Transcriptome meta-analysis and validation to discovery of hub genes and pathways in focal and segmental glomerulosclerosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39232654", "kind": "science-record", "revision": 3, "content_hash": "sha256:4434d00085ade0aec8930ee407f3c92e142091dbe5bc86327bfff39da33d634b", "created_at": "2026-11-01T20:29:22Z", "updated_at": "2026-11-01T22:12:36Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Transcriptome meta-analysis and validation to discovery of hub genes and pathways in focal and segmental glomerulosclerosis.", "doi": "10.1186/s12882-024-03734-4", "pmid": "39232654", "authors": ["Amir Roointan", "Maryam Ghaeidamini", "Parvin Yavari", "Azar Naimi", "Yousof Gheisari", "Alieh Gholaminejad"], "journal": "BMC nephrology", "year": 2024, "abstract": "BACKGROUND: Focal segmental glomerulosclerosis (FSGS), a histologic pattern of injury in the glomerulus, is one of the leading glomerular causes of end-stage renal disease (ESRD) worldwide. Despite extensive research, the underlying biological alterations causing FSGS remain poorly understood. Studying variations in gene expression profiles offers a promising approach to gaining a comprehensive understanding of FSGS molecular pathogenicity and identifying key elements as potential therapeutic targets. This work is a meta-analysis of gene expression profiles from glomerular samples of FSGS patients. The main aims of this study are to establish a consensus list of differentially expressed genes in FSGS, validate these findings, understand the disease's pathogenicity, and identify novel therapeutic targets.\nMETHODS: After a thorough search in the GEO database and subsequent quality control assessments, seven gene expression datasets were selected for the meta-analysis: GSE47183 (GPL14663), GSE47183 (GPL11670), GSE99340, GSE108109, GSE121233, GSE129973, and GSE104948. The random effect size method was applied to identify differentially expressed genes (meta-DEGs), which were then used to construct a regulatory network (STRING, MiRTarBase, and TRRUST) and perform various pathway enrichment analyses. The expression levels of several meta-DEGs, specifically ADAMTS1, PF4, EGR1, and EGF, known as angiogenesis regulators, were analyzed using quantitative reverse transcription polymerase chain reaction (RT-qPCR).\nRESULTS: The identified 2,898 meta-DEGs, including 665 downregulated and 669 upregulated genes, were subjected to various analyses. A co-regulatory network comprising 2,859 DEGs, 2,688 microRNAs (miRNAs), and 374 transcription factors (TFs) was constructed, and the top molecules in the network were identified based on degree centrality. Part of the pathway enrichment analysis revealed significant disruption in the angiogenesis regulatory pathways in the FSGS kidney. The RT-qPCR results confirmed an imbalance in angiogenesis pathways by demonstrating the differential expression levels of ADAMTS1 and EGR1, two key angiogenesis regulators, in the FSGS condition.\nCONCLUSION: In addition to presenting a consensus list of differentially expressed genes in FSGS, this meta-analysis identified significant distortions in angiogenesis-related pathways and factors in the FSGS kidney. Targeting these factors may offer a viable strategy to impede the progression of FSGS.", "claims": [{"id": "claim-method", "statement": "The meta-analysis was successfully conducted using the random effects model, selected based on the Cochran’s Q-test plot results [21, 28].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39232654", "locator": "sections[10] \"DEG identification and meta-analysis: 2898 DEGs were identified as FSGS meta-DEGs\" paragraph 2", "quote": "The meta-analysis was successfully conducted using the random effects model, selected based on the Cochran’s Q-test plot results [21, 28]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The analyzed datasets by the present study are available in the GEO repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE104948], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE129973], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE47183], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE108109], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE99340],[https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121233].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39232654", "locator": "sections[20] \"notes\" paragraph 1", "quote": "The analyzed datasets by the present study are available in the GEO repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE104948], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE129973], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE47183], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE108109], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE99340],[https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121233]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A random-effects meta-analysis of seven FSGS glomerular microarray datasets identified 2,898 differentially expressed genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39232654", "locator": "sections[10] \"DEG identification and meta-analysis: 2898 DEGs were identified as FSGS meta-DEGs\" paragraph 2", "quote": "The outcome of the meta-analysis yielded a list of 2898 differentially expressed genes (DEGs), referred to as meta-DEGs, comprising 1584 upregulated and 1314 downregulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A random-effects meta-analysis of seven FSGS glomerular microarray datasets identified 2,898 differentially expressed 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:39232654"], "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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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE47183 (GPL14663)", "GSE47183 (GPL11670)", "GSE99340", "GSE108109", "GSE121233", "GSE129973", "GSE104948"], "resolved_accessions": ["GSE99340", "GSE108109", "GSE121233", "GSE129973", "GSE104948"], "statements": ["The analyzed datasets by the present study are available in the GEO repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE104948], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE129973], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE47183], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE108109], [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE99340],[https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121233]."], "basis": "The paper names GSE99340, GSE108109, GSE121233, GSE129973, GSE104948 in NCBI Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["random_effects_pool"], "assets": ["source:pmid:39232654", "data:geo:GSE104948"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE104948"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:30:29Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 11029, "completion_tokens": 2059, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:39232654", "type": "paper", "label": "pmid:39232654"}, {"id": "source:pmid:39232654", "type": "manuscript", "label": "PMID 39232654 full text"}, {"id": "data:geo:GSE104948", "type": "dataset", "label": "GEO GSE104948"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:39232654", "type": "paper", "label": "pmid:39232654"}, {"id": "source:pmid:39232654", "type": "manuscript", "label": "PMID 39232654 full text"}, {"id": "data:geo:GSE104948", "type": "dataset", "label": "GEO GSE104948"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-39232654", "type": "extraction", "used": ["source:pmid:39232654"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE104948", "type": "accession_resolution", "used": ["data:geo:GSE104948"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:39232654", "parent_hash": "sha256:7f35076f7ed1e10fd742ebabf6ee60078b0e2f2a48743aff78e772d12129589f", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE104948 licence not read", "asset:data:geo:GSE104948 not downloaded", "asset:data:geo:GSE108109 licence not read", "asset:data:geo:GSE108109 not downloaded", "asset:data:geo:GSE121233 licence not read", "asset:data:geo:GSE121233 not downloaded", "asset:data:geo:GSE129973 licence not read", "asset:data:geo:GSE129973 not downloaded", "asset:data:geo:GSE99340 licence not read", "asset:data:geo:GSE99340 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["rse transcription polymerase chain reaction (RT-qPCR). RESULTS: The identified 2,898 meta-DEGs, i", "regulatory pathways in the FSGS kidney. The RT-qPCR results confirmed an imbalance in angiogenes", "transcription polymerase chain reaction (RT-qPCR). RESULTS: The identified 2,898 meta-DEGs, i", "gulatory pathways in the FSGS kidney. The RT-qPCR results confirmed an imbalance in angiogenes"], "order_basis": "paper_text_order:1598", "id": "assay:1"}, {"role": "analysis", "definition_id": "meta_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["random_effects_pool"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The meta-analysis was successfully conducted using the random effects model, selected based on the Cochran’s Q-test plot results [21, 28]."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}