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pmid:39376789

Single-Cell Sequencing Combined with Transcriptome Sequencing to Explore the Molecular Mechanisms Related to Psoriasis.

Cailing E · Rongying Wang · Zudong Meng · Yulin Zou

Clinical, cosmetic and investigational dermatology · 2024 doi:10.2147/CCID.S484034

Paper

complete

Experiment

complete

Data

partial

Analysis

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Execution

absent

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title
Single-Cell Sequencing Combined with Transcriptome Sequencing to Explore the Molecular Mechanisms Related to Psoriasis.
doi
10.2147/CCID.S484034
pmid
39376789
authors array · 4 items
[0]
Cailing E
[1]
Rongying Wang
[2]
Zudong Meng
[3]
Yulin Zou
journal
Clinical, cosmetic and investigational dermatology
year
2024
abstract
Background: Psoriasis, a chronic and recurrent inflammatory skin disease, current treatments can only alleviate its symptoms. There is still no complete cure. Although increasing research supports the therapeutics to be better, the common mechanism of its occurrence is still not fully elucidated. Our study is about further explore the molecular mechanism of the occurrence of this disease. Methods: The gene expression profiles of psoriasis (GSE151177, GSE41664, GSE30999) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) of psoriasis using R software, three kinds of analyses were performed, namely WGCNA, GWAS Analysis, Drug Target Prediction. Results: A total of 14 common DEGs was selected for subsequent analyses. Our Drug Target Prediction analysis revealed that the expression profiles influenced by certain drugs, including methotrexate, budesonide, amino purvalanol-a, and selumetinib, exhibited negative correlations with the disease-perturbed expression profiles. Finally, It was found that S100A4, JAML, TRAF3IP3, MIAT, IL7R, and KLRB1 were prominently expressed in the immune pathway related to allograft rejection. In the metabolic pathway, oxidative phosphorylation showed high expression levels, while the reactive oxygen species pathway was notably expressed in the signaling pathways domain. Conclusion: Our study reveals the potential drugs and pathogenesis of psoriasis. These potential pathway and hub genes may provide new ideas for further mechanism research.
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Leveraging the limma package, this investigation quantitatively assessed the differential gene expression within the GSE30999 dataset to pinpoint genes variably expressed in psoriasis.
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sections[25] "Drug Target Prediction Using Cmap" paragraph 2
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Leveraging the limma package, this investigation quantitatively assessed the differential gene expression within the GSE30999 dataset to pinpoint genes variably expressed in psoriasis.
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The datasets generated and analysed during the current study are available in the GEO database repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30999, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41664]. The datasets generated and analysed during the current study are available in the scRNA database repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151177].
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sections[30] "Data Sharing Statement" paragraphs 1-4
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The datasets generated and analysed during the current study are available in the GEO database repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30999, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41664]. The datasets generated and analysed during the current study are available in the scRNA database repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151177].
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Analysis of GEO expression data identified six key psoriasis genes—S100A4, JAML, TRAF3IP3, MIAT, IL7R, and KLRB1—candidate drugs, and associated immune and metabolic pathways.
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sections[0] "Abstract" paragraph 4
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Our study reveals the potential drugs and pathogenesis of psoriasis. These potential pathway and hub genes may provide new ideas for further mechanism research.
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sections[20] "Feature Selection via Lasso Regression and SVM" paragraph 3
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We selected these six genes S100A4, JAML, TRAF3IP3, MIAT, IL7R, and KLRB1 as key genes for subsequent research.
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Analysis of GEO expression data identified six key psoriasis genes—S100A4, JAML, TRAF3IP3, MIAT, IL7R, and KLRB1—candidate drugs, and associated immune and metabolic pathways.
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Single-cell RNA sequencing of emigrating cells from human psoriasis skin and control normal skin
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Comparison of Gene Expression in Psoriatic Skin from Different Sources
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Leveraging the limma package, this investigation quantitatively assessed the differential gene expression within the GSE30999 dataset to pinpoint genes variably expressed in psoriasis.
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Leveraging the limma package, this investigation quantitatively assessed the differential gene expression within the GSE30999 dataset to pinpoint genes variably expressed in psoriasis.
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Although increasing research supports the therapeutics to be better, the common mechanism of its occurrence is still not fully elucidated. Our study is about further explore the molecular mechanism of the occurrence of this disease.\nMethods: The gene expression profiles of psoriasis (GSE151177, GSE41664, GSE30999) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) of psoriasis using R software, three kinds of analyses were performed, namely WGCNA, GWAS Analysis, Drug Target Prediction.\nResults: A total of 14 common DEGs was selected for subsequent analyses. Our Drug Target Prediction analysis revealed that the expression profiles influenced by certain drugs, including methotrexate, budesonide, amino purvalanol-a, and selumetinib, exhibited negative correlations with the disease-perturbed expression profiles. Finally, It was found that S100A4, JAML, TRAF3IP3, MIAT, IL7R, and KLRB1 were prominently expressed in the immune pathway related to allograft rejection. In the metabolic pathway, oxidative phosphorylation showed high expression levels, while the reactive oxygen species pathway was notably expressed in the signaling pathways domain.\nConclusion: Our study reveals the potential drugs and pathogenesis of psoriasis. These potential pathway and hub genes may provide new ideas for further mechanism research.", "claims": [{"id": "claim-method", "statement": "Leveraging the limma package, this investigation quantitatively assessed the differential gene expression within the GSE30999 dataset to pinpoint genes variably expressed in psoriasis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39376789", "locator": "sections[25] \"Drug Target Prediction Using Cmap\" paragraph 2", "quote": "Leveraging the limma package, this investigation quantitatively assessed the differential gene expression within the GSE30999 dataset to pinpoint genes variably expressed in psoriasis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and analysed during the current study are available in the GEO database repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30999, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41664].\nThe datasets generated and analysed during the current study are available in the scRNA database repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151177].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39376789", "locator": "sections[30] \"Data Sharing Statement\" paragraphs 1-4", "quote": "The datasets generated and analysed during the current study are available in the GEO database repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30999, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41664].\nThe datasets generated and analysed during the current study are available in the scRNA database repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151177]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Analysis of GEO expression data identified six key psoriasis genes—S100A4, JAML, TRAF3IP3, MIAT, IL7R, and KLRB1—candidate drugs, and associated immune and metabolic pathways.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39376789", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Our study reveals the potential drugs and pathogenesis of psoriasis. These potential pathway and hub genes may provide new ideas for further mechanism research."}, {"asset": "source:pmid:39376789", "locator": "sections[20] \"Feature Selection via Lasso Regression and SVM\" paragraph 3", "quote": "We selected these six genes S100A4, JAML, TRAF3IP3, MIAT, IL7R, and KLRB1 as key genes for subsequent research."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Analysis of GEO expression data identified six key psoriasis genes—S100A4, JAML, TRAF3IP3, MIAT, IL7R, and KLRB1—candidate drugs, and associated immune and metabolic pathways.", "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:39376789"], "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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