Integrated bioinformatics analysis identifies autophagy-associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasis
AbstractAutophagy is implicated in the pathogenesis of psoriasis. We aimed to identify autophagy-related biomarkers in psoriasis via an integrated bioinformatics approach. We downloaded the gene expression profiles of GSE30999 dataset, and the “limma” package was applied to identify differentially e...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Autoimmunity |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/08916934.2023.2259137 |
| _version_ | 1797277188092854272 |
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| author | Sixian Bai Hongyu Cheng Hao Li Peng Bo |
| author_facet | Sixian Bai Hongyu Cheng Hao Li Peng Bo |
| author_sort | Sixian Bai |
| collection | DOAJ |
| description | AbstractAutophagy is implicated in the pathogenesis of psoriasis. We aimed to identify autophagy-related biomarkers in psoriasis via an integrated bioinformatics approach. We downloaded the gene expression profiles of GSE30999 dataset, and the “limma” package was applied to identify differentially expressed genes (DEGs). Then, differentially expressed autophagy-related genes (DEARGs) were identified via integrating autophagy-related genes with DEGs. CytoHubba plugin was used for the identification of hub genes and verified by the GSE41662 dataset. Subsequently, a series of bioinformatics analyses were employed, including protein–protein interaction network, functional enrichment, spearman correlation, receiver operating characteristic, and immune infiltration analyses. One hundred and one DEARGs were identified, and seven DEARGs were identified as hub genes and verified using the GSE41662 dataset. These validated genes had good diagnostic value in distinguishing psoriasis lesions. Immune infiltration analysis indicated that ATG5, SQSTM1, EGFR, MAPK8, MAPK3, MYC, and PIK3C3 were correlated with infiltration of immune cells. Seven DEARGs, namely ATG5, SQSTM1, EGFR, MAPK8, MAPK3, MYC, and PIK3C3, may be involved in the pathogenesis of psoriasis, which expanded the understanding of the development of psoriasis and provided important clinical significance for treatment of this disease. |
| first_indexed | 2024-03-07T15:45:02Z |
| format | Article |
| id | doaj.art-ec0f4757f8b947f98b5af4bc225f122c |
| institution | Directory Open Access Journal |
| issn | 0891-6934 1607-842X |
| language | English |
| last_indexed | 2024-03-07T15:45:02Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Autoimmunity |
| spelling | doaj.art-ec0f4757f8b947f98b5af4bc225f122c2024-03-05T05:02:06ZengTaylor & Francis GroupAutoimmunity0891-69341607-842X2024-12-0157110.1080/08916934.2023.2259137Integrated bioinformatics analysis identifies autophagy-associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasisSixian Bai0Hongyu Cheng1Hao Li2Peng Bo3Chengdu University of Traditional Chinese Medicine, Chengdu, ChinaChengdu University of Traditional Chinese Medicine, Chengdu, ChinaChengdu University of Traditional Chinese Medicine, Chengdu, ChinaChengdu University of Traditional Chinese Medicine, Chengdu, ChinaAbstractAutophagy is implicated in the pathogenesis of psoriasis. We aimed to identify autophagy-related biomarkers in psoriasis via an integrated bioinformatics approach. We downloaded the gene expression profiles of GSE30999 dataset, and the “limma” package was applied to identify differentially expressed genes (DEGs). Then, differentially expressed autophagy-related genes (DEARGs) were identified via integrating autophagy-related genes with DEGs. CytoHubba plugin was used for the identification of hub genes and verified by the GSE41662 dataset. Subsequently, a series of bioinformatics analyses were employed, including protein–protein interaction network, functional enrichment, spearman correlation, receiver operating characteristic, and immune infiltration analyses. One hundred and one DEARGs were identified, and seven DEARGs were identified as hub genes and verified using the GSE41662 dataset. These validated genes had good diagnostic value in distinguishing psoriasis lesions. Immune infiltration analysis indicated that ATG5, SQSTM1, EGFR, MAPK8, MAPK3, MYC, and PIK3C3 were correlated with infiltration of immune cells. Seven DEARGs, namely ATG5, SQSTM1, EGFR, MAPK8, MAPK3, MYC, and PIK3C3, may be involved in the pathogenesis of psoriasis, which expanded the understanding of the development of psoriasis and provided important clinical significance for treatment of this disease.https://www.tandfonline.com/doi/10.1080/08916934.2023.2259137Psoriasisbioinformaticsautophagyhub genesimmune infiltration |
| spellingShingle | Sixian Bai Hongyu Cheng Hao Li Peng Bo Integrated bioinformatics analysis identifies autophagy-associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasis Autoimmunity Psoriasis bioinformatics autophagy hub genes immune infiltration |
| title | Integrated bioinformatics analysis identifies autophagy-associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasis |
| title_full | Integrated bioinformatics analysis identifies autophagy-associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasis |
| title_fullStr | Integrated bioinformatics analysis identifies autophagy-associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasis |
| title_full_unstemmed | Integrated bioinformatics analysis identifies autophagy-associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasis |
| title_short | Integrated bioinformatics analysis identifies autophagy-associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasis |
| title_sort | integrated bioinformatics analysis identifies autophagy associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasis |
| topic | Psoriasis bioinformatics autophagy hub genes immune infiltration |
| url | https://www.tandfonline.com/doi/10.1080/08916934.2023.2259137 |
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