Genome-Wide Linkage Analysis of Systolic and Diastolic Blood Pressure
Bibliographic record
Abstract
BACKGROUND: Blood pressure (BP), an important risk factor for coronary heart disease, is a complex trait with multiple genetic etiologies. While some loci affecting BP variation are known (eg, angiotensinogen), there are likely to be novel signals that can be detected with a genome scan approach. METHODS AND RESULTS: A genome-wide scan was performed in 125 random and 81 obese families participating in the Québec Family Study. A multipoint variance-components linkage analysis of 420 markers (353 microsatellites and 67 restriction fragment length polymorphisms) revealed several signals (P:<0.0023) for systolic BP on 1p (D1S551, ATP1A1), 2p (D2S1790, D2S2972), 5p (D5S1986), 7q (D7S530), 8q (CRH), and 19p (D19S247). Suggestive evidence (0.0023<P:<0.01) was found on 3q, 10p, 12p, 14q, and 22q. The results were encouraging for HSD3B1 (P:<0.03), AGT (P:<0.03), ACE (P:<0.02), and adipsin (P:<0.005) but null with regard to other candidates (eg, renin, and glucocorticoid and adrenergic receptors). CONCLUSIONS: Multiple linkage regions support the notion that risk for hypertension is due to multiple (ie, oligogenic) susceptibility loci. Comparisons across the complete, random, and obese samples suggest that some regions are specific to BP and others may involve obesity (eg, pleiotropy, epistasis, or gene-environment interaction). Some of these areas harbor known candidates. Others involve novel regions, some of which replicate previous reports and provide a focus for future studies to identify novel genes that influence interindividual variation in BP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".