Evidence map›Paper›PMID 33262371›Full record

ArticleScientific reports2020

Network and pathway expansion of genetic disease associations identifies successful drug targets.

Aidan MacNamara, Nikolina Nakic, Ali Amin Al Olama, Cong Guo, Karsten B Sieber, Mark R Hurle, Alex Gutteridge

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

23 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Mapping cross-domain drivers of Alzheimer's disease risk through integrated network analysis.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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  13. Pathway Analysis Interpretation in the Multi-Omic Era.Biotech (Basel (Switzerland)) · 2025
    Review
  14. Article
  15. Review
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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

7 authors at 2 institutions in 1 country.

Aidan MacNamaraFunctional Genomics, GSK, Stevenage, UK.
Nikolina NakicFunctional Genomics, GSK, Stevenage, UK.
Ali Amin Al OlamaHuman Genetics, GSK, Stevenage, UK.
Cong GuoHuman Genetics, GSK, Collegeville, PA, USA.
Karsten B SieberHuman Genetics, GSK, Collegeville, PA, USA.
Mark R HurleHuman Genetics, GSK, Collegeville, PA, USA.
Alex GutteridgeBioinformatics, Lonza, Cambridge, UK. alex.gutteridge@lonza.com.
Age UK · GBLonza (United Kingdom) · GB

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_QA137853
6 · The paper itself

Abstract

Genetic evidence of disease association has often been used as a basis for selecting of drug targets for complex common diseases. Likewise, the propagation of genetic evidence through gene or protein interaction networks has been shown to accurately infer novel disease associations at genes for which no direct genetic evidence can be observed. However, an empirical test of the utility of combining these approaches for drug discovery has been lacking. In this study, we examine genetic associations arising from an analysis of 648 UK Biobank GWAS and evaluate whether targets identified as proxies of direct genetic hits are enriched for successful drug targets, as measured by historical clinical trial data. We find that protein networks formed from specific functional linkages such as protein complexes and ligand-receptor pairs are suitable for even naïve guilt-by-association network propagation approaches. In addition, more sophisticated approaches applied to global protein-protein interaction networks and pathway databases, also successfully retrieve targets enriched for clinically successful drug targets. We conclude that network propagation of genetic evidence can be used for drug target identification.

Indexed as

Gene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyMolecular Targeted TherapyDrug Delivery SystemsHumansHyperlipidemiasModels, GeneticSignal Transduction

Identifiers

PMID33262371
PMCPMC7708424
OpenAlexW3109566584

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.