Genetic variation in hyaluronan metabolism loci is associated with plasma plasminogen activator inhibitor-1 concentration
Bibliographic record
Abstract
Elevated plasma plasminogen activator inhibitor-1 (PAI-1) concentration is associated with cardiovascular disease risk. PAI-1 is the primary inhibitor of fibrinolysis within both the circulation and the arterial wall, playing roles in both atherosclerosis and thrombosis. To define the heritable component, subjects within the population-based SHARE (Study of Health Assessment and Risk in Ethnic groups) and SHARE-AP (Study of Health Assessment and Risk Evaluation in Aboriginal Peoples) studies, composed of Canadians of South Asian (n = 298), Chinese (n = 284), European (n = 227), and Aboriginal (n = 284) descent, were genotyped using the gene-centric Illumina HumanCVD BeadChip. After imputation, more than 150,000 single nucleotide polymorphisms (SNPs) in more than 2000 loci were tested for association with plasma PAI-1 concentration. Marginal association was observed with the PAI-1 locus itself (SERPINE1; P < .05). However, 5 loci (HABP2, HSPA1A, HYAL1, MBTPS1, TARP) were associated with PAI-1 concentration at a P < 1 × 10(-5) threshold. The protein products of 2 of these loci, hyaluronan binding protein 2 (HABP2) and hyaluronoglucosaminidase 1 (HYAL1), play key roles in hyaluronan metabolism, providing genetic evidence to link these pathways.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".