Lysosome and Inflammatory Defects in <i>GBA1</i>‐Mutant Astrocytes Are Normalized by LRRK2 Inhibition
Bibliographic record
Abstract
BACKGROUND: Autosomal recessive mutations in the glucocerebrosidase gene, Beta-glucocerebrosidase 1 (GBA1), cause the lysosomal storage disorder Gaucher's disease. Heterozygous carriers of most GBA1 mutations have dramatically increased Parkinson's disease (PD) risk, but the mechanisms and cells affected remain unknown. Glucocerebrosidase expression is relatively enriched in astrocytes, yet the impact of its mutation in these cells has not yet been addressed. OBJECTIVES: Emerging data supporting non-cell-autonomous mechanisms driving PD pathogenesis inspired the first characterization of GBA1-mutant astrocytes. In addition, we asked whether LRRK2, likewise linked to PD and enriched in astrocytes, intersected with GBA1 phenotypes. METHODS: Using heterozygous and homozygous GBA1 D409V knockin mouse astrocytes, we conducted rigorous biochemical and image-based analyses of lysosomal function and morphology. We also examined basal and evoked cytokine response at the transcriptional and secretory levels. RESULTS: The D409V knockin astrocytes manifested broad deficits in lysosomal morphology and function, as expected. This, however, is the first study to show dramatic defects in basal and TLR4-dependent cytokine production. Albeit to different extents, both the lysosomal dysfunction and inflammatory responses were normalized by inhibition of LRRK2 kinase activity, suggesting functional intracellular crosstalk between glucocerebrosidase and LRRK2 activities in astrocytes. CONCLUSIONS: These data demonstrate novel pathologic effects of a GBA1 mutation on inflammatory responses in astrocytes, indicating the likelihood of broader immunologic changes in GBA-PD patients. Our findings support the involvement of non-cell-autonomous mechanisms contributing to the pathogenesis of GBA1-linked PD and identify new opportunities to correct these changes with pharmacological intervention. © 2020 International Parkinson and Movement Disorder Society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".