Meta-analysis of microarray data to identify potential signature genes and MiRNAs associated with the pathogenesis of asthma
Abstract Background Asthma is a chronic inflammatory airway disease characterized by variable degrees of inflammation and airway hyperresponsiveness. The current study used a bioinformatic meta-analysis to identify key target genes and miRNA biomarkers for early diagnostics, thereby suggesting possi...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12967-025-06646-5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849331656437006336 |
|---|---|
| author | Asma Vafadar Shayan Khalili Alashti Saeed Khazayel Sepideh Babadi Melika Eghtesadi Mohammad Younesi Amir Savardashtaki Manica Negahdaripour |
| author_facet | Asma Vafadar Shayan Khalili Alashti Saeed Khazayel Sepideh Babadi Melika Eghtesadi Mohammad Younesi Amir Savardashtaki Manica Negahdaripour |
| author_sort | Asma Vafadar |
| collection | DOAJ |
| description | Abstract Background Asthma is a chronic inflammatory airway disease characterized by variable degrees of inflammation and airway hyperresponsiveness. The current study used a bioinformatic meta-analysis to identify key target genes and miRNA biomarkers for early diagnostics, thereby suggesting possible therapeutic targets that could impact the management and treatment of asthma sufferers. Methods This study used microarray bioinformatic analysis to discover potential asthma biomarkers by analyzing four microarray datasets of asthma patients and normal groups, namely GSE64913, GSE41863, GSE41862, and GSE165934. Additionally, pathway analysis, gene ontology (GO), and a protein-protein interaction (PPI) network were performed to investigate crucial pathways related to possible biological processes. A meta-analysis of the datasets to identify differentially expressed genes (DEGs) and their hub genes, with their targeting microRNAs, was implemented using bioinformatics tools. Results In this regard, the genes CD44, KRT6A, FOSL1, PTGS2, JUN, CXCL8, IL1B, and DUSP1 were identified as the hub genes while considering the results of the present study. GO analysis of the DEGs revealed significant enrichment of genes involved in antigen presentation and recognition by T cells, along with pathways related to inflammation and metabolism. Finally, hsa-let-7a-5p, hsa-miR-27a-3p, hsa-miR-34a-5p, hsa-miR-92a-3p, hsa-miR-18a-5p, hsa-mir-155-5p, hsa-mir-129-2-3p, hsa-miR-101-3p, hsa-miR-191-5p, and hsa-miR-185-5p presented considerable associations with most hub genes. Conclusions These genetic factors may serve as valuable biomarkers for understanding the etiology and progression of asthma. |
| format | Article |
| id | doaj-art-ba5caacc9a1d4ce4b4fb9feaa329c83d |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-ba5caacc9a1d4ce4b4fb9feaa329c83d2025-08-20T03:46:27ZengBMCJournal of Translational Medicine1479-58762025-07-0123112010.1186/s12967-025-06646-5Meta-analysis of microarray data to identify potential signature genes and MiRNAs associated with the pathogenesis of asthmaAsma Vafadar0Shayan Khalili Alashti1Saeed Khazayel2Sepideh Babadi3Melika Eghtesadi4Mohammad Younesi5Amir Savardashtaki6Manica Negahdaripour7Student Research Committee, Shiraz University of Medical SciencesDepartment of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical SciencesDepartment of Research and Technology, Kermanshah University of Medical SciencesStudent Research Committee, Shiraz University of Medical SciencesStudent Research Committee, Shiraz University of Medical SciencesStudent Research Committee, Shiraz University of Medical SciencesDepartment of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical SciencesPharmaceutical Sciences Research Center, Shiraz University of Medical SciencesAbstract Background Asthma is a chronic inflammatory airway disease characterized by variable degrees of inflammation and airway hyperresponsiveness. The current study used a bioinformatic meta-analysis to identify key target genes and miRNA biomarkers for early diagnostics, thereby suggesting possible therapeutic targets that could impact the management and treatment of asthma sufferers. Methods This study used microarray bioinformatic analysis to discover potential asthma biomarkers by analyzing four microarray datasets of asthma patients and normal groups, namely GSE64913, GSE41863, GSE41862, and GSE165934. Additionally, pathway analysis, gene ontology (GO), and a protein-protein interaction (PPI) network were performed to investigate crucial pathways related to possible biological processes. A meta-analysis of the datasets to identify differentially expressed genes (DEGs) and their hub genes, with their targeting microRNAs, was implemented using bioinformatics tools. Results In this regard, the genes CD44, KRT6A, FOSL1, PTGS2, JUN, CXCL8, IL1B, and DUSP1 were identified as the hub genes while considering the results of the present study. GO analysis of the DEGs revealed significant enrichment of genes involved in antigen presentation and recognition by T cells, along with pathways related to inflammation and metabolism. Finally, hsa-let-7a-5p, hsa-miR-27a-3p, hsa-miR-34a-5p, hsa-miR-92a-3p, hsa-miR-18a-5p, hsa-mir-155-5p, hsa-mir-129-2-3p, hsa-miR-101-3p, hsa-miR-191-5p, and hsa-miR-185-5p presented considerable associations with most hub genes. Conclusions These genetic factors may serve as valuable biomarkers for understanding the etiology and progression of asthma.https://doi.org/10.1186/s12967-025-06646-5AsthmaMicroarray meta-analysisGene expressionMiRNABioinformaticsHub genes |
| spellingShingle | Asma Vafadar Shayan Khalili Alashti Saeed Khazayel Sepideh Babadi Melika Eghtesadi Mohammad Younesi Amir Savardashtaki Manica Negahdaripour Meta-analysis of microarray data to identify potential signature genes and MiRNAs associated with the pathogenesis of asthma Journal of Translational Medicine Asthma Microarray meta-analysis Gene expression MiRNA Bioinformatics Hub genes |
| title | Meta-analysis of microarray data to identify potential signature genes and MiRNAs associated with the pathogenesis of asthma |
| title_full | Meta-analysis of microarray data to identify potential signature genes and MiRNAs associated with the pathogenesis of asthma |
| title_fullStr | Meta-analysis of microarray data to identify potential signature genes and MiRNAs associated with the pathogenesis of asthma |
| title_full_unstemmed | Meta-analysis of microarray data to identify potential signature genes and MiRNAs associated with the pathogenesis of asthma |
| title_short | Meta-analysis of microarray data to identify potential signature genes and MiRNAs associated with the pathogenesis of asthma |
| title_sort | meta analysis of microarray data to identify potential signature genes and mirnas associated with the pathogenesis of asthma |
| topic | Asthma Microarray meta-analysis Gene expression MiRNA Bioinformatics Hub genes |
| url | https://doi.org/10.1186/s12967-025-06646-5 |
| work_keys_str_mv | AT asmavafadar metaanalysisofmicroarraydatatoidentifypotentialsignaturegenesandmirnasassociatedwiththepathogenesisofasthma AT shayankhalilialashti metaanalysisofmicroarraydatatoidentifypotentialsignaturegenesandmirnasassociatedwiththepathogenesisofasthma AT saeedkhazayel metaanalysisofmicroarraydatatoidentifypotentialsignaturegenesandmirnasassociatedwiththepathogenesisofasthma AT sepidehbabadi metaanalysisofmicroarraydatatoidentifypotentialsignaturegenesandmirnasassociatedwiththepathogenesisofasthma AT melikaeghtesadi metaanalysisofmicroarraydatatoidentifypotentialsignaturegenesandmirnasassociatedwiththepathogenesisofasthma AT mohammadyounesi metaanalysisofmicroarraydatatoidentifypotentialsignaturegenesandmirnasassociatedwiththepathogenesisofasthma AT amirsavardashtaki metaanalysisofmicroarraydatatoidentifypotentialsignaturegenesandmirnasassociatedwiththepathogenesisofasthma AT manicanegahdaripour metaanalysisofmicroarraydatatoidentifypotentialsignaturegenesandmirnasassociatedwiththepathogenesisofasthma |