Variations in HDL-carried miR-223 and miR-135a concentrations after consumption of dietary trans fat are associated with changes in blood lipid and inflammatory markers in healthy men - an exploratory study
Bibliographic record
Abstract
A high consumption of trans fatty acids (TFAs) is associated with an increased risk of cardiovascular diseases (CVDs). High-density lipoproteins (HDLs) have many cardioprotective properties and transport functional microRNAs (miRNAs) to recipient cells. We hypothesized that dietary TFAs modify the HDL-carried miRNA profile, therefore modulating its cardioprotective properties. We assessed whether consumption of dietary TFAs modifies HDL-carried miR-223-3p and miR-135a-3p concentration and the inter-relationship between diet-induced changes in HDL-carried miRNA concentration and CVD risk markers. In a double blind, randomized, crossover, controlled study, 9 men were fed each of 3 experimental isoenergetic diets: 1) High in industrial TFA (iTFA; 3.7% energy); 2) High in TFA from ruminants (rTFA; 3.7% energy); 3) Low in TFA (control; 0.8% energy) for 4 weeks each. HDLs were isolated by ultracentrifugation and miRNAs were quantified by RT-qPCR. Variations in HDL-miR-223-3p concentration were negatively correlated with variations in HDL-cholesterol after the iTFA diet (rs = 0.82; P = 0.007), and positively correlated with variations in C-reactive protein concentration after the rTFA diet (rs = 0.75; P = 0.020). Variations in HDL-miR-135a-3p concentration were positively correlated with variations in total triglyceride (TG) concentration following the iTFA diet (rs = -0.82; P = 0.007), and with variations in low-density lipoprotein (LDL)-TG concentration following the rTFA diet (rs = 0.83; P = 0.005), compared to the control diet. However, the consumption of dietary TFAs has no significant unidirectional impact on HDL-carried miR-223-3p and miR-135a-3p concentrations. Our results suggest that the variability in the HDL-carried miRNAs response to TFA intake, by being associated with variations in CVD risk factors, might reflect physiological changes in HDL functions.
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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 | 0.000 | 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 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".