Identification of potential anti aging drugs and targets in chronic kidney disease.

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We analyzed datasets GSE37171 and GSE66494 from the GEO database, identifying 317 differentially expressed genes (DEGs). By intersecting these DEGs with aging related genes, we identified 23 aging associated differential genes (ARDEGs). A protein-protein interaction (PPI) network was constructed using the STRING database, and the top 10 hub ARDEGs were identified using Cytoscape software. Potential anti aging drugs, including Cinnamaldehyde, were identified through the ceRNA and transcription factor regulatory networks, as well as the DGldb database. Among the key regulatory genes identified in CKD patient samples were SOD2, FGF21, FOS, RELA, DDIT4, BMI1, DUSP6, LGALS3, CXCR2, and CEBPB. Cinnamaldehyde and other drugs were found to target aging associated pathways, suggesting their potential to delay CKD progression through modulating these pathways. Finally, we verified the low-expression of DDIT4 and DUSP6, the two targets of Cinnamaldehyde, in unilateral ureteral obstruction (UUO) animal model. Additionally, Cinnamaldehyde was shown to reduce the expression of fibrosis markers such as fibronectin (FN) and α-smooth muscle actin (α-SMA) in HK2 cells under TGF-β1 stimulation. This study provides a foundational understanding of aging related molecular targets in CKD and offers new directions for developing anti aging therapies to treat CKD.", "claims": [{"id": "claim-method", "statement": "The “limma” and “sva” R packages were used to integrate data from GSE37171 and GSE66494.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40319112", "locator": "sections[4] \"2.2 Differential expression genes (DEGs) enrichment analysis\" paragraph 2", "quote": "The “limma” and “sva” R packages were used to integrate data from GSE37171 and GSE66494."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Materials; further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40319112", "locator": "sections[32] \"Data availability\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Materials; further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We analyzed datasets GSE37171 and GSE66494 from the GEO database, identifying 317 differentially expressed genes (DEGs).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40319112", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We analyzed datasets GSE37171 and GSE66494 from the GEO database, identifying 317 differentially expressed genes (DEGs)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We analyzed datasets GSE37171 and GSE66494 from the GEO database, identifying 317 differentially expressed genes (DEGs).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40319112"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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