Docosahexaenoic Acid Attenuates Cardiovascular Risk Factors via a Decline in Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Plasma Levels
Bibliographic record
Abstract
Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a circulating protein that regulates cholesterol metabolism by promoting LDL receptor degradation in the liver and has recently been proposed as a therapeutic target in the management of hyperlipidaemia. We investigated the impact of dietary fat on the metabolism of sterols and on plasma PCSK9 concentrations to explore likely clinical usefulness. In a post hoc analysis of a double-blind randomised crossover controlled feeding trial, the Canola Oil Multicenter Intervention Trial (COMIT), volunteers (n = 54) with at least one condition related to metabolic syndrome consumed diets with one of the following treatment oils in beverages: (1) conventional canola oil (Canola); (2) canola oil rich in docosahexanoic acid (DHA) (CanolaDHA); and (3) high-oleic acid canola oil (CanolaOleic). The enrichment in oleic acid resulted in lower plasma cholesterol concentration compared with diets enriched in DHA. Contrarily, DHA-enriched oil significantly decreased plasma PCSK9 and triacylglycerols levels, but increased circulating levels of sterols. The variations in lathosterol, sitosterol, and campesterol indicate that plasma PCSK9 levels are sensitive to changes in cholesterol synthesis and/or absorption. There was a significant correlation between plasma PCSK9 levels and plasma triacylglicerol and apolipoprotein B levels, which was not affected by dietary fat. Therefore, our results suggest that the impact of dietary fats should not be discarded as complementary treatment in the management of patients with hyperlipidaemia. These findings should be considered in the analysis of ongoing studies and may represent a cautionary note in the treatment of patients with cardiovascular risk.
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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) | 0.001 | 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".