<i>SNCA</i>,<i>MAPT</i>, and<i>GSK3B</i>in Parkinson disease: a gene-gene interaction study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Recent evidence suggests that variation in the SNCA, MAPT, and GSK3B genes interacts in affecting risk for Parkinson disease (PD). In the current study, we attempt to validate previously published findings, evaluating gene-gene interactions between SNCA, MAPT, and GSK3B in association with PD. METHODS: Three Caucasian PD patient-control series from the United States, Ireland, and Norway (combined n = 1020 patients and 1095 controls) were genotyped for SNCA rs356219, MAPT H1/H2-discriminating SNP rs1052553, and GSK3B rs334558 and rs6438552. RESULTS: Our findings indicate that as previously reported, the SNCA rs356219-G allele and MAPT rs1052553 (H1 haplotype) were both associated with an increased risk of PD, whilst contrary to previous reports, GSK3B variants were not. No pair-wise interaction was observed between SNCA, MAPT, and GSK3B; the risk effects of SNCA rs356219-G and MAPT rs1052553-H1 were seen in a similar manner across genotypes of other variants, with no evidence suggesting synergistic, antagonistic, or deferential effects. CONCLUSIONS: In the Caucasian patient-control series examined, risk for PD was influenced by variation in SNCA and MAPT but not GSK3B. Additionally, those three genes did not interact in determining disease risk.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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".