Abstract 14630: Elevated CETP Activity is Associated With Low, Dysfunctional HDL in High Cardiovascular Risk South Asians
Bibliographic record
Abstract
Background and Rationale: Low HDL in South Asians (SA) contribute greatly to their high coronary heart disease (CHD) risk relative to European Caucasians (EC), however, the cause of low HDL in SA is unknown. Here we investigated whether cholesteryl-ester transfer protein (CETP) plays a role in mediating low HDL in SA. Methods: Serum was obtained from metabolically well characterized individuals of SA and EC descent (N=244 and 238, respectively) and measured for CETP activity. HDL lipid and protein contents were quantified and HDL size and particle number were measured via NMR. The capacity of HDL to mediate cholesterol efflux was assessed in J774 macrophages with apoB-depleted patient serum. Results: CETP activity was elevated in SA compared with EC (26.5±0.45 vs. 18.5±0.45 pmol/uL/hr, P< 0.0001). HDL from SA was pro-atherogenic - that is, triglyceride-enriched, cholesteryl ester-depleted, reduced in apoAI and smaller in size than in EC (P< 0.05 for all). SA HDL, moreover, showed a reduced capacity to mediate macrophage cholesterol efflux (by 20%, P< 0.0001), even in a subset of younger SA (<40 years, P<0.01). Composition and size changes in HDL were independent predictors of carotid artery intima-media thickness (IMT) in SA (P< 0.05). Conclusions: We have identified for the first time a mechanism to account for low HDL in SA. Elevated CETP in SA was associated with triglyceride-enriched, cholesteryl ester-depleted HDL, smaller in size and reduced in apoA-I content, producing HDL that is less stable in the circulation and less atheroprotective. This was confirmed with the lower relative capacity of HDL from SA to mediate cellular cholesterol efflux and independent correlation of their HDL compositional changes with carotid IMT.
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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 | 0.001 | 0.001 |
| 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) | 0.005 | 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".