Mutations in<i>LRRK2</i>increase phosphorylation of peroxiredoxin 3 exacerbating oxidative stress-induced neuronal death
Bibliographic record
Abstract
Mutations in the leucine rich repeat kinase 2 (LRRK2) gene are responsible for autosomal dominant and sporadic Parkinson disease (PD), possibly exerting their effects via a toxic gain of function. A common p.G2019S mutation (rs34637584:A>G) is responsible for up to 30-40% of PD cases in some ethnic populations. Here, we show that LRRK2 interacts with human peroxiredoxin 3 (PRDX3), a mitochondrial member of the antioxidant family of thioredoxin (Trx) peroxidases. Importantly, mutations in the LRRK2 kinase domain significantly increased phosphorylation of PRDX3 compared to wild-type. The increase in PRDX3 phosphorylation was associated with decreased peroxidase activity and increased death in LRRK2-expressing but not in LRRK2-depleted or vector-transfected neuronal cells. LRRK2 mutants stimulated mitochondrial factors involved in apoptosis and induced production of reactive oxygen species (ROS) and oxidative modification of macromolecules. Furthermore, immunoblot and immunohistochemical analysis of postmortem human PD patients carrying the p.G2019S mutation showed a marked increase in phosphorylated PRDX3 (p-PRDX3) relative to normal brain. We showed that LRRK2 mutations increase the inhibition of an endogenous peroxidase by phosphorylation promoting dysregulation of mitochondrial function and oxidative damage. Our findings provide a mechanistic link between the enhanced kinase activity of PD-linked LRRK2 and neuronal cell death.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".