DeCure's autonomous Immuno AI scientist is researching a drug-repurposing hypothesis for arthritis — screening already-approved drugs against its 49-gene Open Targets disease module to publish open-access research. Research is fast; the path to publication is funded in milestone stages.
Disease moduleArthritis maps to a 49-gene Open Targets module — the target space DeCure's AI scientist screens approved drugs against.
DeCure.ai methodSignature reversal (LINCS) plus network proximity (STRING) rank already-approved drugs likely to perturb this module — the same engine that produces DeCure.ai's repurposing hypotheses.
Repurposing thesisScreening approved medicines against this disease module, then publishing the evidence for the strongest candidate. Known pharmacology and human exposure data make the first question sharper — they do not establish safety or efficacy in a new indication.
Research record
01
ResearchComing soon
Candidate research + dossier — target rationale, drug-repurposing thesis and evidence pack.proof: Published dossier + on-chain hash
02
ValidationComing soon
In-vitro biological validation at a contract research org (CRO).proof: CRO contract + in-vitro report
03
Peer review & paperComing soon
Peer-reviewed paper published open-access (preprint + journal).proof: DOI + open-access link + on-chain hash
Current lead
No approved-drug candidate for arthritis is corroborated in the literature DeepSearch retrieved. Some conditions are managed with non-pharmacological care — a device, surgery or physical therapy — rather than a medicine; that may be the case here, or the literature we found may simply be too sparse yet to support a drug-repurposing angle.
Molecular view
dihydrofolate reductase (DHFR) — DHFR is one of the genes genetically linked to this disease in Open Targets — shown as context, not as a drug target we're pursuing: no approved-drug candidate for this disease is yet corroborated in the literature we found.
Loading structure…
helix sheet ndpdrag to rotate · scroll to zoom
RCSB Protein Data Bank · entry 4M6J · 1.201 Å · ligand NADPH DIHYDRO-NICOTINAMIDE-ADENINE-DINUCLEOTIDE PHOSPHATE (NDP). Experimental structure, not a prediction.
What the evidence adds up to
In a 2018 study comparing synovial tissue from 21 rheumatoid arthritis and 20 osteoarthritis patients using three public GEO datasets, researchers identified 15 differentially expressed genes between the two conditions, including CXCL13, CD247, CCL5, GZMB, and IL32. Gene ontology analyses showed these genes were enriched in extracellular space and plasma membrane components, and pathway analysis pointed to chemokine signalling and cytokine-cytokine receptor interaction. The protein-protein interaction network was dominated by co-expression (83.22%) with smaller contributions from shared protein domains, colocalisation, predicted interactions, and genetic interactions. The study did not test any drug or intervention.
A 2019 analysis of gene expression data from multiple published studies compared healthy individuals with patients suffering from early and established rheumatoid arthritis, osteoarthritis, and arthralgia. The authors found that cytoskeleton-related genes, particularly those linked to actin filaments, were differentially expressed in early rheumatoid arthritis compared to healthy subjects, and that eight of these genes reversed their expression ratio between men and women. They also reported that miRNAs and other gene biotypes changed expression substantially in rheumatoid arthritis and arthralgia relative to healthy controls. Simple classification models based on intersecting genes could distinguish healthy from rheumatoid arthritis, and early rheumatoid arthritis from other arthritides, but the work did not involve any therapeutic agent.
A 2024 review summarised recent original research on rheumatoid arthritis pathogenesis, noting that knowledge of the mechanisms has become increasingly precise due to genetics and molecular biology studies. A 1992 review stated that medical management of rheumatoid arthritis had been less than optimal for many patients, with progressive deformity, functional disability, and increased mortality, and discussed alternative schedules of existing drugs and novel pharmacologic therapies then under evaluation, as well as nonpharmacologic treatments reported in the preceding year. Neither review provided new trial data or concrete response rates.
What remains missing is any clinical trial testing a repurposed drug in arthritis patients, a clear patient stratification strategy based on the gene expression signatures described, and funding to move from bioinformatic gene lists and pathogenesis reviews to a prospective, randomised study with survival or symptom endpoints.
Evidence
Retrieved by DeepSearch across 234,678,978 indexed works and resolved on OpenAlex — ranked by citations, including the results that did not work.
Journal of Cellular Biochemistry · 2018 · 61 citations
Identification of differentially expressed genes in synovial tissue of rheumatoid arthritis and osteoarthritis in patients
AbstractRheumatoid arthritis (RA) and osteoarthritis (OA) are the common joints disorder in the world. Although they have showed the analogous clinical manifestation and overlapping cellular and molecular foundation, the pathogenesis of RA and OA were different. The pathophysiologic mechanisms of arthritis in RA and OA have not been investigated thoroughly. Thus, the aim of study is to identify the potential crucial genes and pathways associated with RA and OA and further analyze the molecular mechanisms implicated in genesis. First, we compared gene expression profiles in synovial tissue between RA and OA from the National Center of Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Gene Expression Series (GSE) 1919, GSE55235, and GSE36700 were downloaded from the GEO database, including 20 patients of OA and 21 patients of RA. Differentially expressed genes (DEGs) including "CXCL13," "CD247," "CCL5," "GZMB," "IGKC," "IL7R," "UBD///GABBR1," "ADAMDEC1," "BTC," "AIM2," "SHANK2," "CCL18," "LAMP3," "CR1," and "IL32." Second, Gene Ontology analyses revealed that DEGs were significantly enriched in integral component of extracellular space, extracellular region, and plasma membrane in the molecular function group. Signaling pathway analyses indicated that DEGs had common pathways in chemokine signaling pathway, cytokine-cytokine receptor interaction, and cytosolic DNA-sensing pathway. Third, DEGs showed the complex DEGs protein-protein interaction network with the Coexpression of 83.22%, Shared protein domains of 8.40%, Colocalization of 4.76%, Predicted of 2.87%, and Genetic interactions of 0.75%. In conclusion, the novel DEGs and pathways between RA and OA identified in this study may provide new insight into the underlying molecular mechanisms of RA.
Clinical and Experimental Rheumatology · 2024 · 27 citations · open access
Pathogenesis of rheumatoid arthritis: one year in review 2024
AbstractRheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease characterised by joint destruction and extra-articular manifestations. Different cells and soluble components of the innate as well as adaptive immune system actively contribute to the amplification and perpetuation of the inflammatory processes and structural changes. To date, the knowledge on the mechanisms involved in RA pathogenesis is increasingly precise, mainly due to the recent data obtained from studies on genetics and molecular and cellular biology. In this review article we summarised the new insights into RA pathogenesis from original research articles published in the last year.
Current Opinion in Rheumatology · 1992 · 4 citations
New horizons in the medical treatment of rheumatoid arthritis
AbstractTo date, the medical management of rheumatoid arthritis has been less than optimal for a significant number of patients. This has been manifested by progressive deformity, functional disability, and increased mortality in these patients. Alternative treatment schedules of currently available drugs, as recently advocated by some investigators and the results of both the preclinical and the applied clinical evaluations of a number of novel pharmacologic therapies are reviewed. Several effective nonpharmacologic treatments have been reported in the last year, and their significance in the treatment of rheumatoid arthritis are also discussed.
Zenodo (CERN European Organization for Nuclear Research) · 2019 · 0 citations · open access
Data from: Analysis of gene expression in rheumatoid arthritis and related conditions offers insights into sex-bias, gene biotypes and co-expression patterns
AbstractThe era of next-generation sequencing has mounted the foundation of many gene expression studies. In rheumatoid arthritis research, this has led to the discovery of important candidate genes which offered novel insights into mechanisms and their possible roles in the cure of the disease. In the last years, data generation has outstripped data analysis and while many studies focused on specific aspects of the disease, a global picture of the disease is not yet accomplished. Here, we analyzed and compared a collection of gene expression information from healthy individuals and from patients suffering under different arthritis conditions from published studies containing the following clinical conditions: early and established rheumatoid arthritis, osteoarthritis and arthralgia. We show comprehensive overviews of this data collection and give new insights specifically on gene expression in the early stage, into sex-dependent gene expression, and we describe general differences in expression of different biotypes of genes. Many genes that are related to cytoskeleton changes (actin filament related genes) are differently expressed in early rheumatoid arthritis in comparison to healthy subjects; interestingly, eight of these genes reverse their expression ratio significantly between men and women compared early rheumatoid arthritis and healthy subjects. There are some slighter changes between men and woman between the conditions early and established rheumatoid arthritis. Another aspect are miRNAs and other gene biotypes which are not only promising candidates for diagnoses but also change their expression grossly in average at rheumatoid arthritis and arthralgia compared to the healthy condition. With a selection of intersecting genes, we were able to generate simple classification models to distinguish between healthy and rheumatoid arthritis as well as between early rheumatoid arthritis to other arthritides based on gene expression.
Disease module: DeepOracle (Open Targets). Structures: RDKit from PubChem SMILES. Literature: retrieved by DeepSearch across 234,678,978 indexed works (targeted per-candidate search), resolved on OpenAlex.
DeCure is a research and publication project, not medical advice and not a treatment. "DeCure for X" describes a research goal, not a claim that a cure exists. Backing a cure is a contribution to fund the research — it is not an investment, and confers no yield, royalty, equity or IP ownership. Papers are published open-access by the DeCure.ai DAO.
