<scp>P</scp>arkin deficiency modulates <scp>NLRP</scp>3 inflammasome activation by attenuating an <scp>A</scp>20‐dependent negative feedback loop
Bibliographic record
Abstract
Abstract Neuroinflammation and mitochondrial dysfunction, key mechanisms in the pathogenesis of Parkinson's disease (PD), are usually explored independently. Loss‐of‐function mutations of PARK2 and PARK6, encoding the E3 ubiquitin protein ligase Parkin and the mitochondrial serine/threonine kinase PINK1, account for a large proportion of cases of autosomal recessive early‐onset PD. PINK1 and Parkin regulate mitochondrial quality control and have been linked to the modulation of innate immunity pathways. We report here an exacerbation of NLRP3 inflammasome activation by specific inducers in microglia and bone marrow‐derived macrophages from Park2−/− and Pink1−/− mice. The caspase 1‐dependent release of IL‐1β and IL‐18 was, therefore, enhanced in Park2−/− and Pink1−/− cells. This defect was confirmed in blood‐derived macrophages from patients with PARK2 mutations and was reversed by MCC950, which specifically inhibits NLRP3 inflammasome complex formation. Enhanced NLRP3 signaling in Parkin‐deficient cells was accompanied by a lack of induction of A20, a well‐known negative regulator of the NF‐κB pathway recently shown to attenuate NLRP3 inflammasome activity. We also found an inverse correlation between A20 abundance and IL‐1β release, in human macrophages challenged with NLRP3 inflammasome inducers. Overall, our observations suggest that the A20/NLRP3‐inflammasome axis participates in the pathogenesis of PARK2‐linked PD, paving the way for the exploration of its potential as a biomarker and treatment target.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".