Bioinformatics analysis of the potential regulatory mechanisms of renal fibrosis and the screening and identification of factors related to human renal fibrosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35812190", "kind": "science-record", "revision": 4, "content_hash": "sha256:eb122b22e1bb3202daa11485edf3a079cededfa5491387ecc644714ee09406f6", "created_at": "2026-11-01T18:14:51Z", "updated_at": "2026-11-01T22:06:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics analysis of the potential regulatory mechanisms of renal fibrosis and the screening and identification of factors related to human renal fibrosis.", "doi": "10.21037/tau-22-366", "pmid": "35812190", "authors": ["Cixiao Wang", "Shaobo Wu", "Jiang Li", "Yuexian Ma", "Youqun Huang", "Na Fang"], "journal": "Translational andrology and urology", "year": 2022, "abstract": "Background: This paper aimed to identify the key genes and potential mechanisms of renal fibrosis, and provide methods of evaluation and new ideas for the early diagnosis and treatment of renal fibrosis.\nMethods: The GSE102515 dataset was searched from the Gene Expression Omnibus (GEO) database was searched, the differential genes were screened out, and the down-regulated and up-regulated genes were identified. Enrichment analysis of differential genes in the development of renal fibrosis was carried out using the DAVID database, differential genes were analyzed using the STRING database, and Cytoscape software was used for visual processing.\nResults: Eighteen up-regulated genes and ten down-regulated genes were screened. Differential genes are mainly involved in the integrin-mediated signaling pathway and mitotic sister chromatid binding, etc. We found that the molecular functions (MFs) of the differential genes are phospholipid binding and regulatory region DNA binding, etc. Moreover, the cellular components (CCs) of the differential genes are mainly related to low-density lipoprotein (LDL) particles and nuclei. Screening revealed that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 were core genes in the interaction network of renal fibrosis risk-related proteins.\nConclusions: In this study, the differential genes in the occurrence of renal fibrosis were screened out via dataset analysis. It was found that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 may be important participants in the development of renal fibrosis, which provides analytical support for the identification of valuable markers of renal fibrosis.", "claims": [{"id": "claim-method", "statement": "We also used the GEO2R online analytical tools to analyze the gene expression differences and filter [filter conditions: P<0.05 and |log2fold change (FC)| >1].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35812190", "locator": "sections[4] \"Screening for differential genes\" paragraph 2", "quote": "We also used the GEO2R online analytical tools to analyze the gene expression differences and filter [filter conditions: P<0.05 and |log2fold change (FC)| >1]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Gene expression data were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/), which is the national biotechnology information of high-throughput gene expression data repository. We selected the GSE102515 dataset, and the platform was GPL13912.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35812190", "locator": "sections[3] \"Chip analysis of genetic data\" paragraph 2", "quote": "Gene expression data were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/), which is the national biotechnology information of high-throughput gene expression data repository. We selected the GSE102515 dataset, and the platform was GPL13912."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Screening revealed that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 were core genes in the interaction network of renal fibrosis risk-related proteins.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35812190", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Eighteen up-regulated genes and ten down-regulated genes were screened."}, {"asset": "source:pmid:35812190", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Screening revealed that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 were core genes in the interaction network of renal fibrosis risk-related proteins."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Screening revealed that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 were core genes in the interaction network of renal fibrosis risk-related proteins.", "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:35812190"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE102515"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE102515"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35812190", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tau-22-366", "sha256": "sha256:2b5f14fe214f881cc7b2c62ebb8aa994c7e8ae5c759afd23a84fb273ec4699b9", "bytes": 25790, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/tau-22-366", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9262747", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE102515", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE102515", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE102515", "version": null, "note": "Gene expression data were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/), which is the national biotechnology information of high-throughput gene expression data repository. 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