Parkinson’s disease (PD) is clinically characterized by motor dysfunction, and its pathology primarily involves the progressive loss of dopaminergic neurons. Despite extensive research, the precise etiological mechanisms remain elusive. Recent findings have revealed a significant role of astrocytes in PD onset and progression. However, fully elucidating their function has been challenging because of the heterogeneity of cells and the complexity of the disease progression. Here, we successfully used single-nuclear RNA sequencing to characterize diverse genes expressed by astrocytes and analyzed changes in biological processes in a PD mouse model. Pseudotime analysis (Monocle2) indicated that as PD progressed the status of astrocytes transitioned from immune activation states to neurotoxic subtypes, which correlates with marked upregulation of inflammation-related genes, including Nlrp3 and IL-1β. Furthermore, CellChat analysis demonstrated that BMP signaling exhibited significant specificity in PD, with Bmp6 as the primary ligand and astrocytes as crucial mediators and responders. Thus, we demonstrated that BMP signaling activation in astrocytes exacerbates dopamine neuronal death. Rather, inhibiting BMP signaling in astrocytes significantly improved motor dysfunction and reduced the loss of dopamine neurons in a PD mouse model. Mechanistically, we found that activation of the BMP signaling pathway promoted the release of Nlrp3, IL-1β, and TNF-α, suggesting that increased neuroinflammation aggravated dopaminergic neuronal death. Together, these findings highlight the crucial role of astrocytes in the pathogenesis of PD and reveal a novel cellular mechanism that offers potential therapeutic targets for PD intervention.
Inhibition of astrocyte BMP signaling alleviates neuroinflammation in experimental models of Parkinson’s disease
Yibo Li,Jiaxin Hao,Wenyu Wang,Zhaowen Su,Xiaofeng Tian,Hongfang Wang,Qing Liu,Jiamin Gao,Dandan Geng,Lei Wang
Published 2025 in Cell Death Discovery
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- Publication year
2025
- Venue
Cell Death Discovery
- Publication date
2025-11-10
- Fields of study
Biology, Medicine
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- Source metadata
Semantic Scholar, PubMed
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