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pmid:39280684
Research on key pathogenesis and potential intervention targets of idiopathic renal calculi composed of calcium oxalate (CaOx) based on bioinformatics.
Jian Li · Yu Chen
Translational andrology and urology · 2024 doi:10.21037/tau-24-302
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Experiment
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Complete file
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In recent years, with the development of bioinformatics, there has been a deeper understanding of the pathogenesis of this type of disease. This study aimed to analyze the gene expression profiles of idiopathic kidney stones composed of CaOx using bioinformatics methods. By investigating the pathogenesis at the molecular level and identifying potential therapeutic targets, the study also integrated clinical data to validate the clinical relevance of the target genes.\nMethods: Gene expression profiles from the GSE73680 dataset were analyzed via the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between Randall's plaques (RPs) from kidney papillae associated with CaOx stones and normal kidney papillae tissues. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to construct transcription factor (TF)-DEG-microRNA (miRNA) networks, and key genes were screened using the Molecular Complex Detection (MCODE) plugin. A gene set enrichment analysis (GSEA) was performed to investigate the possible underlying mechanisms of the key genes. The clinical data of idiopathic CaOx kidney stone patients who received treatment at the General Hospital of Northern Theater Command from January 2020 to December 2022 were retrospectively analyzed. Enzyme-linked immunosorbent assay (ELISA) kits were used to measure the transcriptional activity of the key genes in calcified kidney papillae tissues. Univariate and multivariate logistic regression analyses were employed to analyze the transcriptional activity of the key genes and their association with idiopathic kidney stones composed of CaOx.\nResults: In the GSE73680 dataset, 276 upregulated and 538 downregulated DEGs were identified. Protein-protein interaction network construction revealed one significant module and three candidate genes [interleukin 11 (IL-11), interleukin 16 (IL-16), and interleukin 32 (IL-32)]. The TF-DEG-miRNA network indicated that IL-11 might be regulated by 25 TFs and interact with six miRNAs. The GSEA suggested that IL-11 could influence the development of idiopathic CaOx stones through chemokine expression and via the signaling pathways of the nucleotide-binding oligomerization domain-like receptors [NOD-like receptors (NLRs)] and toll-like receptors (TLRs). The clinical data analysis revealed that the IL-11 serum levels were significantly elevated in the patients with idiopathic kidney stones composed of CaOx compared to the control subjects (P<0.001). Additionally, IL-11 was identified as an independent risk factor for the development of idiopathic CaOx kidney stones (P<0.001).\nConclusions: The bioinformatically identified key genes and signaling pathways provide a deeper understanding of the potential mechanisms underlying idiopathic CaOx kidney stones. Preliminary clinical trials suggest that elevated serum IL-11 levels in idiopathic CaOx kidney stone patients could serve as a possible diagnostic biomarker and treatment target.", "claims": [{"id": "claim-method", "statement": "Use the empirical Bayesian method in the limma package to statistically test the differences in gene expression levels.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39280684", "locator": "sections[5] \"Identification of DEGs\" paragraph 2", "quote": "Use the empirical Bayesian method in the limma package to statistically test the differences in gene expression levels."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Available at https://tau.amegroups.com/article/view/10.21037/tau-24-302/dss\n10.21037/tau-24-302", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39280684", "locator": "sections[25] \"Data Sharing Statement\" paragraphs 1-3", "quote": "Available at https://tau.amegroups.com/article/view/10.21037/tau-24-302/dss\n10.21037/tau-24-302"}], "state": "complete"}, {"id": "claim-target-result", "statement": "In the GSE73680 dataset, 276 upregulated and 538 downregulated DEGs were identified.", "kind": "quantitative", "target": {"value": 0.05, "unit": "p-value", "tolerance": null, "source": "The limma package was used in R to identify the DEGs that met the following criteria: |log FC| >1 and P<0.05."}, "evidence": [{"asset": "source:pmid:39280684", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "In the GSE73680 dataset, 276 upregulated and 538 downregulated DEGs were identified."}, {"asset": "source:pmid:39280684", "locator": "sections[13] \"Data normalization and identification of DEGs\" paragraph 2", "quote": "The limma package was used in R to identify the DEGs that met the following criteria: |log FC| >1 and P<0.05."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In the GSE73680 dataset, 276 upregulated and 538 downregulated DEGs were identified.", "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:39280684"], "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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