A large-scale international meta-analysis of paraoxonase gene polymorphisms in sporadic ALS
Bibliographic record
Abstract
BACKGROUND: Six candidate gene studies report a genetic association of DNA variants within the paraoxonase locus with sporadic amyotrophic lateral sclerosis (ALS). However, several other large studies, including five genome-wide association studies, have not duplicated this finding. METHODS: We conducted a meta-analysis of 10 published studies and one unpublished study of the paraoxonase locus, encompassing 4,037 ALS cases and 4,609 controls, including genome-wide association data from 2,018 ALS cases and 2,425 controls. RESULTS: The combined fixed effects odds ratio (OR) for rs662 (PON1 Q192R) was 1.09 (95% confidence interval [CI], 1.02-1.16, p = 0.01); the genotypic OR for RR homozygotes at Q192R was 1.25 (95% CI, 1.07-1.45, p = 0.0004); the combined OR for rs854560 (PON1 L55M) was 0.97 (95% CI, 0.86-1.10, p = 0.62); the OR for rs10487132 (PON2) was 1.08 (95% CI, 0.92-1.27, p = 0.35). Although the rs662 polymorphism reached a nominal level of significance, no polymorphism was significant after multiple testing correction. In the subanalysis of samples with genome-wide data from which population outliers were removed, rs662 had an OR of 1.06 (95% CI, 0.97-1.16, p = 0.22). CONCLUSIONS: In contrast to previous positive smaller studies, our genetic meta-analysis showed no significant association of amyotrophic lateral sclerosis (ALS) with the PON locus. This is the largest meta-analysis of a candidate gene in ALS to date and the first ALS meta-analysis to include data from whole genome association studies. The findings reinforce the need for much larger and more collaborative investigations of the genetic determinants of ALS.
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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 | 0.019 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.031 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".