Evidence map›Paper›PMID 37831083›Full record

ArticleNucleic acids research2024

PharmGWAS: a GWAS-based knowledgebase for drug repurposing.

Hongen Kang, Siyu Pan, Shiqi Lin, Yin-Ying Wang, Na Yuan, Peilin Jia

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.2field-weighted citation impact, top 5% 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

15 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Old drugs, new challenges: reassigning drugs for cancer therapies.Cellular & molecular biology letters · 2025
    Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Genomic strategies for drug repurposing.Journal of the Egyptian National Cancer Institute · 2024
    Review
  14. Review
  15. RNA Sequencing in Disease Diagnosis.Annual review of genomics and human genetics · 2024
    Review
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

6 authors at 1 institution in 1 country.

Hongen KangCAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-9581-1329
Siyu PanCAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.
Shiqi LinCAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.
Yin-Ying WangCAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.
Na YuanCAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0003-3614-2441
Peilin JiaCAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0003-4523-4153
Chinese Academy of Sciences · CN

Funding

National Natural Science Foundation of China 32270706Startup Research Fund of Henan Academy of Sciences 232016009Strategic Priority Research Program of the Chinese Academy of Sciences
6 · The paper itself

Abstract

Leveraging genetics insights to promote drug repurposing has become a promising and active strategy in pharmacology. Indeed, among the 50 drugs approved by FDA in 2021, two-thirds have genetically supported evidence. In this regard, the increasing amount of widely available genome-wide association studies (GWAS) datasets have provided substantial opportunities for drug repurposing based on genetics discoveries. Here, we developed PharmGWAS, a comprehensive knowledgebase designed to identify candidate drugs through the integration of GWAS data. PharmGWAS focuses on novel connections between diseases and small-molecule compounds derived using a reverse relationship between the genetically-regulated expression signature and the drug-induced signature. Specifically, we collected and processed 1929 GWAS datasets across a diverse spectrum of diseases and 724 485 perturbation signatures pertaining to a substantial 33609 molecular compounds. To obtain reliable and robust predictions for the reverse connections, we implemented six distinct connectivity methods. In the current version, PharmGWAS deposits a total of 740 227 genetically-informed disease-drug pairs derived from drug-perturbation signatures, presenting a valuable and comprehensive catalog. Further equipped with its user-friendly web design, PharmGWAS is expected to greatly aid the discovery of novel drugs, the exploration of drug combination therapies and the identification of drug resistance or side effects. PharmGWAS is available at https://ngdc.cncb.ac.cn/pharmgwas.

Indexed as

Databases, PharmaceuticalDrug RepositioningGenome-Wide Association Study

Identifiers

PMID37831083
PMCPMC10767932
OpenAlexW4387600082

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.