Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy
Abstract Allergic rhinitis (AR) resulted in impairing human health and quality of life seriously. There is currently no definitive remedy for AR. Recent studies have shown that autophagy may regulate airway inflammation. Our comprehension of autophagy and its molecular mechanism in the field of AR c...
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Nature Portfolio
2024-11-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-78375-6 |
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| author | Tao Zhou Hua Cai Lisha Wu Jianjun Chen Liuqing Zhou Jun Liu |
| author_facet | Tao Zhou Hua Cai Lisha Wu Jianjun Chen Liuqing Zhou Jun Liu |
| author_sort | Tao Zhou |
| collection | DOAJ |
| description | Abstract Allergic rhinitis (AR) resulted in impairing human health and quality of life seriously. There is currently no definitive remedy for AR. Recent studies have shown that autophagy may regulate airway inflammation. Our comprehension of autophagy and its molecular mechanism in the field of AR condition remains incomplete. Our research endeavors to bridge this knowledge deficit by investigating the correlation between AR and autophagy. The AR-related gene expression profile GSE50223 was screened and downloaded. The “limma” package of R software was utilized to identify differentially expressed genes associated with autophagy. GO, KEGG, and Gene set enrichment analyses were conducted. A PPI network of differentially expressed autophagy-related genes were established and further identified through the CytoHubba algorithm. A receiver operating characteristic curve analysis was employed to evaluate the diagnostic effectiveness of the hub genes and to examine the relationship between autophagy-related genes and AR. Finally, qRT-PCR was carried out to confirm the chosen autophagy-related genes using clinical samples. 21 autophagy-related genes in allergic rhinitis were identified. BECN1, PIK3C3, GABARAPL2, ULK2, and UVRAG were considered as significant differentially expressed autophagy-related genes. However, additional molecular biological experiments will be necessary to elucidate the underlying mechanism connecting autophagy and AR. |
| format | Article |
| id | doaj-art-c852d6b306824653abdc93496c08d1b4 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-c852d6b306824653abdc93496c08d1b42025-02-02T12:25:21ZengNature PortfolioScientific Reports2045-23222024-11-0114111010.1038/s41598-024-78375-6Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagyTao Zhou0Hua Cai1Lisha Wu2Jianjun Chen3Liuqing Zhou4Jun Liu5Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Otorhinolaryngology Head and Neck Surgery, Xiangya Hospital of Central South UniversityDepartment of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Otorhinolaryngology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and ScienceAbstract Allergic rhinitis (AR) resulted in impairing human health and quality of life seriously. There is currently no definitive remedy for AR. Recent studies have shown that autophagy may regulate airway inflammation. Our comprehension of autophagy and its molecular mechanism in the field of AR condition remains incomplete. Our research endeavors to bridge this knowledge deficit by investigating the correlation between AR and autophagy. The AR-related gene expression profile GSE50223 was screened and downloaded. The “limma” package of R software was utilized to identify differentially expressed genes associated with autophagy. GO, KEGG, and Gene set enrichment analyses were conducted. A PPI network of differentially expressed autophagy-related genes were established and further identified through the CytoHubba algorithm. A receiver operating characteristic curve analysis was employed to evaluate the diagnostic effectiveness of the hub genes and to examine the relationship between autophagy-related genes and AR. Finally, qRT-PCR was carried out to confirm the chosen autophagy-related genes using clinical samples. 21 autophagy-related genes in allergic rhinitis were identified. BECN1, PIK3C3, GABARAPL2, ULK2, and UVRAG were considered as significant differentially expressed autophagy-related genes. However, additional molecular biological experiments will be necessary to elucidate the underlying mechanism connecting autophagy and AR.https://doi.org/10.1038/s41598-024-78375-6AutophagyAllergic rhinitisBiomarkerDatabaseGene expression |
| spellingShingle | Tao Zhou Hua Cai Lisha Wu Jianjun Chen Liuqing Zhou Jun Liu Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy Scientific Reports Autophagy Allergic rhinitis Biomarker Database Gene expression |
| title | Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy |
| title_full | Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy |
| title_fullStr | Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy |
| title_full_unstemmed | Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy |
| title_short | Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy |
| title_sort | bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy |
| topic | Autophagy Allergic rhinitis Biomarker Database Gene expression |
| url | https://doi.org/10.1038/s41598-024-78375-6 |
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