Common X-chromosome variants are associated with Parkinson’s disease risk
Bibliographic record
Abstract
Abstract Objective Identify genetic variants on the X-chromosome associated with Parkinson’s disease (PD) risk. Methods We performed an X-chromosome-wide association study (XWAS) of PD risk by meta-analyzing results from sex-stratified analyses. To avoid spurious associations, we designed a specific harmonization pipeline for the X-chromosome and focused on a European ancestry sample. We included 11,324 cases, 280,060 controls, and 5,379 proxy cases, based on parental history of PD. Additionally, we tested the association of significant variants with: (i) PD risk in an independent replication with 1,564 cases and 2,467 controls, and (ii) putamen volume in 33,360 individuals from the UK Biobank. Results In the discovery meta-analysis, we identified: rs7066890 (OR=1.10 [1.06-1.14]; P=2.2×10 −9 ) intron of GPM6B , and rs28602900 (OR=1.10 [1.07-1.14]; P=1.6×10 −8 ) in a high gene density region including RPL10, ATP6A1, FAM50A, PLXNA3 . The rs28602900 association with PD was replicated (OR=1.16 [1.03-1.30]; P=0.016) and shown to colocalize with a significant expression quantitative locus (eQTL) regulating RPL10 expression in the putamen and other brain tissues in GTEx. Additionally, the rs28602900 locus was found to be associated with reduced brain putamen volume. No results reached genome-wide significance in the sex-stratified analyses. Interpretation We report the first XWAS of PD and identify two genome-wide significant loci. The rs28602900 association replicated in an independent PD dataset and showed concordant effects in its association with putamen volume. Critically, rs26802900 is a significant eQTL of RPL10 .These results support a role for ribosomal proteins in PD pathogenesis and show that the X-chromosome contributes to PD genetic risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".