Smooth muscle cell lysosomal acid lipase in atherosclerosis
Bibliographic record
Abstract
Background: Atherosclerosis, in the form of ischemic heart disease and stroke, is the leading cause of death globally. Its pathogenesis involves lipid accumulation in artery wall foam cells. Previous work indicates that foam cells in human and mouse atherosclerotic lesions are predominantly derived from smooth muscle cells (SMCs). Our laboratory has also characterized SMCs as being low in lysosomal acid lipase (LAL), the sole lysosomal cholesteryl ester hydrolase. Cholesteryl ester hydrolysis is critical in releasing cellular cholesterol stores for removal via cholesterol efflux. SMCs therefore represent a resistant pool of foam cells with reduced ability to efflux cholesterol. My dissertation investigates whether increasing LAL in SMCs can increase efflux for therapeutic effect in atherosclerosis. Methods and Results: In Chapter 1, I provided an overview of atherosclerosis, SMCs, and LAL. In Chapter 2, I tested whether increasing LAL activity in SMCs in vitro reduces lysosomal cholesteryl ester accumulation and increases cholesterol efflux, using adenoviral vectors, lipid nanoparticles (LNPs), and conditioned medium from SMCs treated with LNPs carrying LIPA mRNA, which encodes LAL. Increasing LAL activity by these methods reduced lysosomal cholesteryl esters. Treating SMCs with LNP LIPA conditioned medium increased efflux to ApoAI. In Chapter 3, I utilized a mouse model containing a tetracycline-response element promoter controlling human LIPA and a SMC specific promoter (SM22alpha) controlling a reverse-tetracycline transactivator, on a background of ApoE-deficiency, to specifically overexpress LAL in SMCs in response to doxycycline. I confirmed with preliminary data that increased SMC LAL reduced atherosclerosis progression. In Chapter 4, I tested whether increased circulating LAL stimulates atherosclerosis regression. LNPs carrying LIPA mRNA were injected into ApoE-deficient and AAV-PCSK9 atherosclerotic mice. I demonstrated increased serum LAL activity and aortic LAL protein, and preliminary evidence of reduced atherosclerosis, but also excess mortality in ApoE-deficient mice with prolonged LNP treatment. Conclusions: Increasing LAL in SMCs reduces lysosomal cholesteryl esters, freeing cholesterol stores to be effluxed from the cell. I determined that this reduces atherosclerotic lesion area in my SMC-specific LAL overexpression model. I also investigated LNP-mRNA as a method to increase LAL and target SMCs. These studies validate LAL and SMC foam cells as crucial therapeutic foci for atherosclerosis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".