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pmid:39213249

Identification of cuproptosis-related genes related to the progression of ankylosing spondylitis by integrated bioinformatics analysis.

Junyi Fan · Qihua Liu · Ting Chen · Yongbin Chen · Junzhe Wu

Medicine · 2024 doi:10.1097/MD.0000000000038313

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:39213249
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science-record
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sha256:47f2d3b13d437d178f92cb87158115963fc00cb17ee94cd00e97f0e40e869771
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T20:29:20Z
updated_at
2026-11-01T22:12:34Z
generator object · 2 fields
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paper object · 10 fields
state
complete
title
Identification of cuproptosis-related genes related to the progression of ankylosing spondylitis by integrated bioinformatics analysis.
doi
10.1097/MD.0000000000038313
pmid
39213249
authors array · 5 items
[0]
Junyi Fan
[1]
Qihua Liu
[2]
Ting Chen
[3]
Yongbin Chen
[4]
Junzhe Wu
journal
Medicine
year
2024
abstract
Ankylosing spondylitis (AS) is an autoimmune disease, and the relationship between copper death and AS is not clear. The aim of this study was to analyze and identify potential cuprosis-related genes associated with the onset of AS by bioinformatics methods. We obtained the AS gene expression profile GSE25101 from the Gene Expression Omnibus (GEO) database, which consists of blood samples from 16 active AS patients and 16 sex-and age-matched controls. After analyzing the data, we utilized the WGCNA method to identify genes that exhibited significant differential expression. In order to assess the prognostic and predictive power of these genes, we constructed receiver operating characteristic (ROC) curves. To further validate our predictions, we employed nomograms, calibration curves, decision curve analysis, and external datasets. Lastly, we conducted an analysis on immune infiltration and explored the correlation between key genes and immune response. Three genes, namely INPP5E, CYB5R1, and HGD, have been identified through analysis to be associated with AS. The diagnosis of patients using these genes has been found to possess a high level of accuracy. The area under the ROC curve is reported to be 0.816 for INPP5E, 0.879 for CYB5R1, and also 0.879 for HGD. Furthermore, the nomogram demonstrates an excellent predictive power, and it has been calibrated using a Calibration curve. Its clinical usefulness and net benefit have been thoroughly analyzed and estimated through the use of a DCA curve. Moreover, INPP5E, CYB5R1, and HGD are found to be associated with various types of immune cells. In conclusion, the systematic analysis of cuprosis-related genes may aid in the identification of mechanisms related to copper-induced cell death in AS and offer valuable biomarkers for the diagnosis and treatment of AS.
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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The area under the ROC curve is reported to be 0.816 for INPP5E, 0.879 for CYB5R1, and also 0.879 for HGD.
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The area under the ROC curve is reported to be 0.816 for INPP5E, 0.879 for CYB5R1, and also 0.879 for HGD.
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The area under the ROC curve is reported to be 0.816 for INPP5E, 0.879 for CYB5R1, and also 0.879 for HGD.
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Gene Expression in Inflammatory Diseases
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6947
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Expression profiling in whole blood in ankylosing spondylitis patients and controls
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2026-11-01T15:39:54Z
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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72
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null
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10558
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Homo sapiens
title
Sexual Dimorphism in the Th17 Signature of Ankylosing Spondylitis
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2026-11-01T15:39:55Z
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[4]
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To assess the prognostic and predictive power of these genes, we constructed receiver operating characteristic (ROC) curves.
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assay:2
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39213249", "kind": "science-record", "revision": 3, "content_hash": "sha256:47f2d3b13d437d178f92cb87158115963fc00cb17ee94cd00e97f0e40e869771", "created_at": "2026-11-01T20:29:20Z", "updated_at": "2026-11-01T22:12:34Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of cuproptosis-related genes related to the progression of ankylosing spondylitis by integrated bioinformatics analysis.", "doi": "10.1097/MD.0000000000038313", "pmid": "39213249", "authors": ["Junyi Fan", "Qihua Liu", "Ting Chen", "Yongbin Chen", "Junzhe Wu"], "journal": "Medicine", "year": 2024, "abstract": "Ankylosing spondylitis (AS) is an autoimmune disease, and the relationship between copper death and AS is not clear. The aim of this study was to analyze and identify potential cuprosis-related genes associated with the onset of AS by bioinformatics methods. We obtained the AS gene expression profile GSE25101 from the Gene Expression Omnibus (GEO) database, which consists of blood samples from 16 active AS patients and 16 sex-and age-matched controls. After analyzing the data, we utilized the WGCNA method to identify genes that exhibited significant differential expression. In order to assess the prognostic and predictive power of these genes, we constructed receiver operating characteristic (ROC) curves. To further validate our predictions, we employed nomograms, calibration curves, decision curve analysis, and external datasets. Lastly, we conducted an analysis on immune infiltration and explored the correlation between key genes and immune response. Three genes, namely INPP5E, CYB5R1, and HGD, have been identified through analysis to be associated with AS. The diagnosis of patients using these genes has been found to possess a high level of accuracy. The area under the ROC curve is reported to be 0.816 for INPP5E, 0.879 for CYB5R1, and also 0.879 for HGD. Furthermore, the nomogram demonstrates an excellent predictive power, and it has been calibrated using a Calibration curve. Its clinical usefulness and net benefit have been thoroughly analyzed and estimated through the use of a DCA curve. Moreover, INPP5E, CYB5R1, and HGD are found to be associated with various types of immune cells. In conclusion, the systematic analysis of cuprosis-related genes may aid in the identification of mechanisms related to copper-induced cell death in AS and offer valuable biomarkers for the diagnosis and treatment of AS.", "claims": [{"id": "claim-data-access", "statement": "The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39213249", "locator": "sections[27] \"fn-group\" paragraph 1", "quote": "The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The area under the ROC curve is reported to be 0.816 for INPP5E, 0.879 for CYB5R1, and also 0.879 for HGD.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39213249", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The area under the ROC curve is reported to be 0.816 for INPP5E, 0.879 for CYB5R1, and also 0.879 for HGD."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The area under the ROC curve is reported to be 0.816 for INPP5E, 0.879 for CYB5R1, and also 0.879 for HGD.", "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:39213249"], "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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