Exploring the molecular mechanisms of asthma across multiple datasets
AbstractBackground Asthma, a prevalent chronic respiratory disorder, remains enigmatic, notwithstanding considerable advancements in our comprehension. Continuous efforts are crucial for discovering novel molecular targets and gaining a comprehensive understanding of its pathogenesis.Materials and m...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Annals of Medicine |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/07853890.2023.2258926 |
| _version_ | 1797260597508702208 |
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| author | Lianshan Guo Enhao Huang Tongting Wang Yun Ling Zhengzhao Li |
| author_facet | Lianshan Guo Enhao Huang Tongting Wang Yun Ling Zhengzhao Li |
| author_sort | Lianshan Guo |
| collection | DOAJ |
| description | AbstractBackground Asthma, a prevalent chronic respiratory disorder, remains enigmatic, notwithstanding considerable advancements in our comprehension. Continuous efforts are crucial for discovering novel molecular targets and gaining a comprehensive understanding of its pathogenesis.Materials and methods In this study, we analyzed gene expression data from 212 individuals, including asthma patients and healthy controls, to identify 267 differentially expressed genes, among which C1orf64 and C7orf26 emerged as potential key genes in asthma pathogenesis. Various bioinformatics tools, including differential gene expression analysis, pathway enrichment, drug target prediction, and single-cell analysis, were employed to explore the potential roles of the genes.Results Quantitative PCR demonstrated differential expression of C1orf64 and C7orf26 in the asthmatic airway epithelial tissue, implying their potential involvement in asthma pathogenesis. GSEA enrichment analysis revealed significant enrichment of these genes in signaling pathways associated with asthma progression, such as ABC transporters, cell cycle, CAMs, DNA replication, and the Notch signaling pathway. Drug target prediction, based on upregulated and downregulated differential expression, highlighted potential asthma treatments, including Tyrphostin-AG-126, Cephalin, Verrucarin-a, and Emetine. The selection of these drugs was based on their significance in the analysis and their established anti-inflammatory and antiviral invasion properties. Utilizing Seurat and Celldex packages for single-cell sequencing analysis unveiled disease-specific gene expression patterns and cell types. Expression of C1orf64 and C7orf26 in T cells, NK cells, and B cells, instrumental in promoting hallmark features of asthma, was observed, suggesting their potential influence on asthma development and progression.Conclusion This study uncovers novel genetic aspects of asthma, highlighting potential therapeutic pathways. It exemplifies the power of integrative bioinformatics in decoding complex disease patterns. However, these findings require further validation, and the precise roles of C1orf64 and C7orf26 in asthma warrant additional investigation to validate their therapeutic potential. |
| first_indexed | 2024-04-24T23:27:51Z |
| format | Article |
| id | doaj.art-1d8ddcc268ac407ab3e8498c8ff1c4ce |
| institution | Directory Open Access Journal |
| issn | 0785-3890 1365-2060 |
| language | English |
| last_indexed | 2024-04-24T23:27:51Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Annals of Medicine |
| spelling | doaj.art-1d8ddcc268ac407ab3e8498c8ff1c4ce2024-03-15T18:19:27ZengTaylor & Francis GroupAnnals of Medicine0785-38901365-20602024-12-0156110.1080/07853890.2023.2258926Exploring the molecular mechanisms of asthma across multiple datasetsLianshan Guo0Enhao Huang1Tongting Wang2Yun Ling3Zhengzhao Li4Department of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, ChinaDepartment of Anesthesiology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, ChinaDepartment of Nursing, The Second Affiliated Hospital of Guangxi Medical University, Nanning, ChinaDepartment of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, ChinaDepartment of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, ChinaAbstractBackground Asthma, a prevalent chronic respiratory disorder, remains enigmatic, notwithstanding considerable advancements in our comprehension. Continuous efforts are crucial for discovering novel molecular targets and gaining a comprehensive understanding of its pathogenesis.Materials and methods In this study, we analyzed gene expression data from 212 individuals, including asthma patients and healthy controls, to identify 267 differentially expressed genes, among which C1orf64 and C7orf26 emerged as potential key genes in asthma pathogenesis. Various bioinformatics tools, including differential gene expression analysis, pathway enrichment, drug target prediction, and single-cell analysis, were employed to explore the potential roles of the genes.Results Quantitative PCR demonstrated differential expression of C1orf64 and C7orf26 in the asthmatic airway epithelial tissue, implying their potential involvement in asthma pathogenesis. GSEA enrichment analysis revealed significant enrichment of these genes in signaling pathways associated with asthma progression, such as ABC transporters, cell cycle, CAMs, DNA replication, and the Notch signaling pathway. Drug target prediction, based on upregulated and downregulated differential expression, highlighted potential asthma treatments, including Tyrphostin-AG-126, Cephalin, Verrucarin-a, and Emetine. The selection of these drugs was based on their significance in the analysis and their established anti-inflammatory and antiviral invasion properties. Utilizing Seurat and Celldex packages for single-cell sequencing analysis unveiled disease-specific gene expression patterns and cell types. Expression of C1orf64 and C7orf26 in T cells, NK cells, and B cells, instrumental in promoting hallmark features of asthma, was observed, suggesting their potential influence on asthma development and progression.Conclusion This study uncovers novel genetic aspects of asthma, highlighting potential therapeutic pathways. It exemplifies the power of integrative bioinformatics in decoding complex disease patterns. However, these findings require further validation, and the precise roles of C1orf64 and C7orf26 in asthma warrant additional investigation to validate their therapeutic potential.https://www.tandfonline.com/doi/10.1080/07853890.2023.2258926Asthmabioinformaticsdifferentially expressed genesC1orf64C7orf26 |
| spellingShingle | Lianshan Guo Enhao Huang Tongting Wang Yun Ling Zhengzhao Li Exploring the molecular mechanisms of asthma across multiple datasets Annals of Medicine Asthma bioinformatics differentially expressed genes C1orf64 C7orf26 |
| title | Exploring the molecular mechanisms of asthma across multiple datasets |
| title_full | Exploring the molecular mechanisms of asthma across multiple datasets |
| title_fullStr | Exploring the molecular mechanisms of asthma across multiple datasets |
| title_full_unstemmed | Exploring the molecular mechanisms of asthma across multiple datasets |
| title_short | Exploring the molecular mechanisms of asthma across multiple datasets |
| title_sort | exploring the molecular mechanisms of asthma across multiple datasets |
| topic | Asthma bioinformatics differentially expressed genes C1orf64 C7orf26 |
| url | https://www.tandfonline.com/doi/10.1080/07853890.2023.2258926 |
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