Association study of <i>DNAJC13, UCHL1, HTRA2, GIGYF2</i> and <i>EIF4G1</i> with Parkinson’s disease
Bibliographic record
Abstract
Abstract Rare mutations in genes originally discovered in multi-generational families have been associated with increased risk of Parkinson’s Disease (PD). The involvement of rare variants in DNAJC13, UCHL1, HTRA2, GIGYF2 and EIF4G1 loci have been poorly studied or produced conflicting results across cohorts. However, they are still being often referred to as “PD-genes” and used in different models. To further elucidate the role of these five genes in PD, we fully sequenced them using molecular inversion probes in 2,408 PD patients and 3,444 controls from 3 different cohorts. A total of 788 rare variants were identified across the five genes and three cohorts. Burden analyses and optimized sequence Kernel association tests revealed no significant association between any of the genes and PD after correction for multiple comparisons. Our results do not support an association of the five tested genes with PD. Combined with previous studies, it is unlikely that any of these genes plays an important role in PD. Their designation as “ PARK ” genes should be reconsidered.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".