Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis
Background. Aberrant DNA methylation patterns are of increasing interest in the study of psoriasis mechanisms. This study aims to screen potential diagnostic indicators affected by DNA methylation for psoriasis based on bioinformatics using multiple machine learning algorithms and to preliminarily e...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Mediators of Inflammation |
| Online Access: | http://dx.doi.org/10.1155/2022/7731082 |
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| _version_ | 1850214541363773440 |
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| author | Lu Xing Tao Wu Li Yu Nian Zhou Zhao Zhang Yunjing Pu Jinnan Wu Hong Shu |
| author_facet | Lu Xing Tao Wu Li Yu Nian Zhou Zhao Zhang Yunjing Pu Jinnan Wu Hong Shu |
| author_sort | Lu Xing |
| collection | DOAJ |
| description | Background. Aberrant DNA methylation patterns are of increasing interest in the study of psoriasis mechanisms. This study aims to screen potential diagnostic indicators affected by DNA methylation for psoriasis based on bioinformatics using multiple machine learning algorithms and to preliminarily explore its molecular mechanisms. Methods. GSE13355, GSE14905, and GSE73894 were collected from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated region- (DMR-) genes between psoriasis and control samples were combined to obtain differentially expressed methylated genes. Subsequently, a protein-protein interaction (PPI) network was established to analyze the interaction between differentially expressed methylated genes. Moreover, the hub genes of psoriasis were screened by the least absolute shrinkage and selection operator (LASSO), Random Forest (RF), and Support Vector Machine (SVM), which were further performed single-gene gene set enrichment analysis (GSEA) to clarify the pathogenesis of psoriasis. The druggable genes were predicted using DGIdb. Finally, the expressions of hub genes in psoriasis lesions and healthy controls were detected by immunohistochemistry (IHC) and quantitative real-time PCR (RT-qPCR). Results. In this study, a total of 767 DEGs and 896 DMR-genes were obtained. Functional enrichment showed that they were significantly associated with skin development, skin barrier function, immune/inflammatory response, and cell cycle. The combined transcriptomic and DNA methylation data resulted in 33 differentially expressed methylated genes, of which GJB2 was the final identified hub gene for psoriasis, with robust diagnostic power. IHC and RT-qPCR showed that GJB2 was significantly higher in psoriasis samples than those in healthy controls. Additionally, GJB2 may be involved in the development and progression of psoriasis by disrupting the body’s immune system, mediating the cell cycle, and destroying the skin barrier, in addition to possibly inducing diseases related to the skeletal aspects of psoriasis. Moreover, OCTANOL and CARBENOXOLONE were identified as promising compounds through the DGIdb database. Conclusion. The abnormal expression of GJB2 might play a critical role in psoriasis development and progression. The genes identified in our study might serve as a diagnostic indicator and therapeutic target in psoriasis. |
| format | Article |
| id | doaj-art-80bb05f740834fdeb26ecea0072fa452 |
| institution | OA Journals |
| issn | 1466-1861 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Mediators of Inflammation |
| spelling | doaj-art-80bb05f740834fdeb26ecea0072fa4522025-08-20T02:08:50ZengWileyMediators of Inflammation1466-18612022-01-01202210.1155/2022/7731082Exploration of Biomarkers of Psoriasis through Combined Multiomics AnalysisLu Xing0Tao Wu1Li Yu2Nian Zhou3Zhao Zhang4Yunjing Pu5Jinnan Wu6Hong Shu7Department of DermatologyDepartment of Colorectal SurgeryDepartment of DermatologyDepartment of DermatologyDepartment of DermatologyDepartment of DermatologyDepartment of DermatologyDepartment of DermatologyBackground. Aberrant DNA methylation patterns are of increasing interest in the study of psoriasis mechanisms. This study aims to screen potential diagnostic indicators affected by DNA methylation for psoriasis based on bioinformatics using multiple machine learning algorithms and to preliminarily explore its molecular mechanisms. Methods. GSE13355, GSE14905, and GSE73894 were collected from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated region- (DMR-) genes between psoriasis and control samples were combined to obtain differentially expressed methylated genes. Subsequently, a protein-protein interaction (PPI) network was established to analyze the interaction between differentially expressed methylated genes. Moreover, the hub genes of psoriasis were screened by the least absolute shrinkage and selection operator (LASSO), Random Forest (RF), and Support Vector Machine (SVM), which were further performed single-gene gene set enrichment analysis (GSEA) to clarify the pathogenesis of psoriasis. The druggable genes were predicted using DGIdb. Finally, the expressions of hub genes in psoriasis lesions and healthy controls were detected by immunohistochemistry (IHC) and quantitative real-time PCR (RT-qPCR). Results. In this study, a total of 767 DEGs and 896 DMR-genes were obtained. Functional enrichment showed that they were significantly associated with skin development, skin barrier function, immune/inflammatory response, and cell cycle. The combined transcriptomic and DNA methylation data resulted in 33 differentially expressed methylated genes, of which GJB2 was the final identified hub gene for psoriasis, with robust diagnostic power. IHC and RT-qPCR showed that GJB2 was significantly higher in psoriasis samples than those in healthy controls. Additionally, GJB2 may be involved in the development and progression of psoriasis by disrupting the body’s immune system, mediating the cell cycle, and destroying the skin barrier, in addition to possibly inducing diseases related to the skeletal aspects of psoriasis. Moreover, OCTANOL and CARBENOXOLONE were identified as promising compounds through the DGIdb database. Conclusion. The abnormal expression of GJB2 might play a critical role in psoriasis development and progression. The genes identified in our study might serve as a diagnostic indicator and therapeutic target in psoriasis.http://dx.doi.org/10.1155/2022/7731082 |
| spellingShingle | Lu Xing Tao Wu Li Yu Nian Zhou Zhao Zhang Yunjing Pu Jinnan Wu Hong Shu Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis Mediators of Inflammation |
| title | Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis |
| title_full | Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis |
| title_fullStr | Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis |
| title_full_unstemmed | Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis |
| title_short | Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis |
| title_sort | exploration of biomarkers of psoriasis through combined multiomics analysis |
| url | http://dx.doi.org/10.1155/2022/7731082 |
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