Microglial Activation and Inflammatory Responses in Parkinson's Disease Models Are Attenuated by <scp>TRPM2</scp> Depletion
Bibliographic record
Abstract
Inflammation, and particularly microglial cells, has become a central feature in Parkinson's disease (PD) pathology. The transient receptor potential melastatin 2 (TRPM2) is a calcium-permeable nonselective channel involved in the pathological mechanism of several inflammatory and neurodegenerative diseases. However, the role of TRPM2 in inflammation and microglial activation in the context of PD remains unclear. Here, we combined both in vivo and in vitro PD models to investigate that question. Male and female TRPM2 partial and complete knockout mice were submitted to the 6-hydroxidopamine mouse model of PD. We assessed microglia and lysosome-associated protein (CD68) density levels, microglial morphology and cluster classification, CD68 area in individual microglial cells, and the protein levels of six different cytokines in the substantia nigra pars compacta and the striatum. Our results indicate that TRPM2 deletion reduced microglial density, rescued its morphology, decreased CD68 staining area within microglia, and lowered pro-inflammatory cytokines levels in both male and female mice. To better understand TRPM2 involvement in PD pathology, we selectively knocked-down TRPM2 in neurons, microglia, or both cells in a human neuron-microglia co-culture PD model. An improvement in cell viability and a decrease in cell death were observed across the different experimental approaches. Lastly, TRPM2 deletion revealed reduced microglial phagocytosis and decreased expression of inflammation-related molecules. For the first time, we demonstrated that TRPM2 is a critical mediator of microglial function in the context of PD. Thus, this study suggests that TRPM2 inhibition may offer a novel therapeutic target for PD modification.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 0.000 |
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 teacher head, 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".