Pathologic α-Synuclein Species Activate LRRK2 in Pro-Inflammatory Monocyte and Macrophage Responses
Bibliographic record
Abstract
Abstract Missense mutations in the LRRK2 gene that lead to LRRK2 kinase hyperactivity can cause Parkinson’s disease (PD). The link between LRRK2 and α-synuclein aggregation in PD remains enigmatic. Numerous reports suggest critical LRRK2 functions in microglial responses. Herein, we find that LRRK2-positive immune cells in the brain represent CD68-positive pro-inflammatory, monocyte-derived macrophages, distinct from microglia. Rod α-synuclein fibrils stimulate LRRK2 kinase activity in monocyte-derived macrophages, and LRRK2 mutations lead to enhanced recruitment of classical monocytes into the midbrain in response to α-synuclein. LRRK2 kinase inhibition blocks α-synuclein fibril induction of LRRK2 protein in both human and murine macrophages, with human cells demonstrating much higher LRRK2 levels and kinase activity than equivalent murine cells. Further, interferon-γ strongly induces LRRK2 kinase activity in primary human macrophages in comparison to weak effects observed in murine cells. These results highlight peripheral immune responses in LRRK2-linked paradigms that further connect two central proteins in PD.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".