DeCure's autonomous Nephrology AI scientist is researching a drug-repurposing hypothesis for focal segmental glomerulosclerosis 5 — screening already-approved drugs against its 1-gene Open Targets disease module to publish open-access research. Research is fast; the path to publication is funded in milestone stages.
Disease moduleFocal segmental glomerulosclerosis 5 maps to a 1-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 focal segmental glomerulosclerosis 5 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
inverted formin 2 (INF2) — INF2 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 adpdrag to rotate · scroll to zoom
RCSB Protein Data Bank · entry 9AZP · 3.79 Å · ligand ADENOSINE-5'-DIPHOSPHATE (ADP). Experimental structure, not a prediction.
What the evidence adds up to
Focal segmental glomerulosclerosis (FSGS) is defined by sclerosis in some glomeruli and podocyte injury. The 2022 minireview notes that recent work has redefined the classification of FSGS based on genetic and immunologic advances, and that clinical trial activity with repurposed agents has been unprecedented, but it does not name any specific drug or report any numerical outcomes. A 2014 paper states that FSGS occurs in both children and adults and is considered the main idiopathic nephrotic syndrome; it emphasises that morphological diagnosis is extremely difficult because sclerotic glomeruli are often too few to quantify, and that biological molecules are being evaluated as diagnostic markers.
A 2021 bioinformatics study analysed three public microarray datasets from kidney tissue of FSGS patients and healthy controls. It identified 85 differentially expressed genes common to all three datasets: 16 were up-regulated and 69 down-regulated. The up-regulated genes were enriched in extracellular matrix organisation, ECM proteoglycans, and integrin-mediated signalling pathways. Four hub genes with the highest degree of interaction were fibronectin-1 (FN1), complement C3, collagen type IV alpha 1 (COL4A1), and integrin β6 (ITGB6). Over-representation analysis showed that FN1, C3, ITGB6, COL4A1, C7, and LUM were enriched in those pathways with an enrichment ratio above 50% (p<0.0001). The study also validated expression of these genes in an independent RNA-seq dataset and examined correlations with GFR and proteinuria, but it did not test any intervention or report survival or response rates.
A 2021 Chinese expert consensus states that FSGS prognosis is very heterogeneous and urges personalised therapy, but it provides no trial results. A 2015 article notes that many genetic advances have been made but that more research is needed to identify additional susceptibility genes and understand the underlying pathophysiology. No abstract reports a completed randomised trial, a response rate, or a survival benefit for any drug in FSGS. What remains missing are adequately powered clinical trials, validated biomarkers to stratify patients by genetic or immunologic subtype, and funding to move from bioinformatic gene lists to therapeutic testing.
Evidence
Retrieved by DeepSearch across 234,678,978 indexed works and resolved on OpenAlex — ranked by citations, including the results that did not work.
Kidney International Reports · 2022 · 31 citations · open access
AbstractFocal segmental glomerulosclerosis (FSGS) is a histologic pattern of injury defined by the presence of sclerosis in some (segmental) of certain glomeruli (focal). On electron microscopy, it is characterized by a variable degree of podocyte foot process effacement and gaps in the coverage of the glomerular basement membrane. The pattern of injury occurs when podocytes, highly differentiated cells with limited regenerative capacity, are reduced in number. The heterogeneity in underlying causes of podocyte loss results in equally variable clinical phenotypes. Recent work acknowledging advances in defining the genetic and immunologic basis of disease has redefined the classification of FSGS. Unprecedented clinical trial activity and efficacy of repurposed agents presents hope for improved therapeutic options. This minireview summarizes recent advances with a focus on novel treatment paradigms in FSGS.
Disease Markers · 2014 · 8 citations · open access
Renal Biopsy: Use of Biomarkers as a Tool for the Diagnosis of Focal Segmental Glomerulosclerosis
AbstractFocal segmental glomerulosclerosis (FSGS) is a glomerulopathy associated with nephrotic syndrome and podocyte injury. FSGS occurs both in children and adults and it is considered the main idiopathic nephrotic syndrome nowadays. It is extremely difficult to establish a morphological diagnosis, since some biopsies lack a considerable quantifiable number of sclerotic glomeruli, given their focal aspect and the fact that FSGS occurs in less than half of the glomeruli. Therefore, many biological molecules have been evaluated as potential markers that would enhance the diagnosis of FSGS. Some of these molecules and receptors are associated with the pathogenesis of FSGS and have potential use in diagnosis.
International Journal of Applied Biology and Pharmaceutical Technology · 2021 · 4 citations · open access
Identification of Crucial Degs and Hub Genes in Focal Segmental Glomerulosclerosis: A Bioinformatics Study
AbstractAims In individuals with focal segmental glomerulosclerosis, identify the important differentially expressed genes (DEGs) relative to healthy control, in kidney tissue samples (glomeruli and tubulointerstitium tissue) and examine their probable role in the molecular mechanism and pathogenesis process of disease. Methods From the Gene Expression Omnibus (GEO) database, raw microarray data generated from kidney tissues from focal segmental glomerulosclerosis patients, and healthy controls patients (GSE121233, GSE125779, GSE129973) were retrieved. Transcription analysis console 4.0 was used to identify DEGs. FUNRICH (Functional enrichment analysis tools) and Enrichr were used to perform functional gene enrichment analysis. Then, Search Tool for Retrieval Interacting Genes (STRING) 10.0 for PPI analysis and cyto scape's for network visualization was used. Further hub genes were identified using the cytohubbaalogorithm plug-in. Then KEGG and REACTOME databases were integrated with Shiny Go and FUNRICH to perform pathway analysis. We used GSEA analysis and associated pathway enrichment by metascape analysis utilizing the molecular complex identification (MCODE) algorithm to discover densely linked network components to further elucidate the likely mechanism of action of related genes in FSGS. The MCODE networks identified for individual gene lists have been gathered. Pathway and process enrichment analysis has been applied to each MCODE component independently, and the three best-scoring terms by p-value have been retained as the functional description of the corresponding components, shown in the tables underneath corresponding network plots further cross validation was done by ORA (over representation analysis) for the commonly (up-regulated) genes including hubgene from all three datasets was done by webgestalt. Finally, we check the raw expression level of all up regulated DEGs, including hub genes, in one main data set (GSE121233) and one validation dataset (GSE129973) to validate the expression of genes identified. We also checked the gene expression level in ERCB (RNA-seq) datasets for various kidney diseases with diabetes including FSGS and other demographic parameters such as GFR and proteinuria, as well as gene expression in gender by using nephroseq. Results 85 DEGs were co-expressed in the three datasets, out of which 16 genes were up-regulated and 69 genes were down regulated in FSGS. DEGs are mostly involved in extracellular matrix organization (biological process), extracellular matrix proteoglycans and integrins cell surface interaction (biological pathways). Protein–protein interaction (PPI) network of 16 upregulated degs in FSGS, identified 43 co expressed genes out of which 20 genes as hub gene where identified by cytohubba, four high ranked hubgenes with greater degree of interaction were (Fibronectin-1, Complement C3 & collagen, type IV, alpha 1, Integrin β6). Metascape analysis results suggests extracellular matrix organization and the genes involved to regulated this biological process are (COL4A1, FN1, ITGB6, LUM, ADAMTS1) shows highest interactions with ECM proteoglycans regulated by genes (COL4A1, FN1, ITGB6, LUM) and integrin mediated signaling pathways regulated by genes (COL4A1, FN1, ITGB6, LUM, ADAMTS1) with enrichment score 134 and 120 with p value p<0.01 and z score 21 and 14. Over representation analysis suggests FN1, C3, ITGB6, COL4A1, C7 and LUMgene is enriched in above stated pathways identified with enrichment ratio more than 50% with p value P<0.0001, GSEA suggests higher expression of genes in these pathways. Three datasets showed the same expression in average as well as raw signals, of upregulated genes including hub gene (LUM,ABCG1, ADAMTS1, C3, MIR4521, PIGR, FN1, COL4A1, MYOF, ITGB6, CLDN1, REN, CDH6, C7, HAVCR1, NR1D1) further each identified genes are checked in nephroseq database at RNA-seq levels for different demographics and other diabetes associated diseases, shown by box plot and bar graph as in our bioinformatics analysis. Conclusion In FSGS, bioinformatics analysis revealed 16 upregulated genes, including 11 crucial genes (HAVCR1, COL4A1, ABCG1, C3, ITGB6, LUM, MYOF, PIGR, C7, FN1, ADAMTS1) and 4 hub-genes (FN1, C3, ITGB6, COL4A1) with high rank and high degree of interaction from three FSGS datasets included in the study, indicating their involvement in FSGS pathways and suggesting they could be potential targets in the disease molecular mechanism.
[Expert consensus on diagnosis and treatment of focal segmental glomerulosclerosis in adults].
AbstractFocal segmental glomerular sclerosis (FSGS) is a clinicopathological syndrome. The prognosis of FSGS patients is very heterogeneous, urging for personalized therapy to improve the long-term prognosis of patients. It provides FSGS clinical diagnosis and treatment workers with a masterable and practical treatment plan to help clinicians further improve their comprehensive diagnosis and treatment capabilities and levels. This collaborative group compiles the Chinese FSGS diagnosis and treatment expert consensus.
AbstractMany advances have been made in understanding the genetics behind focal segmental glomerulosclerosis (FSGS). However, more research is needed to identify additional susceptibility genes and, more importantly, to understand the underlying pathophysiology of FSGS. This article discusses familial FSGS that was presented during the first Michelle Winn Endowed Lecture at Kidney Week 2014.
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.
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