Proatherogenic Role of Elevated CE Transfer From HDL to VLDL <sub>1</sub> and Dense LDL in Type 2 Diabetes
Bibliographic record
Abstract
Plasma cholesteryl ester transfer protein (CETP) facilitates intravascular lipoprotein remodeling by promoting the heteroexchange of neutral lipids. To determine whether the degree of triglyceridemia may influence the CETP-mediated redistribution of HDL CE between atherogenic plasma lipoprotein particles in type 2 diabetes, we evaluated CE mass transfer from HDL to apoB-containing lipoprotein acceptors in the plasma of type 2 diabetes subjects (n=38). In parallel, we investigated the potential relationship between CE transfer and the appearance of an atherogenic dense LDL profile. The diabetic population was divided into 3 subgroups according to fasting plasma triglyceride (TG) levels: group 1 (G1), TG<100 mg/dL; group 2 (G2), 100<TG<200 mg/dL; and group 3 (G3), TG>200 mg/dL. Type 2 diabetes patients displayed an asymmetrical LDL profile in which the dense LDL subfractions predominated. Plasma levels of dense LDL subfractions were strongly positively correlated with those of plasma triglyceride (TG) (r=0.471; P:=0.0003). The rate of CE mass transfer from HDL to apoB-containing lipoproteins was significantly enhanced in G3 compared with G2 or G1 (46.2+/-8.1, 33.6+/-5.3, and 28.2+/-2.7 microg CE transferred. h(-1). mL(-1) in G3, G2, and G1, respectively; P:<0.0001 G3 versus G1, P:=0.0001 G2 versus G1, and P:=0.02 G2 versus G3). The relative capacities of VLDL and LDL to act as acceptors of CE from HDL were distinct between type 2 diabetes subgroups. LDL particles represented the preferential CE acceptor in G1 and accounted for 74% of total CE transferred from HDL. By contrast, in G2 and G3, TG-rich lipoprotein subfractions accounted for 47% and 72% of total CE transferred from HDL, respectively. Moreover, the relative proportion of CE transferred from HDL to VLDL(1) in type 2 diabetes patients increased progressively with increase in plasma TG levels. The VLDL(1) subfraction accounted for 34%, 43%, and 52% of total CE transferred from HDL to TG-rich lipoproteins in patients from G1, G2, and G3, respectively. Finally, dense LDL acquired an average of 45% of total CE transferred from HDL to LDL in type 2 diabetes patients. In conclusion, CETP contributes significantly to the formation of small dense LDL particles in type 2 diabetes by a preferential CE transfer from HDL to small dense LDL, as well as through an indirect mechanism involving an enhanced CE transfer from HDL to VLDL(1), the specific precursors of small dense LDL particles in plasma.
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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 | 0.000 |
| 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 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".