Prelamin A Does Not Promote Atherosclerosis or Vascular Smooth Muscle Loss
Bibliographic record
Abstract
ABSTRACT BACKGROUND Hutchinson-Gilford progeria syndrome (HGPS) is an accelerated aging disorder characterized by numerous symptoms, including early-onset atherosclerosis, with most patients suffering fatal myocardial infarctions or strokes by the second decade of life. HGPS is caused by mutations in LMNA that lead to expression of an internally truncated, farnesylated prelamin A variant called progerin, which induces loss of vascular smooth muscle cells (VSMCs). Some studies have also reported that accumulation of full-length farnesylated prelamin A, which is normally completely processed to mature non-farnesylated lamin A, can also drive vascular pathology during physiological aging. METHODS To assess the effects of prelamin A expression on atherosclerosis and aortic VSMCs, we used Lmna L648R/L648R mice that express a prelamin A variant with a lysine to arginine point mutation that prevents its processing to mature lamin A. To determine if prelamin A expression has an impact on atherosclerotic plaques, we crossed Lmna L648R/L648R mice to LDL receptor-deficient Ldlr −/− mice that develop hyperlipidemia on a high-fat diet. RESULTS Atherosclerotic plaque lesion area and necrotic core area were not different in hyperlipidemic Lmna L648R/L648R mice that expressed only prelamin A, and no mature lamin A, compared to hyperlipidemic Lmna +/+ mice that expressed only fully-processed mature lamin A and no prelamin A. Additionally, exclusive prelamin A expression did not result in loss of aortic VSMCs or adventitial thickening in hyperlipidemic Lmna L648R/L648R mice with atherosclerosis at 28 weeks of age. Indeed, aortic vascular smooth muscle remained normal in older Lmna L648R/L648R mice at 52 weeks of age. CONCLUSIONS In contrast to the prelamin A variant progerin expressed in HGPS, prelamin A does not appear to cause vascular smooth muscle loss, promote atherosclerosis or drive vascular aging.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".