LRRK2 exonic variants and risk of multiple system atrophy
Bibliographic record
Abstract
Objective: The aim of this study was to evaluate the association between common exonic variants in the leucine-rich repeat kinase 2 (LRRK2) gene and risk of multiple system atrophy (MSA). Methods: One series from the United States (92 patients with pathologically confirmed MSA, 416 controls) and a second series from the United Kingdom (85 patients with pathologically confirmed MSA, 352 controls) were included in this case-control study.We supplemented these data with those of 53 patients from the United States with clinically probable or possible MSA. Seventeen common LRRK2 exonic variants were genotyped and assessed for association withMSA. Results: In the combined series of 177 patients with pathologically confirmed MSA and 768 controls, there was a significant association between LRRK2 p.M2397T and MSA (odds ratio [OR] = 0.60, p = 0.002). This protective effect was observed more strongly in the US series (OR = 0.46, p = 0.0008) than the UK series (OR = 0.82, p = 0.41). We observed other noteworthy associations with MSA for p.G1624G (OR = 0.63, p = 0.006) and p.N2081D (OR = 0.15, p = 0.010). The p.G1624G-M2397T haplotype was significantly associated with MSA in the US series (p <0.0001) and combined series (p = 0.003) but not the UK series (p = 0.67). Results were consistent when additionally including the US patients with clinical MSA, where the strongest singlevariant association was again observed for p.M2397T (OR = 0.59, p = 0.0005). Conclusions: These findings provide evidence that LRRK2 exonic variants may contribute to susceptibility to MSA. Validation in other series and meta-analytic studies will be important.
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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 | 0.001 |
| 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".