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pmid:40557155

Integrated analysis of exosome-related genes and their role in psoriasis pathogenesis.

Zhen Wang · Fang Luo

Frontiers in immunology · 2025 doi:10.3389/fimmu.2025.1492012

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:40557155
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science-record
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sha256:bb0ed10d524a8e09eced1fd45191fd68cb191fde6b447c949d8eb9935c2ed2b4
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2026-11-01T20:30:38Z
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2026-11-01T22:56:41Z
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title
Integrated analysis of exosome-related genes and their role in psoriasis pathogenesis.
doi
10.3389/fimmu.2025.1492012
pmid
40557155
authors array · 2 items
[0]
Zhen Wang
[1]
Fang Luo
journal
Frontiers in immunology
year
2025
abstract
Objective: This study aimed to analyze gene expression data from psoriasis and control samples, focusing on identifying exosome and cell senescence genes, integrating datasets, and validating batch effect removal using principal component analysis (PCA). Methods: We analyzed gene expression profiles from Gene Expression Omnibus (GEO) to identify significant differences between healthy and diseased tissues. It evaluated immune cell proportion variations and used weighted gene co-expression network analysis (WGCNA) to find key modules. Protein-protein interaction (PPI) networks were constructed to explore gene interactions, followed by enrichment analysis for biological functions and pathways. To validate findings, feature genes were confirmed using additional GEO datasets and real-time fluorescence quantitative PCR (RT-qPCR). Results: This study integrated GSE30999 and GSE13355 datasets, identifying 274 exosome-related and cell senescence genes. After standardizing and normalizing the data, PCA confirmed effective batch effect removal. Differentially expressed genes (DEGs) were analyzed for immune-related functions, and PPI networks were constructed. The results, visualized with heatmaps, revealed significant differences in the expression of exosome-related DEGs between psoriasis and control samples. These findings provide insights into potential novel targets for psoriasis therapy. Conclusions: Sixteen exosome-related differentially expressed genes (ERDEGs), including CD274 and SERPINB3, are likely to play a significant role in the development of psoriasis.
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The R package limma was used to perform differential analysis of genes between the Psoriasis group and the Control group.
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sections[4] "Differentially expressed genes in psoriasis-related exosomes" paragraph 2
quote
The R package limma was used to perform differential analysis of genes between the Psoriasis group and the Control group.
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sections[25] "Data availability statement" paragraph 2
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .
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Sixteen exosome-related differentially expressed genes, including CD274 and SERPINB3, are likely to play a significant role in the development of psoriasis.
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sections[0] "Abstract" paragraph 4
quote
Sixteen exosome-related differentially expressed genes (ERDEGs), including CD274 and SERPINB3, are likely to play a significant role in the development of psoriasis.
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Sixteen exosome-related differentially expressed genes, including CD274 and SERPINB3, are likely to play a significant role in the development of psoriasis.
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Gene expression data of skin from psoriatic patients and normal controls
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .
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Expression data from skin biopsy samples from patients with moderate-to-severe psoriasis
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The R package limma was used to perform differential analysis of genes between the Psoriasis group and the Control group.
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .
basis
The paper names GSE30999, GSE13355 in Gene Expression Omnibus and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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and real-time fluorescence quantitative PCR (RT-qPCR). Results: This study integrated GSE30999 an
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real-time fluorescence quantitative PCR (RT-qPCR). Results: This study integrated GSE30999 an
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The R package limma was used to perform differential analysis of genes between the Psoriasis group and the Control group.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40557155", "kind": "science-record", "revision": 4, "content_hash": "sha256:bb0ed10d524a8e09eced1fd45191fd68cb191fde6b447c949d8eb9935c2ed2b4", "created_at": "2026-11-01T20:30:38Z", "updated_at": "2026-11-01T22:56:41Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated analysis of exosome-related genes and their role in psoriasis pathogenesis.", "doi": "10.3389/fimmu.2025.1492012", "pmid": "40557155", "authors": ["Zhen Wang", "Fang Luo"], "journal": "Frontiers in immunology", "year": 2025, "abstract": "Objective: This study aimed to analyze gene expression data from psoriasis and control samples, focusing on identifying exosome and cell senescence genes, integrating datasets, and validating batch effect removal using principal component analysis (PCA).\nMethods: We analyzed gene expression profiles from Gene Expression Omnibus (GEO) to identify significant differences between healthy and diseased tissues. It evaluated immune cell proportion variations and used weighted gene co-expression network analysis (WGCNA) to find key modules. Protein-protein interaction (PPI) networks were constructed to explore gene interactions, followed by enrichment analysis for biological functions and pathways. To validate findings, feature genes were confirmed using additional GEO datasets and real-time fluorescence quantitative PCR (RT-qPCR).\nResults: This study integrated GSE30999 and GSE13355 datasets, identifying 274 exosome-related and cell senescence genes. After standardizing and normalizing the data, PCA confirmed effective batch effect removal. Differentially expressed genes (DEGs) were analyzed for immune-related functions, and PPI networks were constructed. The results, visualized with heatmaps, revealed significant differences in the expression of exosome-related DEGs between psoriasis and control samples. These findings provide insights into potential novel targets for psoriasis therapy.\nConclusions: Sixteen exosome-related differentially expressed genes (ERDEGs), including CD274 and SERPINB3, are likely to play a significant role in the development of psoriasis.", "claims": [{"id": "claim-method", "statement": "The R package limma was used to perform differential analysis of genes between the Psoriasis group and the Control group.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40557155", "locator": "sections[4] \"Differentially expressed genes in psoriasis-related exosomes\" paragraph 2", "quote": "The R package limma was used to perform differential analysis of genes between the Psoriasis group and the Control group."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40557155", "locator": "sections[25] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Sixteen exosome-related differentially expressed genes, including CD274 and SERPINB3, are likely to play a significant role in the development of psoriasis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40557155", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Sixteen exosome-related differentially expressed genes (ERDEGs), including CD274 and SERPINB3, are likely to play a significant role in the development of psoriasis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Sixteen exosome-related differentially expressed genes, including CD274 and SERPINB3, are likely to play a significant role in the development of psoriasis.", "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:40557155"], "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:GSE13355"], "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:GSE13355"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40557155", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2025.1492012", "sha256": "sha256:fd291a8cd1e543e2c111d39d24841b8af8740b4b13063b4be1362df796f7f218", "bytes": 44681, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2025.1492012", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12185452", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE13355", "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=GSE13355", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE13355", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. 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