The <scp><i>LRRK2</i> R</scp>1628<scp>P</scp> Variant Plays a Protective Role in <scp>H</scp>an <scp>C</scp>hinese Population with <scp>A</scp>lzheimer's Disease
Bibliographic record
Abstract
AIMS: Alzheimer's disease (AD) and Parkinson's disease (PD) are the most prevalent neurodegenerative disorders that may share some overlapping etiologies. Mutations within leucine-rich repeat kinase 2 (LRRK2) have been reported to be responsible for PD, and the location of LRRK2 is within a linkage peak for sporadic AD (SAD). The aim of this study was to investigate two Asian-specific LRRK2 variants, R1628P and G2385R, with the association of Han Chinese SAD. METHODS: Genotyping of R1628P and G2385R was performed by PCR-restriction fragment length polymorphism (RFLP) analysis in 390 patients with SAD and 545 unrelated age- and sex-matched healthy controls. RESULTS: The frequency of the C allele within R1628P was more than three times higher in control group (1.7%) than in patients with SAD (0.5%) (OR 0.264; 95% CI, 0.088-0.792, P = 0.018). After stratification by the presence of one or two apolipoprotein E ε4 alleles, the protective effect becomes stronger (ε44: OR 0.028; 95% CI, 0.003-0.303, P = 0.003; ε4: OR 0.104; 95% CI, 0.013-0.818, P = 0.031). However, no difference was found in G2385R variant. CONCLUSION: Our study suggested that R1628P variant within LRRK2 plays a protective role in Han Chinese population with SAD and such effect has an interaction with the APOE genotype.
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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) | 0.001 | 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) | 0.003 | 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".