SCARB2 variants and glucocerebrosidase activity in Parkinson’s disease
Bibliographic record
Abstract
Abstract Mutations in glucocerebrosidase (GBA) are a common risk factor for Parkinson's disease (PD). The scavenger receptor class B member 2 (SCARB2) gene encodes a receptor responsible for the transport of glucocerebrosidase (GCase) to the lysosome. Two common SNPs in linkage disequilibrium with SCARB2, rs6812193 and rs6825004, have been associated with PD and Lewy Body Disease in genome-wide association studies. Whether these SNPs are associated with altered glucocerebrosidase enzymatic activity is unknown. Our objective was to determine whether SCARB2 SNPs are associated with PD and with reduced GCase activity. The GBA gene was fully sequenced, and the LRRK2 G2019S and SCARB2 rs6812193 and rs6825004 SNPs were genotyped in 548 PD patients and 272 controls. GCase activity in dried blood spots was measured by tandem mass spectrometry. We tested the association between SCARB2 genotypes and PD risk in regression models adjusted for gender, age, and LRRK2 G2019S and GBA mutation status. We compared GCase activity between participants with different genotypes at rs6812193 and rs6825004. Genotype at rs6812193 was associated with PD status. PD cases were less likely to carry the T allele than the C allele (OR=0.71; P=0.004), but GCase enzymatic activity was similar across rs6812193 genotypes (C/C: 11.88 μmol/l/h; C/T: 11.80 μmol/l/h; T/T: 12.02 μmol/l/h; P=0.867). Genotype at rs6825004 was not associated with either PD status or GCase activity. In conclusion, our results support an association between SCARB2 genotype at rs6812193 and PD, but suggest that the increased risk is not mediated by GCase activity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".