Analysis of DNM3 and VAMP4 as genetic modifiers of LRRK2 Parkinson’s disease
Bibliographic record
Abstract
The LRRK2 gene has rare (p.G2019S) and common risk variants for Parkinson's disease (PD). DNM3 has previously been reported as a genetic modifier of the age at onset in PD patients carrying the LRRK2 p.G2019S mutation. We analyzed this effect in a new cohort of LRRK2 p.G2019S heterozygotes (n = 724) and meta-analyzed our data with previously published data (n = 754). VAMP4 is in close proximity to DNM3, and was associated with PD in a recent study, so it is possible that variants in this gene may be important. We also analyzed the effect of VAMP4 rs11578699 on LRRK2 penetrance. Our analysis of DNM3 in previously unpublished data does not show an effect on age at onset in LRRK2 p.G2019S carriers; however, the inter-study heterogeneity may indicate ethnic or population-specific effects of DNM3. There was no evidence for linkage disequilibrium between DNM3 and VAMP4. Analysis of sporadic patients stratified by the risk variant LRRK2 rs10878226 indicates a possible interaction between common variation in LRRK2 and VAMP4 in disease risk.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".