Synaptic function is modulated by LRRK2 and glutamate release is increased in cortical neurons of G2019S LRRK2 knock-in mice
Bibliographic record
Abstract
Mutations in Leucine-Rich Repeat Kinase-2 (LRRK2) result in familial Parkinson's disease and the G2019S mutation alone accounts for up to 30% in some ethnicities. Despite this, the function of LRRK2 is largely undetermined although evidence suggests roles in phosphorylation, protein interactions, autophagy and endocytosis. Emerging reports link loss of LRRK2 to altered synaptic transmission, but the effects of the G2019S mutation upon synaptic release in mammalian neurons are unknown. To assess wild type and mutant LRRK2 in established neuronal networks, we conducted immunocytochemical, electrophysiological and biochemical characterization of >3 week old cortical cultures of LRRK2 knock-out, wild-type overexpressing and G2019S knock-in mice. Synaptic release and synapse numbers were grossly normal in LRRK2 knock-out cells, but discretely reduced glutamatergic activity and reduced synaptic protein levels were observed. Conversely, synapse density was modestly but significantly increased in wild-type LRRK2 overexpressing cultures although event frequency was not. In knock-in cultures, glutamate release was markedly elevated, in the absence of any change to synapse density, indicating that physiological levels of G2019S LRRK2 elevate probability of release. Several pre-synaptic regulatory proteins shown by others to interact with LRRK2 were expressed at normal levels in knock-in cultures; however, synapsin 1 phosphorylation was significantly reduced. Thus, perturbations to the pre-synaptic release machinery and elevated synaptic transmission are early neuronal effects of LRRK2 G2019S. Furthermore, the comparison of knock-in and overexpressing cultures suggests that one copy of the G2019S mutation has a more pronounced effect than an ~3-fold increase in LRRK2 protein. Mutant-induced increases in transmission may convey additional stressors to neuronal physiology that may eventually contribute to the pathogenesis of Parkinson's disease.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".