Evidence map›Paper›PMID 41256806›Full record

ArticleNAR molecular medicine2024

Trends in drug development for rare and intractable diseases based on the KEGG NETWORK.

Mao Tanabe, Makoto Hirata, Ryuichi Sakate

Abstract read
In one paragraph

Article in NAR molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mao TanabeLaboratory of Rare Disease Information and Resource Library, Center for Intractable Diseases and ImmunoGenomics (CiDIG), National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), Ibaraki, Osaka 567-0085, Japan.ORCID https://orcid.org/0000-0002-2160-5004
Makoto HirataLaboratory of Rare Disease Information and Resource Library, Center for Intractable Diseases and ImmunoGenomics (CiDIG), National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), Ibaraki, Osaka 567-0085, Japan.
Ryuichi SakateLaboratory of Rare Disease Information and Resource Library, Center for Intractable Diseases and ImmunoGenomics (CiDIG), National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), Ibaraki, Osaka 567-0085, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pathophysiological mechanisms underlying many rare and intractable diseases remain unclear, and there are few drugs for the treatment of these diseases. An understanding of approved drugs is important to improve drug development. In DDrare (Database of Drug Development for Rare Diseases), the targets of drugs in clinical trials are mapped to the KEGG PATHWAY to be grasped on molecular networks. In this study, to understand the relationship between drug targets and disease genes, we mapped them to the KEGG NETWORK (networks) defined as functionally meaningful segments of pathways. We found that disease genes tended to be included in networks characteristic for each disease group, whereas drug targets were mapped to networks common to many disease groups. The number of drugs targeting the networks containing disease genes was small in every disease group. However, because several studies have recently addressed that the drugs targeting proteins with genetic evidence of disease association are more likely to be approved, we confirmed the results using the KEGG NETWORK and integrating the risk genes obtained from the latest GWAS data. The results were clearer and more detailed than those of previous studies, which suggests a direction for future drug development.

Identifiers

PMID41256806
PMCPMC12429956

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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.