Altered DNA Methylation of Long Noncoding RNA <i>H19</i> in Calcific Aortic Valve Disease Promotes Mineralization by Silencing <i>NOTCH1</i>
Bibliographic record
Abstract
BACKGROUND: Calcific aortic valve disease is characterized by an abnormal mineralization of the aortic valve. Osteogenic activity in the aortic valve is under the control of NOTCH1, which regulates the expression of key pro-osteogenic genes such as RUNX2 and BMP2. Long noncoding RNAs (lncRNAs) may reprogram cells by altering the gene expression pattern. METHODS: Multidimensional genomic profiling was performed in human aortic valves to document the expression of lncRNAs and the DNA methylation pattern in calcific aortic valve disease. In-depth functional assays were carried out to document the impact of lncRNA on the mineralization of the aortic valve. RESULTS: We documented that lncRNA H19 (H19) was increased in calcific aortic valve disease. Hypomethylation of the promoter region was observed in mineralized aortic valves and was inversely associated with H19 expression. Knockdown and overexpression experiments showed that H19 induces a strong osteogenic phenotype by altering the NOTCH1 pathway. Gene promoter analyses showed that H19 silenced NOTCH1 by preventing the recruitment of p53 to its promoter. A knockdown of H19 in valve interstitial cells (VICs) increased the expression of NOTCH1 and decreased the level of RUNX2 and BMP2, 2 downstream targets repressed by NOTCH1. In rescue experiments, the transfection of a vector encoding for the active Notch intracellular domain prevented H19-induced mineralization of valve interstitial cells. CONCLUSIONS: These findings indicate that a dysregulation of DNA methylation in the promoter of H19 during calcific aortic valve disease is associated with a higher expression of this lncRNA, which promotes an osteogenic program by interfering with the expression of NOTCH1.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".