Disrupting the key circadian regulator CLOCK leads to age-dependent cardiovascular disease
Bibliographic record
Abstract
The circadian mechanism underlies daily rhythms in cardiovascular physiology and rhythm disruption is a major risk factor for heart disease and worse outcomes. However, the role of circadian rhythms is generally clinically unappreciated. Clock is a core component of the circadian mechanism and here we examine the role of Clock as a vital determinant of cardiac physiology and pathophysiology in aging. Clock Δ19/Δ19 mice develop age-dependent increases in heart weight, hypertrophy, dilation, impaired contractility, and reduced myogenic responsiveness. Young Clock Δ19/Δ19 hearts express dysregulated mRNAs and miRNAs in the PTEN-AKT signal pathways important for cardiac hypertrophy. We found a rhythm in the Pten gene and PTEN protein in WT hearts; rhythmic oscillations are lost in Clock Δ19/Δ19 hearts. Changes in PTEN are associated with reduced AKT activation and changes in downstream mediators GSK-3β, PRAS40, and S6K1. Cardiomyocyte cultures confirm that Clock regulates the AKT signalling pathways crucial for cardiac hypertrophy. In old Clock Δ19/Δ19 mice cardiac AKT, GSK3β, S6K1 phosphorylation are increased, consistent with the development of age-dependent cardiac hypertrophy. Lastly, we show that pharmacological modulation of the circadian mechanism with the REV-ERB agonist SR9009 reduces AKT activation and heart weight in old WT mice. Furthermore, SR9009 attenuates cardiac hypertrophy in mice subjected to transverse aortic constriction (TAC), supporting that the circadian mechanism plays an important role in regulating cardiac growth. These findings demonstrate a crucial role for Clock in growth and renewal; disrupting Clock leads to age-dependent cardiomyopathy. Pharmacological targeting of the circadian mechanism provides a new opportunity for treating heart disease.
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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".