Academic Journal
An In‐Silico Study to Identify Relevant Biomarkers in Sepsis Applying Integrated Bulk RNA Sequencing and Single‐Cell RNA Sequencing Analyses.
| Τίτλος: | An In‐Silico Study to Identify Relevant Biomarkers in Sepsis Applying Integrated Bulk RNA Sequencing and Single‐Cell RNA Sequencing Analyses. |
|---|---|
| Συγγραφείς: | Ye, Qile, Dong, Yuhang, Liang, Jingting, Lv, Jingyao, Tang, Rong, Zhao, Shuai, Hou, Guiying |
| Πηγή: | Global Challenges; Apr2025, Vol. 9 Issue 4, p1-10, 10p |
| Θεματικοί όροι: | RNA sequencing, Killer cells, Membrane proteins, Antigen presentation, Antigen processing |
| Περίληψη: | This study aims to discover sepsis‐related biomarkers via in‐silico analyses. The single‐cell sequencing RNA (sc‐RNA) data and metabolism‐related genes are obtained from public databases and previous studies, respectively. Cell subpopulations are identified and annotated, followed by performing single‐sample geneset enrichment analysis (ssGSEA and identification of differentially expressed genes (DEGs). Weighted gene co‐expression network analysis (WGCNA) is applied to classify specific gene modules, and the key module is subjected to immune infiltration analysis. The communication between the subclusters of monocytes is visualized. Five cell subpopulations (subcluster C1‐5) containing a relatively higher percentage of monocytes are identified, with subcluster C4 having the lowest enrichment score of metabolism‐related genes. Genes with a higher expression in the subclusters are enriched for antigen processing and presentation of exogenous antigen, lymphocyte differentiation, and leukocyte activation. Subcluster C5 affected other subclusters through galectin 9 (LGALS9)‐CD45 and LGALS9‐CD44, while other subclusters affected subcluster C5 through MIF‐(CD74+C‐X‐C motif chemokine receptor 4 (CXCR4)) and MIF‐(CD74+CD44). Six genes (F‐Box Protein 4, FBXO4; Forkhead Box K1, FOXK1; MSH2 with MutS Homolog 2, MSH2; Nop‐7‐associated 2, NSA2; Transmembrane Protein 128, TMEM128; and SBDS) are determined as the hub genes for sepsis. The 6 hub genes are positively correlated with, among others, monocytes and NK cells, but negatively correlated with neutrophils. This study identifies accurate biomarkers for sepsis, contributing to the diagnosis and treatment of the disease. [ABSTRACT FROM AUTHOR] |
| Copyright of Global Challenges is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 |
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| Header | DbId: edb DbLabel: Complementary Index An: 184573549 RelevancyScore: 984 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 983.703247070313 |
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| Items | – Name: Title Label: Title Group: Ti Data: An In‐Silico Study to Identify Relevant Biomarkers in Sepsis Applying Integrated Bulk RNA Sequencing and Single‐Cell RNA Sequencing Analyses. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ye%2C+Qile%22">Ye, Qile</searchLink><br /><searchLink fieldCode="AR" term="%22Dong%2C+Yuhang%22">Dong, Yuhang</searchLink><br /><searchLink fieldCode="AR" term="%22Liang%2C+Jingting%22">Liang, Jingting</searchLink><br /><searchLink fieldCode="AR" term="%22Lv%2C+Jingyao%22">Lv, Jingyao</searchLink><br /><searchLink fieldCode="AR" term="%22Tang%2C+Rong%22">Tang, Rong</searchLink><br /><searchLink fieldCode="AR" term="%22Zhao%2C+Shuai%22">Zhao, Shuai</searchLink><br /><searchLink fieldCode="AR" term="%22Hou%2C+Guiying%22">Hou, Guiying</searchLink> – Name: TitleSource Label: Source Group: Src Data: Global Challenges; Apr2025, Vol. 9 Issue 4, p1-10, 10p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22RNA+sequencing%22">RNA sequencing</searchLink><br /><searchLink fieldCode="DE" term="%22Killer+cells%22">Killer cells</searchLink><br /><searchLink fieldCode="DE" term="%22Membrane+proteins%22">Membrane proteins</searchLink><br /><searchLink fieldCode="DE" term="%22Antigen+presentation%22">Antigen presentation</searchLink><br /><searchLink fieldCode="DE" term="%22Antigen+processing%22">Antigen processing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study aims to discover sepsis‐related biomarkers via in‐silico analyses. The single‐cell sequencing RNA (sc‐RNA) data and metabolism‐related genes are obtained from public databases and previous studies, respectively. Cell subpopulations are identified and annotated, followed by performing single‐sample geneset enrichment analysis (ssGSEA and identification of differentially expressed genes (DEGs). Weighted gene co‐expression network analysis (WGCNA) is applied to classify specific gene modules, and the key module is subjected to immune infiltration analysis. The communication between the subclusters of monocytes is visualized. Five cell subpopulations (subcluster C1‐5) containing a relatively higher percentage of monocytes are identified, with subcluster C4 having the lowest enrichment score of metabolism‐related genes. Genes with a higher expression in the subclusters are enriched for antigen processing and presentation of exogenous antigen, lymphocyte differentiation, and leukocyte activation. Subcluster C5 affected other subclusters through galectin 9 (LGALS9)‐CD45 and LGALS9‐CD44, while other subclusters affected subcluster C5 through MIF‐(CD74+C‐X‐C motif chemokine receptor 4 (CXCR4)) and MIF‐(CD74+CD44). Six genes (F‐Box Protein 4, FBXO4; Forkhead Box K1, FOXK1; MSH2 with MutS Homolog 2, MSH2; Nop‐7‐associated 2, NSA2; Transmembrane Protein 128, TMEM128; and SBDS) are determined as the hub genes for sepsis. The 6 hub genes are positively correlated with, among others, monocytes and NK cells, but negatively correlated with neutrophils. This study identifies accurate biomarkers for sepsis, contributing to the diagnosis and treatment of the disease. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Global Challenges is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/gch2.202400321 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 1 Subjects: – SubjectFull: RNA sequencing Type: general – SubjectFull: Killer cells Type: general – SubjectFull: Membrane proteins Type: general – SubjectFull: Antigen presentation Type: general – SubjectFull: Antigen processing Type: general Titles: – TitleFull: An In‐Silico Study to Identify Relevant Biomarkers in Sepsis Applying Integrated Bulk RNA Sequencing and Single‐Cell RNA Sequencing Analyses. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ye, Qile – PersonEntity: Name: NameFull: Dong, Yuhang – PersonEntity: Name: NameFull: Liang, Jingting – PersonEntity: Name: NameFull: Lv, Jingyao – PersonEntity: Name: NameFull: Tang, Rong – PersonEntity: Name: NameFull: Zhao, Shuai – PersonEntity: Name: NameFull: Hou, Guiying IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20566646 Numbering: – Type: volume Value: 9 – Type: issue Value: 4 Titles: – TitleFull: Global Challenges Type: main |
| ResultId | 1 |