Modularized Genes in an Adrenal Pathway Reveal a Novel Mechanism in Hypertension Pathogenesis
Bibliographic record
Abstract
Human epidemiological studies have statistically localized a multitude of quantitative trait loci (QTLs) for blood pressure (BP). However, their potential pathogenic mechanisms causing hypertension remain mysterious. To fill this void, we utilized congenic knock-in genetics to physiologically analyze the BP effects of individual and combinational QTLs. The effect magnitude from a single QTL in vivo ranged from 33.8 to 59.8%. 'Double' and multiple combinations of QTLs exhibited the same BP impact as a single QTL alone. Consequently, the products of these QTLs seemed to belong to the same pathway involved in physiological BP regulations. From this, we identified a novel pathway of hypertension pathogenesis in vivo controlled by the CUE domain containing 1 protein (Cuedc1). This pathway physiologically modulates blood pressure, aldosterone production, and renal and cardiac functions. CUEDC1 originated from common mammalian ancestors, partly explaining similar blood pressures between humans and rodents on this shared mechanistic basis. A translation of CUEDC1 into diagnostic and treatment applications to humans seems individualized and mechanistic because humans and rats may utilize the same BP-regulating mechanisms involving CUEDC1. The future sustainability of post-GWAS will depend on a balanced and robust 'ecosystem' provided by model studies that are founded on the physiologies and mechanisms of BP regulations in vivo.
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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 | 0.000 |
| 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 | 0.001 |
| 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".