Evidence map›Paper›PMID 39391813›Full record

ArticleJID innovations : skin science from molecules to population health2024

Drug Repurposing Using Molecular Network Analysis Identifies Jak as Targetable Driver in Necrobiosis Lipoidica.

Alysia N Hughes, Xing Li, Julia S Lehman, Steven A Nelson, David J DiCaudo, Rekha Mudappathi, Angelina Hwang, Jacob Kechter, Mark R Pittelkow, Aaron R Mangold and 1 more

Abstract read
In one paragraph

Article in JID innovations : skin science from molecules to population health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Alysia N HughesDepartment of Dermatology, Mayo Clinic, Scottsdale, Arizona, USA.
Xing LiDepartment of Dermatology, Mayo Clinic, Scottsdale, Arizona, USA.
Julia S LehmanDepartment of Dermatology, Mayo Clinic, Rochester, Minnesota, USA.
Steven A NelsonDepartment of Dermatology, Mayo Clinic, Scottsdale, Arizona, USA.
David J DiCaudoDepartment of Dermatology, Mayo Clinic, Scottsdale, Arizona, USA.
Rekha MudappathiDepartment of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona, USA.
Angelina HwangDepartment of Dermatology, Mayo Clinic, Scottsdale, Arizona, USA.
Jacob KechterDepartment of Dermatology, Mayo Clinic, Scottsdale, Arizona, USA.
Mark R PittelkowDepartment of Dermatology, Mayo Clinic, Scottsdale, Arizona, USA.
Aaron R MangoldDepartment of Dermatology, Mayo Clinic, Scottsdale, Arizona, USA.
Aleksandar SekulicIntegrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, Arizona, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug repurposing is an attractive strategy for therapy development, particularly in rare diseases where traditional drug development approaches may be challenging owing to high cost and small numbers of patients. In this study, we used a drug identification and repurposing pipeline to identify candidate targetable drivers of disease and corresponding therapies through application of causal reasoning using a combination of open-access resources and transcriptomics data. We optimized our approach on psoriasis as a disease model, demonstrating the ability to identify known and, to date, unrecognized molecular drivers of psoriasis and link them to current and emerging therapies. Application of our approach to a cohort of tissue samples of necrobiosis lipoidica (an unrelated; rare; and, to date, molecularly poorly characterized cutaneous inflammatory disorder) identified a unique set of upstream regulators, particularly highlighting the role of IFNG and the Jak-signal transducer and activator of transcription pathway as a likely driver of disease pathogenesis and linked it to Jak inhibitors as potential therapy. Analysis of an independent cohort of necrobiosis lipoidica samples validated these findings, with the overall agreement of drug-matched upstream regulators above 96%. These data highlight the utility of our approach in rare diseases and offer an opportunity for drug discovery in other rare diseases in dermatology and beyond.

Indexed as

BioinformaticsDrug developmentGene RegulationGenomicsInflammatorySkin diseases

Identifiers

PMID39391813
PMCPMC11465178

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.