Tissue-Specific Roles of ABCA1 Influence Susceptibility to Atherosclerosis
Bibliographic record
Abstract
OBJECTIVE: The ATP-binding cassette transporter, subfamily A, member 1 (ABCA1) plays a key role in HDL cholesterol metabolism. However, the role of ABCA1 in modulating susceptibility to atherosclerosis is controversial. METHODS AND RESULTS: We investigated the role of ABCA1 in atherosclerosis using a combination of overexpression and selective deletion models. First, we examined the effect of transgenic overexpression of a full-length human ABCA1-containing bacterial artificial chromosome (BAC) in the presence or absence of the endogenous mouse Abca1 gene. ABCA1 overexpression in the atherosclerosis-susceptible Ldlr(-/-) background significantly reduced the development of atherosclerosis in both the presence and absence of mouse Abca1. Next, we used mice with tissue-specific inactivation of Abca1 to dissect the discrete roles of Abca1 in different tissues on susceptibility to atherosclerosis. On the Apoe(-/-) background, mice lacking hepatic Abca1 had significantly reduced HDL cholesterol and accelerated atherosclerosis, indicating that the liver is an important site at which Abca1 plays an antiatherogenic role. In contrast, mice with macrophage-specific inactivation of Abca1 on the Ldlr(-/-) background displayed no change in atherosclerotic lesion area. CONCLUSIONS: These data indicate that physiological expression of Abca1 modulates the susceptibility to atherosclerosis and establish hepatic Abca1 expression as an important site of atheroprotection. In contrast, we show that selective deletion of macrophage Abca1 does not significantly modulate atherogenesis.
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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".