Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria
BackgroundChronic spontaneous urticaria (CSU) is an immune-driven skin condition with a multifaceted and not yet fully understood pathogenesis. Although substantial research has been conducted, viable therapeutic targets are still scarce. Studies indicate that disruptions in lipid metabolism signifi...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
|
| Series: | Frontiers in Genetics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2025.1550205/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849330971541766144 |
|---|---|
| author | Zhiming Hu Zhiming Hu Qiong Wang Qiong Wang Yuqi Wang Yuqi Wang Yao Gao Jianhua Hao Jianhua Hao Rui Li Rui Li Hua Zhao Shuping Guo Shuping Guo Hongzhou Cui Hongzhou Cui |
| author_facet | Zhiming Hu Zhiming Hu Qiong Wang Qiong Wang Yuqi Wang Yuqi Wang Yao Gao Jianhua Hao Jianhua Hao Rui Li Rui Li Hua Zhao Shuping Guo Shuping Guo Hongzhou Cui Hongzhou Cui |
| author_sort | Zhiming Hu |
| collection | DOAJ |
| description | BackgroundChronic spontaneous urticaria (CSU) is an immune-driven skin condition with a multifaceted and not yet fully understood pathogenesis. Although substantial research has been conducted, viable therapeutic targets are still scarce. Studies indicate that disruptions in lipid metabolism significantly influence the development of immune-related disorders. Nevertheless, the precise relationship between lipid metabolism and CSU remains underexplored, warranting further investigation.MethodsWe obtained the GSE72540 and GSE57178 datasets from the Gene Expression Omnibus (GEO) repository. For the GSE72540 dataset, we identified differentially expressed genes (DEGs) and performed weighted gene co-expression network analysis (WGCNA) on them. The identified DEGs were cross-referenced with lipid metabolism-related genes (LMRGs). To identify hub genes, we constructed a protein-protein interaction (PPI) network. These hub genes were validated using the GSE57178 dataset to identify potential diagnostic markers. Additionally, gene set enrichment analysis (GSEA) and receiver operating characteristic (ROC) curve analysis were employed to evaluate their diagnostic potential. In the CSU mouse model, we further validated the expression levels of these hub genes. Finally, untargeted metabolomics was conducted to detect lipid metabolism-related metabolites in the serum of CSU patients.ResultUsing bioinformatics analysis, three hub genes were identified: SLC2A4, PTGS2, and PLA2G2A. In skin tissues from CSU-like mouse models, the mRNA levels of PTGS2 and PLA2G2A were significantly upregulated compared to the control group. Additionally, untargeted metabolomics revealed 60 distinct lipid metabolites, with a marked increase in arachidonic acid levels observed in the CSU group.ConclusionPTGS2 and PLA2G2A are key hub genes for CSU, and arachidonic acid can serve as a potential serum biomarker. |
| format | Article |
| id | doaj-art-a3b0d09c5a8e4dc08f3923e8fb197421 |
| institution | Kabale University |
| issn | 1664-8021 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj-art-a3b0d09c5a8e4dc08f3923e8fb1974212025-08-20T03:46:46ZengFrontiers Media S.A.Frontiers in Genetics1664-80212025-08-011610.3389/fgene.2025.15502051550205Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticariaZhiming Hu0Zhiming Hu1Qiong Wang2Qiong Wang3Yuqi Wang4Yuqi Wang5Yao Gao6Jianhua Hao7Jianhua Hao8Rui Li9Rui Li10Hua Zhao11Shuping Guo12Shuping Guo13Hongzhou Cui14Hongzhou Cui15Department of Dermatology, First Hospital of Shanxi Medical University, Taiyuan, ChinaThe First Clinical Medical College of Shanxi Medical University, Taiyuan, ChinaDepartment of Dermatology, First Hospital of Shanxi Medical University, Taiyuan, ChinaThe First Clinical Medical College of Shanxi Medical University, Taiyuan, ChinaDepartment of Dermatology, First Hospital of Shanxi Medical University, Taiyuan, ChinaThe First Clinical Medical College of Shanxi Medical University, Taiyuan, ChinaThe First Clinical Medical College of Shanxi Medical University, Taiyuan, ChinaDepartment of Dermatology, First Hospital of Shanxi Medical University, Taiyuan, ChinaThe First Clinical Medical College of Shanxi Medical University, Taiyuan, ChinaDepartment of Dermatology, First Hospital of Shanxi Medical University, Taiyuan, ChinaThe First Clinical Medical College of Shanxi Medical University, Taiyuan, ChinaDermatology Department, Changzhi Second People’s Hospital, Changzhi, ChinaDepartment of Dermatology, First Hospital of Shanxi Medical University, Taiyuan, ChinaThe First Clinical Medical College of Shanxi Medical University, Taiyuan, ChinaDepartment of Dermatology, First Hospital of Shanxi Medical University, Taiyuan, ChinaThe First Clinical Medical College of Shanxi Medical University, Taiyuan, ChinaBackgroundChronic spontaneous urticaria (CSU) is an immune-driven skin condition with a multifaceted and not yet fully understood pathogenesis. Although substantial research has been conducted, viable therapeutic targets are still scarce. Studies indicate that disruptions in lipid metabolism significantly influence the development of immune-related disorders. Nevertheless, the precise relationship between lipid metabolism and CSU remains underexplored, warranting further investigation.MethodsWe obtained the GSE72540 and GSE57178 datasets from the Gene Expression Omnibus (GEO) repository. For the GSE72540 dataset, we identified differentially expressed genes (DEGs) and performed weighted gene co-expression network analysis (WGCNA) on them. The identified DEGs were cross-referenced with lipid metabolism-related genes (LMRGs). To identify hub genes, we constructed a protein-protein interaction (PPI) network. These hub genes were validated using the GSE57178 dataset to identify potential diagnostic markers. Additionally, gene set enrichment analysis (GSEA) and receiver operating characteristic (ROC) curve analysis were employed to evaluate their diagnostic potential. In the CSU mouse model, we further validated the expression levels of these hub genes. Finally, untargeted metabolomics was conducted to detect lipid metabolism-related metabolites in the serum of CSU patients.ResultUsing bioinformatics analysis, three hub genes were identified: SLC2A4, PTGS2, and PLA2G2A. In skin tissues from CSU-like mouse models, the mRNA levels of PTGS2 and PLA2G2A were significantly upregulated compared to the control group. Additionally, untargeted metabolomics revealed 60 distinct lipid metabolites, with a marked increase in arachidonic acid levels observed in the CSU group.ConclusionPTGS2 and PLA2G2A are key hub genes for CSU, and arachidonic acid can serve as a potential serum biomarker.https://www.frontiersin.org/articles/10.3389/fgene.2025.1550205/fullbioinformatics analysischronic spontaneous urticarialipid metabolismuntargeted metabolomicsarachidonic acidimmunity |
| spellingShingle | Zhiming Hu Zhiming Hu Qiong Wang Qiong Wang Yuqi Wang Yuqi Wang Yao Gao Jianhua Hao Jianhua Hao Rui Li Rui Li Hua Zhao Shuping Guo Shuping Guo Hongzhou Cui Hongzhou Cui Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria Frontiers in Genetics bioinformatics analysis chronic spontaneous urticaria lipid metabolism untargeted metabolomics arachidonic acid immunity |
| title | Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria |
| title_full | Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria |
| title_fullStr | Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria |
| title_full_unstemmed | Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria |
| title_short | Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria |
| title_sort | bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism related genes and their biological markers in chronic spontaneous urticaria |
| topic | bioinformatics analysis chronic spontaneous urticaria lipid metabolism untargeted metabolomics arachidonic acid immunity |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2025.1550205/full |
| work_keys_str_mv | AT zhiminghu bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT zhiminghu bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT qiongwang bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT qiongwang bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT yuqiwang bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT yuqiwang bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT yaogao bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT jianhuahao bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT jianhuahao bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT ruili bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT ruili bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT huazhao bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT shupingguo bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT shupingguo bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT hongzhoucui bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria AT hongzhoucui bioinformaticsanalysiscombinedwithuntargetedmetabolomicsrevealslipidmetabolismrelatedgenesandtheirbiologicalmarkersinchronicspontaneousurticaria |