Critical role of Oas1g and STAT1 pathways in neuroinflammation: insights for Alzheimer’s disease therapeutics
Abstract Background Alzheimer’s disease (AD) has a significant impact on an individual’s health and places a heavy burden on society. Studies have emphasized the importance of microglia in the progression and development of AD. Interferon responses and Interferon-stimulated genes (ISGs) significantl...
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BMC
2025-02-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-025-06112-2 |
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| author | Zhixin Xie Linxi Li Weizhong Hou Zhongxi Fan Lifan Zeng Limin He Yunxiang Ji Jingbai Zhang Fangran Wang Zhou Xing Yezhong Wang Yongyi Ye |
| author_facet | Zhixin Xie Linxi Li Weizhong Hou Zhongxi Fan Lifan Zeng Limin He Yunxiang Ji Jingbai Zhang Fangran Wang Zhou Xing Yezhong Wang Yongyi Ye |
| author_sort | Zhixin Xie |
| collection | DOAJ |
| description | Abstract Background Alzheimer’s disease (AD) has a significant impact on an individual’s health and places a heavy burden on society. Studies have emphasized the importance of microglia in the progression and development of AD. Interferon responses and Interferon-stimulated genes (ISGs) significantly function in neuroinflammatory and neurodegenerative diseases involving AD. Therefore, further exploration of the relationship among microglia, ISGs, and neuroinflammation in AD is warranted. Methods Microglia datasets from the GEO database were retrieved, along with additional microglia RNA-seq data from laboratory mice. Weighted Correlation Network Analysis was used on the training dataset to identify gene co-expression networks. Genes from the black module were intersected with interferon-stimulated genes, and differentially expressed genes (DEGs) were identified. Machine learning algorithms were applied to DEGs, and genes selected by both methods were identified as hub genes, with ROC curves used to evaluate their diagnostic accuracy. Gene Set Enrichment Analysis was performed to reveal functional pathways closely relating to hub genes. Microglia cells were transfected with siRNAs targeting Oas1g and STAT1. Total RNA from microglia cells and mouse brain tissues was extracted, reverse-transcribed, and analyzed via qRT-PCR. Proteins were extracted from cells, quantified, separated by SDS-PAGE, transferred to PVDF membranes, and probed with antibodies. Microglia cells were fixed, permeabilized, blocked, and stained with antibodies for STAT1, then visualized and photographed. Results Bioinformatics and machine learning algorithms revealed that Oas1g was identified as a hub gene, with an AUC of 0.812. Enrichment Analysis revealed that Oas1g is closely associated with interferon-related pathways. Expression of Oas1g was validated in AD mouse models, where it was significantly upregulated after microglial activation. Knockdown experiments suggested siOas1g attenuated the effect of siSTAT1, and the expressions of STAT1 and p-STAT1 were elevated. siOas1g could reverse the effect of siSTAT1, indicating that Oas1g potentially regulates the ISGs through the STAT1 pathway. Conclusion We demonstrated that Oas1g was identified as a hub ISG in AD and can downregulate the activation of IFN-β and STAT1, reducing the expression of ISGs in neuroinflammation. Oas1g might potentially be a beneficial candidate for both prevention and treatment of AD. |
| format | Article |
| id | doaj-art-90cb6522dda240a8a01ce5f921c72ae3 |
| institution | DOAJ |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
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| series | Journal of Translational Medicine |
| spelling | doaj-art-90cb6522dda240a8a01ce5f921c72ae32025-08-20T03:00:58ZengBMCJournal of Translational Medicine1479-58762025-02-0123111510.1186/s12967-025-06112-2Critical role of Oas1g and STAT1 pathways in neuroinflammation: insights for Alzheimer’s disease therapeuticsZhixin Xie0Linxi Li1Weizhong Hou2Zhongxi Fan3Lifan Zeng4Limin He5Yunxiang Ji6Jingbai Zhang7Fangran Wang8Zhou Xing9Yezhong Wang10Yongyi Ye11The Second Clinical Medicine School, Guangzhou Medical UniversityDepartment of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical UniversityThe Second Clinical Medicine School, Guangzhou Medical UniversityThe Third Clinical Medicine School, Guangzhou Medical UniversityThe Third Clinical Medicine School, Guangzhou Medical UniversityThe Sixth Clinical Medicine School, Guangzhou Medical UniversityDepartment of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical UniversityDepartment of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical UniversityDepartment of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical UniversityDepartment of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical UniversityDepartment of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical UniversityDepartment of Neurosurgery, Institute of Neuroscience, the Second Affiliated Hospital of Guangzhou Medical UniversityAbstract Background Alzheimer’s disease (AD) has a significant impact on an individual’s health and places a heavy burden on society. Studies have emphasized the importance of microglia in the progression and development of AD. Interferon responses and Interferon-stimulated genes (ISGs) significantly function in neuroinflammatory and neurodegenerative diseases involving AD. Therefore, further exploration of the relationship among microglia, ISGs, and neuroinflammation in AD is warranted. Methods Microglia datasets from the GEO database were retrieved, along with additional microglia RNA-seq data from laboratory mice. Weighted Correlation Network Analysis was used on the training dataset to identify gene co-expression networks. Genes from the black module were intersected with interferon-stimulated genes, and differentially expressed genes (DEGs) were identified. Machine learning algorithms were applied to DEGs, and genes selected by both methods were identified as hub genes, with ROC curves used to evaluate their diagnostic accuracy. Gene Set Enrichment Analysis was performed to reveal functional pathways closely relating to hub genes. Microglia cells were transfected with siRNAs targeting Oas1g and STAT1. Total RNA from microglia cells and mouse brain tissues was extracted, reverse-transcribed, and analyzed via qRT-PCR. Proteins were extracted from cells, quantified, separated by SDS-PAGE, transferred to PVDF membranes, and probed with antibodies. Microglia cells were fixed, permeabilized, blocked, and stained with antibodies for STAT1, then visualized and photographed. Results Bioinformatics and machine learning algorithms revealed that Oas1g was identified as a hub gene, with an AUC of 0.812. Enrichment Analysis revealed that Oas1g is closely associated with interferon-related pathways. Expression of Oas1g was validated in AD mouse models, where it was significantly upregulated after microglial activation. Knockdown experiments suggested siOas1g attenuated the effect of siSTAT1, and the expressions of STAT1 and p-STAT1 were elevated. siOas1g could reverse the effect of siSTAT1, indicating that Oas1g potentially regulates the ISGs through the STAT1 pathway. Conclusion We demonstrated that Oas1g was identified as a hub ISG in AD and can downregulate the activation of IFN-β and STAT1, reducing the expression of ISGs in neuroinflammation. Oas1g might potentially be a beneficial candidate for both prevention and treatment of AD.https://doi.org/10.1186/s12967-025-06112-2Alzheimer’s diseaseOas1gWGCNAInterferon-stimulated genesNeuroinflammationMachine learning |
| spellingShingle | Zhixin Xie Linxi Li Weizhong Hou Zhongxi Fan Lifan Zeng Limin He Yunxiang Ji Jingbai Zhang Fangran Wang Zhou Xing Yezhong Wang Yongyi Ye Critical role of Oas1g and STAT1 pathways in neuroinflammation: insights for Alzheimer’s disease therapeutics Journal of Translational Medicine Alzheimer’s disease Oas1g WGCNA Interferon-stimulated genes Neuroinflammation Machine learning |
| title | Critical role of Oas1g and STAT1 pathways in neuroinflammation: insights for Alzheimer’s disease therapeutics |
| title_full | Critical role of Oas1g and STAT1 pathways in neuroinflammation: insights for Alzheimer’s disease therapeutics |
| title_fullStr | Critical role of Oas1g and STAT1 pathways in neuroinflammation: insights for Alzheimer’s disease therapeutics |
| title_full_unstemmed | Critical role of Oas1g and STAT1 pathways in neuroinflammation: insights for Alzheimer’s disease therapeutics |
| title_short | Critical role of Oas1g and STAT1 pathways in neuroinflammation: insights for Alzheimer’s disease therapeutics |
| title_sort | critical role of oas1g and stat1 pathways in neuroinflammation insights for alzheimer s disease therapeutics |
| topic | Alzheimer’s disease Oas1g WGCNA Interferon-stimulated genes Neuroinflammation Machine learning |
| url | https://doi.org/10.1186/s12967-025-06112-2 |
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