LRRK2 levels in immune cells are increased in Parkinson’s disease
Bibliographic record
Abstract
Abstract Mutations associated with leucine-rich repeat kinase 2 are the most common known cause of Parkinson’s disease. The known expression of leucine-rich repeat kinase 2 in immune cells and its negative regulatory function of nuclear factor of activated T cells implicates leucine-rich repeat kinase 2 in the development of the inflammatory environment characteristic of Parkinson’s disease. The aim of this study was to determine the expression pattern of leucine-rich repeat kinase 2 in immune cell subsets and correlate it with the immunophenotype of cells from Parkinson’s disease and healthy subjects. For immunophenotyping, blood cells from 40 Parkinson’s disease patients and 32 age and environment matched-healthy control subjects were analyzed by flow cytometry. Multiplexed immunoassays were used to measure cytokine output of stimulated cells. Leucine-rich repeat kinase 2 expression was increased in B cells ( p = 0.0095), T cells ( p = 0.029), and CD16 + monocytes ( p = 0.01) of Parkinson’s disease patients compared to healthy controls. Leucine-rich repeat kinase 2 induction was also increased in monocytes and dividing T cells in Parkinson’s disease patients compared to healthy controls. In addition, Parkinson’s disease patient monocytes secreted more inflammatory cytokines compared to healthy control, and cytokine expression positively correlated with leucine-rich repeat kinase 2 expression in T cells from Parkinson’s disease but not healthy controls. Finally, the regulatory surface protein that limits T-cell activation signals, CTLA-4 (cytotoxic T-lymphocyte-associated protein 4), was decreased in Parkinson’s disease compared to HC in T cells ( p = 0.029). In sum, these findings suggest that leucine-rich repeat kinase 2 has a regulatory role in immune cells and Parkinson’s disease. Functionally, the positive correlations between leucine-rich repeat kinase 2 expression levels in T-cell subsets, cytokine expression and secretion, and T-cell activation states suggest that targeting leucine-rich repeat kinase 2 with therapeutic interventions could have direct effects on immune cell function.
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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 | 0.001 | 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".