Evidence map›Paper›PMID 29164333›Full record

ArticleHuman genetics2018

The ubiquity of pleiotropy in human disease.

Kevin Chesmore, Jacquelaine Bartlett, Scott M Williams

Open access · hybridAbstract read
PubMed Publisher
In one paragraph

Article in Human genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 1 pooled it
11.2field-weighted citation impact, top 1% of its field
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

66 citing papers in PubMed, 1 synthesis or guideline pooled it, 117 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Phenotype-Specific Recalibration of MAVE Data Enables Repurposing ofmedRxiv : the preprint server for health sciences · 2026
    Article
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  7. Article
  8. Review
  9. Article
  10. Local genetic correlation analysis of Alzheimer's disease and stroke implicatesmedRxiv : the preprint server for health sciences · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Convergent genetic adaptation ofFrontiers in molecular biosciences · 2024
    Article
  18. Patterns and evolutionary consequences of pleiotropy.Annual review of ecology, evolution, and systematics · 2023
    Article
  19. Article
  20. Article

6 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 at 2 institutions in 1 country.

Kevin ChesmoreDepartment of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA.
Jacquelaine BartlettDepartments of Population and Quantitative Health Sciences, Institute of Computational Biology, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA.
Scott M WilliamsDepartments of Population and Quantitative Health Sciences, Institute of Computational Biology, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA. smw154@case.edu.ORCID http://orcid.org/0000-0002-4835-9544
Case Western Reserve University · USDartmouth College · US

Funding

Quantitative Biology Research InstituteP20GM103534 · NIGMS · DARTMOUTH COLLEGE · PI AMOS, CHRISTOPHER I. · 2012 to 2016
$8.6M
Molecular and Cellular Biology at DartmouthT32GM008704 · NIGMS · DARTMOUTH COLLEGE · PI COMPTON, DUANE A. · 1998 to 2018
$6.8M
National Institute of General Medical Sciences P20GM103534National Institute of General Medical Sciences T32GM008704U.S. National Library of Medicine LM010098
6 · The paper itself

Abstract

Pleiotropy has long been thought to be a common phenomenon in the human genome; however, until recently appropriate data was unavailable to test this hypothesis. Prior studies focused on assessing the prevalence of pleiotropy in only small subsets of phenotypes (≤ 53 phenotypes), without a truly comprehensive assessment of pleiotropy in the human genome. In this study, we determined the prevalence of pleiotropy, using the entire GWAS catalog (1094 disease phenotypes, 14,459 genes), as well as investigate the relationship between the degree of pleiotropy and the average effect size for each associating gene. The number of associating phenotypes per gene ranged from 1 to 53, with 44% of genes reported in the GWAS catalog associating with more than one phenotype. The proportion of genes shown to be pleiotropic has continued to increase as more studies are added to the catalog. We also found the degree of pleiotropy scales positively with a gene's average effect size (r = 0.04, p value = 0.0003) and negatively with the variance of effect sizes in genes with a given number of associating phenotypes (r = - 0.590, p value = 0.0019). Based on this and prior work, it is becoming evident that pleiotropy is a common, if not ubiquitous, phenomenon. These results have implications in understanding disease etiologies, potentially common biology underlying even disparate diseases, and in elucidating the genotype-phenotype map.

Indexed as

Genetic Association StudiesGenetic PleiotropyGenome, HumanDiseaseHumansModels, GeneticPhenotype

Identifiers

PMID29164333
OpenAlexW2768144164

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.