Elevated cholesteryl ester transfer protein (CETP) activity, a major determinant of the atherogenic dyslipidemia, and atherosclerotic cardiovascular disease in South Asians
Bibliographic record
Abstract
AIMS: Why South Asians are at increased risk of premature atherosclerotic cardiovascular diseases compared with other ethnic groups is not fully understood. Atherogenic dyslipoproteinemia - hypertriglyceridemia, elevated numbers of low-density lipoprotein (LDL) particles and low high-density lipoprotein cholesterol (HDL-C) - is more common in South Asians but the mechanisms responsible have not been explicated. Here we examined whether the circulating lipid transfer protein, cholesteryl ester transfer protein (CETP), plays a role in the pathogenesis of the atherogenic dyslipoproteinemia among South Asians. METHODS AND RESULTS: CETP activity was determined by exogenous substrate assay in the serum of healthy, metabolically well-characterized individuals of South Asian and European descent (N = 244 and 238, respectively). Serum and lipoprotein lipids and apolipoproteins were measured and lipoprotein particle number and size were quantified via nuclear magnetic resonance spectroscopy. All the elements of the atherogenic dyslipoproteinemia were more severe in South Asians and CETP activity was significantly greater by 30% in South Asians compared with Europeans, adjusted for age, sex, body mass index and waist circumference (p < 0.0001). CETP activity was directly associated with serum triglycerides and inversely with HDL-C in the whole population. CETP activity was also directly related to apoB and LDL particle number. Finally, increased CETP activity was associated with pro-atherogenic reductions in HDL and LDL particle size. CONCLUSIONS: We identified novel associations between elevated CETP activity and the triad of quantitative and qualitative lipoprotein abnormalities in the atherogenic dyslipidemia in South Asians, a major contributor of increased atherosclerotic cardiovascular diseases in South Asians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.000 | 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".