Independent and joint effects of the <i>MAPT</i> and <i>SNCA</i> genes in Parkinson disease
Bibliographic record
Abstract
OBJECTIVE: We studied the independent and joint effects of the genes encoding alpha-synuclein (SNCA) and microtubule-associated protein tau (MAPT) in Parkinson disease (PD) as part of a large meta-analysis of individual data from case-control studies participating in the Genetic Epidemiology of Parkinson's Disease (GEO-PD) consortium. METHODS: Participants of Caucasian ancestry were genotyped for a total of 4 SNCA (rs2583988, rs181489, rs356219, rs11931074) and 2 MAPT (rs1052553, rs242557) single nucleotide polymorphism (SNPs). Individual and joint effects of SNCA and MAPT SNPs were investigated using fixed- and random-effects logistic regression models. Interactions were studied on both a multiplicative and an additive scale, and using a case-control and case-only approach. RESULTS: Fifteen GEO-PD sites contributed a total of 5,302 cases and 4,161 controls. All 4 SNCA SNPs and the MAPT H1-haplotype-defining SNP (rs1052553) displayed a highly significant marginal association with PD at the significance level adjusted for multiple comparisons. For SNCA, the strongest associations were observed for SNPs located at the 3' end of the gene. There was no evidence of statistical interaction between any of the 4 SNCA SNPs and rs1052553 or rs242557, neither on the multiplicative nor on the additive scale. INTERPRETATION: This study confirms the association between PD and both SNCA SNPs and the H1 MAPT haplotype. It shows, based on a variety of approaches, that the joint action of variants in these 2 loci is consistent with independent effects of the genes without additional interacting effects.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".