Identification of necroptosis-related genes in Parkinson's disease by integrated bioinformatics analysis and experimental validation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37284660", "kind": "science-record", "revision": 4, "content_hash": "sha256:9337ac4c153ac3e435326ce75d3420a1edd66200d940793f439800b3fc93e7ee", "created_at": "2026-11-01T19:02:00Z", "updated_at": "2026-11-01T22:52:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of necroptosis-related genes in Parkinson's disease by integrated bioinformatics analysis and experimental validation.", "doi": "10.3389/fnins.2023.1097293", "pmid": "37284660", "authors": ["Cheng Lei", "Zhou Zhongyan", "Shi Wenting", "Zhang Jing", "Qin Liyun", "Hu Hongyi", "Yan Juntao", "Ye Qing"], "journal": "Frontiers in neuroscience", "year": 2023, "abstract": "Background: Parkinson's disease (PD) is the second most common neurodegeneration disease worldwide. Necroptosis, which is a new form of programmed cell death with high relationship with inflammation, plays a vital role in the progression of PD. However, the key necroptosis related genes in PD are not fully elucidated.\nPurpose: Identification of key necroptosis-related genes in PD.\nMethod: The PD associated datasets and necroptosis related genes were downloaded from the GEO Database and GeneCards platform, respectively. The DEGs associated with necroptosis in PD were obtained by gap analysis, and followed by cluster analysis, enrichment analysis and WGCNA analysis. Moreover, the key necroptosis related genes were generated by PPI network analysis and their relationship by spearman correlation analysis. Immune infiltration analysis was used for explore the immune state of PD brain accompanied with the expression levels of these genes in various types of immune cells. Finally, the gene expression levels of these key necroptosis related genes were validated by an external dataset, blood samples from PD patients and toxin-induced PD cell model using real-time PCR analysis.\nResult: Twelve key necroptosis-related genes including ASGR2, CCNA1, FGF10, FGF19, HJURP, NTF3, OIP5, RRM2, SLC22A1, SLC28A3, WNT1 and WNT10B were identified by integrated bioinformatics analysis of PD related dataset GSE7621. According to the correlation analysis of these genes, RRM2 and WNT1 were positively and negatively correlated with SLC22A1 respectively, while WNT10B was positively correlated with both OIF5 and FGF19. As the results from immune infiltration analysis, M2 macrophage was the highest population of immune cell in analyzed PD brain samples. Moreover, we found that 3 genes (CCNA1, OIP5 and WNT10B) and 9 genes (ASGR2, FGF10, FGF19, HJURP, NTF3, RRM2, SLC22A1, SLC28A3 and WNT1) were down- and up- regulated in an external dataset GSE20141, respectively. All the mRNA expression levels of these 12 genes were obviously upregulated in 6-OHDA-induced SH-SY5Y cell PD model while CCNA1 and OIP5 were up- and down- regulated, respectively, in peripheral blood lymphocytes of PD patients.\nConclusion: Necroptosis and its associated inflammation play fundamental roles in the progression of PD and these identified 12 key genes might be served as new diagnostic markers and therapeutic targets for PD.", "claims": [{"id": "claim-method", "statement": "Gap analysis of genes in different groups was performed using the limma R package (Ritchie et al., 2015).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37284660", "locator": "sections[4] \"Gap analysis\" paragraph 2", "quote": "Gap analysis of genes in different groups was performed using the limma R package (Ritchie et al., 2015)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37284660", "locator": "sections[21] \"Data availability statement\" paragraph 2", "quote": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Integrated bioinformatics analysis of the PD-related dataset GSE7621 identified 12 key necroptosis-related genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37284660", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Twelve key necroptosis-related genes including ASGR2, CCNA1, FGF10, FGF19, HJURP, NTF3, OIP5, RRM2, SLC22A1, SLC28A3, WNT1 and WNT10B were identified by integrated bioinformatics analysis of PD related dataset GSE7621."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Integrated bioinformatics analysis of the PD-related dataset GSE7621 identified 12 key necroptosis-related 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:37284660"], "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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Result: Twelve key necroptosis-rel"], "order_basis": "paper_text_order:1252", "id": "assay:2"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["were obviously upregulated in 6-OHDA-induced SH-SY5Y cell PD model while CCNA1 and OIP5 were up-", "significantly upregulated in 6-OHDA treated SH-SY5Y cells (Figure 8B). However, CCNA1 was upregu", "in toxin 6-OHDA-induced injury of neuroblast SH-SY5Y cell model. 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