Identification of differentially expressed genes and pathways in kidney of ANCA-associated vasculitis by integrated bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35172670", "kind": "science-record", "revision": 5, "content_hash": "sha256:5b59631f37fd8a462fde7056a48c9b5adbd29204837857cfee0f4a59d9c34349", "created_at": "2026-11-01T17:36:55Z", "updated_at": "2026-11-01T22:05:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of differentially expressed genes and pathways in kidney of ANCA-associated vasculitis by integrated bioinformatics analysis.", "doi": "10.1080/0886022X.2022.2030755", "pmid": "35172670", "authors": ["Xu Deng", "Junying Gao", "Fei Zhao"], "journal": "Renal failure", "year": 2022, "abstract": "The antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a systematic of relatively rare autoimmune diseases with unknown cause. Kidney involvement is one of the most common clinical manifestations, and the degree of renal damage is closely associated with the development and prognosis of AAV. In this study, we utilized the Robust Rank Aggreg (RRA) method in R to integrate GSE104948, GSE104954, GSE108109, GSE108112, and GSE108113 profile datasets loaded from Gene Expression Omnibus (GEO) database and identified a set of differentially expressed genes (DEGs) in kidney between AAV patients and living donors. Then, the results of gene ontology (GO) functional annotation showed that immunity and metabolism involved process of AAV both in glomerulus and tubulointerstitial. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that following pathways, such as complement and coagulation cascades pathway; Staphylococcus aureus infection; disease-COVID-19; and systemic lupus erythematosus (SLE) pathway play a crucial role in AAV. Next, the results analyzed by protein-protein interaction (PPI) network and Cytoscape software exhibited the hub genes ALB, TYROBP, and CYBB existed in both glomerular and tubulointerstitial compartments datasets. Finally, KEGG analysis using genes of two most important modules also further validated complement and coagulation cascades pathway and S. aureus infection existed both in glomerulus and tubulointerstitial compartments datasets. In conclusion, this study identified key genes and pathways involved in kidney of AAV, which was benefit to further uncover the mechanisms underlying the development and progress of AAV, biomarkers, and potential therapeutic targets as well.", "claims": [{"id": "claim-method", "statement": "The captured DEGs were further integrated applying the RRA R package according to glomerular compartments DEGs, tubulointerstitial compartments DEGs, glomerular and tubulointerstitial compartments DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35172670", "locator": "sections[5] \"Integration of expression datasets\" paragraph 2", "quote": "The captured DEGs were further integrated applying the RRA R package according to glomerular compartments DEGs, tubulointerstitial compartments DEGs, glomerular and tubulointerstitial compartments DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "By searching in GEO database (http://www.ncbi.nlm.nih.gov/geo/), GSE104948, GSE104954, GSE108109, GSE108112 and GSE108113 profile datasets which met our requirements were downloaded. The samples of GSE104948 and GSE108109 came from glomerular compartments, samples of GSE104954 and GSE108112 from tubulointerstitial compartments. GSE108113 dataset was composed by GSE108109 and GSE108112.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35172670", "locator": "sections[3] \"Microarray data and kidney tissue processing\" paragraph 2", "quote": "By searching in GEO database (http://www.ncbi.nlm.nih.gov/geo/), GSE104948, GSE104954, GSE108109, GSE108112 and GSE108113 profile datasets which met our requirements were downloaded."}, {"asset": "source:pmid:35172670", "locator": "sections[3] \"Microarray data and kidney tissue processing\" paragraph 2", "quote": "The samples of GSE104948 and GSE108109 came from glomerular compartments, samples of GSE104954 and GSE108112 from tubulointerstitial compartments."}, {"asset": "source:pmid:35172670", "locator": "sections[3] \"Microarray data and kidney tissue processing\" paragraph 2", "quote": "GSE108113 dataset was composed by GSE108109 and GSE108112."}], "state": "complete"}, {"id": "claim-target-result", "statement": "RRA identified 143 integrated DEGs from the glomerular compartment datasets GSE104948 and GSE108109, consisting of 73 upregulated and 70 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35172670", "locator": "sections[10] \"Identification of integrated DEGs in ANCA-associated vasculitis by RRA\" paragraph 2", "quote": "About 143 integrated DEGs from glomerular compartments datasets (GSE104948 and GSE108109), consisting of 73 upregulated genes and 70 downregulated genes, were identified by the RRA method."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "RRA identified 143 integrated DEGs from the glomerular compartment datasets GSE104948 and GSE108109, consisting of 73 upregulated and 70 downregulated genes.", "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:35172670"], "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:GSE104948"], "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:GSE104948"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35172670", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1080/0886022X.2022.2030755", "sha256": "sha256:3d259dd174468d3888b7a811dac3a27106555828ac18b98c88f32411e5ed7786", "bytes": 29550, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1080/0886022X.2022.2030755", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8856091", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE104948", "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=GSE104948", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE104948", "version": null, "note": "By searching in GEO database (http://www.ncbi.nlm.nih.gov/geo/), GSE104948, GSE104954, GSE108109, GSE108112 and GSE108113 profile datasets which met our requirements were downloaded. The samples of GSE104948 and GSE108109 came from glomerular compartments, samples of GSE104954 and GSE108112 from tubulointerstitial compartments. GSE108113 dataset was composed by GSE108109 and GSE108112.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "By searching in GEO database (http://www.ncbi.nlm.nih.gov/geo/), GSE104948, GSE104954, GSE108109, GSE108112 and GSE108113 profile datasets which met our requirements were downloaded. The samples of GSE104948 and GSE108109 came from glomerular compartments, samples of GSE104954 and GSE108112 from tubulointerstitial compartments. 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The samples of GSE104948 and GSE108109 came from glomerular compartments, samples of GSE104954 and GSE108112 from tubulointerstitial compartments. GSE108113 dataset was composed by GSE108109 and GSE108112.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "By searching in GEO database (http://www.ncbi.nlm.nih.gov/geo/), GSE104948, GSE104954, GSE108109, GSE108112 and GSE108113 profile datasets which met our requirements were downloaded. The samples of GSE104948 and GSE108109 came from glomerular compartments, samples of GSE104954 and GSE108112 from tubulointerstitial compartments. 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The samples of GSE104948 and GSE108109 came from glomerular compartments, samples of GSE104954 and GSE108112 from tubulointerstitial compartments. GSE108113 dataset was composed by GSE108109 and GSE108112.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "By searching in GEO database (http://www.ncbi.nlm.nih.gov/geo/), GSE104948, GSE104954, GSE108109, GSE108112 and GSE108113 profile datasets which met our requirements were downloaded. The samples of GSE104948 and GSE108109 came from glomerular compartments, samples of GSE104954 and GSE108112 from tubulointerstitial compartments. 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