The endothelial protein C receptor (PROCR) Ser219Gly variant and risk of common thrombotic disorders: a HuGE review and meta-analysis of evidence from observational studies
Bibliographic record
Abstract
The endothelial protein C receptor (EPCR) limits thrombus formation by enhancing activation of the protein C anticoagulant pathway, and therefore may play a role in the etiology of thrombotic disorders. The rs867186 single-nucleotide polymorphism in the PROCR gene (g.6936A > G, c.4600A > G), resulting in a serine-to-glycine substitution at codon 219, has been associated with reduced activation of the protein C pathway, although its association with thrombosis risk remains unclear. The present study is a highly comprehensive systematic review and meta-analysis, including unpublished genome-wide association study results, conducted to evaluate the evidence for an association between rs867186 and 2 common thrombotic outcomes, venous thromboembolism (VTE) and myocardial infarction (MI), which are hypothesized to share some etiologic pathways. MEDLINE, EMBASE, and HuGE Navigator were searched through July 2011 to identify relevant epidemiologic studies, and data were summarized using random-effects meta-analysis. Twelve candidate genes and 13 genome-wide association studies were analyzed (11 VTE and 14 MI, including 37,415 cases and 84,406 noncases). Under the additive genetic model, the odds of VTE increased by a factor of 1.22 (95% confidence interval, 1.11-1.33, P < .001) for every additional copy of the G allele. No evidence for association with MI was observed.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.021 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".