Evidence map›Paper›PMID 34302145›Full record

ReviewNature reviews. Genetics2021

Advancing the use of genome-wide association studies for drug repurposing.

William R Reay, Murray J Cairns

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 186 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
186citing papers in PubMed, 11 pooled it
37.9field-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

186 citing papers in PubMed, 11 syntheses or guidelines pooled it, 287 citations in OpenAlex.

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  6. Genome-wide meta-analysis identifies ancestry-specific loci for Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
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  12. Big data and psychiatry: advances, constraints and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026
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126 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

2 authors at 1 institution in 1 country.

William R ReaySchool of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, New South Wales, Australia.
Murray J CairnsSchool of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, New South Wales, Australia. murray.cairns@newcastle.edu.au.ORCID http://orcid.org/0000-0003-2490-2538
Hunter Medical Research Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have revealed important biological insights into complex diseases, which are broadly expected to lead to the identification of new drug targets and opportunities for treatment. Drug development, however, remains hampered by the time taken and costs expended to achieve regulatory approval, leading many clinicians and researchers to consider alternative paths to more immediate clinical outcomes. In this Review, we explore approaches that leverage common variant genetics to identify opportunities for repurposing existing drugs, also known as drug repositioning. These approaches include the identification of compounds by linking individual loci to genes and pathways that can be pharmacologically modulated, transcriptome-wide association studies, gene-set association, causal inference by Mendelian randomization, and polygenic scoring.

Indexed as

Gene Regulatory NetworksGenome-Wide Association StudyMultifactorial InheritancePolymorphism, Single NucleotideDrug RepositioningHumansPharmaceutical PreparationsTranscriptomePharmaceutical Preparations

Identifiers

PMID34302145
OpenAlexW3184279863

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.