing the nature of pleiotropic genetic variation provide clues to which genetic relationships are important and should be incorporated into analyses of selection, while findings that effect sizes vary between populations indicate that GWAS measurements could be misleading if effect sizes have also changed throughout human history.

Indexed as

evolutiongenome-wide association studypopulation geneticsquantitative geneticsstatistical genetics

Identifiers

PMID34868244
PMCPMC8636146

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Registered trials

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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.