<i>LRRK2</i> gene in Parkinson disease
Bibliographic record
Abstract
BACKGROUND: In addition to the four well-confirmed genes linked to early-onset Parkinson disease (PD) (SNCA, PARKIN, DJ-1, and PINK1), mutations in the leucine-rich repeat kinase 2 gene (LRRK2) have recently been identified in families with autosomal dominant late-onset PD. OBJECTIVE: To perform mutation analysis of LRRK2 in probands of families showing dominant inheritance of PD and to conduct a case control association study to test the hypothesis that common coding variations might be associated with increased susceptibility to PD. METHODS: All 51 LRRK2 coding exons were sequenced in 23 probands and the mutation frequencies were evaluated in 180 neurologically normal control subjects. For the association study the authors genotyped four coding LRRK2 polymorphisms in 250 normal control subjects and 121 patients with PD (predominantly white patients of Canadian origin), 84% of whom had age at onset before 50 years and 42% had a positive family history. RESULTS: The authors identified three probands with heterozygous LRRK2 mutations: two of them have the known G2019S substitution and one proband has a novel I1371V substitution. Mutation analysis of a large family demonstrated complete segregation of the G2019S with PD. However, there was no association between PD and any of the four polymorphisms at the allelic or genotypic levels (p > 0.17). Furthermore, the authors did not detect a modifying effect for any genotype or of APOE genotypes upon the age at onset in the PD group (p > 0.20). CONCLUSIONS: The results support the prior suggestion that LRRK2 mutations cause PD. The disease in the families reported here presents a phenotype indistinguishable from typical PD. All three families demonstrate a very variable age at onset that is not explained by APOE genotypes. The common coding variations in the LRRK2 gene neither constitute strong PD risk factors nor modify the age at onset; however, the possibility of a modest risk effect remains to be assessed in large datasets.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".