Modeling gene-environment interactions in Parkinson’s Disease: Helicobacter pylori induces CD8 T cell associated motor phenotype in PINK1-/- mice 9116
Bibliographic record
Abstract
Abstract Description Parkinson’s disease (PD) is a neurodegenerative disorder with progressive loss of dopaminergic neurons in substantia nigra and motor dysfunction. Genetic risk factors, environmental triggers, and dysregulated immune response have been implicated in PD. Here, we aim to study PD- associated gene - PINK1 and pathogen-Helicobacter (H.) pylori in the PD development and immune autoreactivity. We established H. pylori infection in Pink1 -/- mice and wild-type littermate controls. At two months post-infection mice underwent behavioral tests, and the stomach, the brain and the spleen were harvested. We developed in vitro assays of H.pylori induced priming of autoreactive CD8 T cells and suppression by regulatory T cells (T reg). H.pylori infected Pink1-/- mice developed a PD-like motor-behavioral dysfunction that was abrogated by CD8 cells depletion prior to infection. Motor-behaviural phenotype in infected KO mice strongly correlated with the yield of MitAg+ CD8 cells and CD8 T cell brain infiltration. H.pylori infection in vivo and in vitro altered T reg FoxP3 expression. The absence of PINK1 in dendritic cells exposed to H.pylori triggered robust priming of autoreactive 2C T cells, that can be suppressed by the WT, but poorly by the PINK1-deficient T regs. Using a model that integrates PINK1 gene and a PD-relevant pathogen we recapitulated the major features of the complex PD pathophysiology and were able to demonstrate an immune autoreactivity underlying the phenotype. Funding Sources This study was funded by The Michael J. Fox Foundation for Parkinson’s Research (MJFF) and the Aligning Science Across Parkinson’s (ASAP) initiative. MJFF administers the grant ASAP 000525 on behalf of ASAP and itself. Topic Categories Neuroimmunology (NEUR)
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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 | 0.001 |
| 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".