The G2019S LRRK2 Mutation is Rare in Korean Patients with Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: A number of causative mutations such as alpha-synuclein, parkin, UCHL1, Pink-1, DJ-1 have been identified in Parkinson's disease (PD). They are usually found in the familial cases. One mutation of great interest is the G2019S mutation in the LRRK2 gene, which has been reported in both familial and sporadic PD. Its prevalence has been reported to vary markedly among different races. We examined the prevalence of the G2019S mutation in the Korean PD population for genetic study planning. METHODS: We conducted a genetic analysis of the G2019S mutation by standard PCR and restriction digestion method. 453 PD patients were studied, 34% of whom had an age at onset of < 50 years and 3.8% had a positive family history. RESULTS: None of the 453 study subjects carried the G2019S mutation. CONCLUSIONS: Our result confirms previous reports that the G2019S mutation is rare among PD patients in the Asian population. This result supports the notion that the prevalence of this LRRK2 mutation is population specific, and that there may be a founder effect within western populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".