Evidence map›Paper›PMID 27957775›Full record

ArticleHuman mutation2017

Landscape of Pleiotropic Proteins Causing Human Disease: Structural and System Biology Insights.

Sirawit Ittisoponpisan, Eman Alhuzimi, Michael J E Sternberg, Alessia David

Open access · bronzeAbstract read
In one paragraph

Article in Human mutation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

29 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. Phenotype-Specific Recalibration of MAVE Data Enables Repurposing ofmedRxiv : the preprint server for health sciences · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Putting proteins in context.Cell systems · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Contextual AI models for single-cell protein biology.bioRxiv : the preprint server for biology · 2024
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Sirawit IttisoponpisanStructural Bioinformatics Group, Department of Life Sciences, Imperial College London, London, UK.
Eman AlhuzimiStructural Bioinformatics Group, Department of Life Sciences, Imperial College London, London, UK.
Michael J E SternbergStructural Bioinformatics Group, Department of Life Sciences, Imperial College London, London, UK.
Alessia DavidStructural Bioinformatics Group, Department of Life Sciences, Imperial College London, London, UK.
Imperial College London · GB

Funding

Medical Research Council MR/K021613/1Wellcome Trust
6 · The paper itself

Abstract

Pleiotropy is the phenomenon by which the same gene can result in multiple phenotypes. Pleiotropic proteins are emerging as important contributors to rare and common disorders. Nevertheless, little is known on the mechanisms underlying pleiotropy and the characteristic of pleiotropic proteins. We analyzed disease-causing proteins reported in UniProt and observed that 12% are pleiotropic (variants in the same protein cause more than one disease). Pleiotropic proteins were enriched in deleterious and rare variants, but not in common variants. Pleiotropic proteins were more likely to be involved in the pathogenesis of neoplasms, neurological, and circulatory diseases and congenital malformations, whereas non-pleiotropic proteins in endocrine and metabolic disorders. Pleiotropic proteins were more essential and had a higher number of interacting partners compared with non-pleiotropic proteins. Significantly more pleiotropic than non-pleiotropic proteins contained at least one intrinsically long disordered region (P < 0.001). Deleterious variants occurring in structurally disordered regions were more commonly found in pleiotropic, rather than non-pleiotropic proteins. In conclusion, pleiotropic proteins are an important contributor to human disease. They represent a biologically different class of proteins compared with non-pleiotropic proteins and a better understanding of their characteristics and genetic variants can greatly aid in the interpretation of genetic studies and drug design.

Indexed as

Genetic Association StudiesGenetic PleiotropyGenetic Predisposition to DiseaseComputational BiologyDatabases, GeneticHomeodomain ProteinsHumansIntrinsically Disordered ProteinsModels, MolecularOdds RatioProtein BindingProtein ConformationProteinsSignal TransductionStructure-Activity RelationshipSystems BiologyHomeodomain ProteinsIntrinsically Disordered ProteinsProteinsVinculindisordered protein regiongenetic variantshuman diseasepleiotropy

Identifiers

PMID27957775
PMCPMC5748329
OpenAlexW2566212027

What OpenQuestion holds

Textmetadata
LicenceTDM
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.