Proprotein Convertase Subtilisin/Kexin type 9 affects insulin but not lipid metabolism in cystic fibrosis
Bibliographic record
Abstract
PURPOSE: Cystic Fibrosis (CF) is the most common genetic disorder and, with improved survival, glucose abnormalities have emerged as a major comorbidity. Proprotein convertase subtilisin/kexin type 9 (PCSK9), a regulator of plasma LDL-cholesterol homeostasis, is associated with lipid and glucose metabolism in healthy individuals. Here we report on the link between PCSK9 and markers of metabolism in CF. METHODS: Cross-sectional analysis was performed on CF patients (≥ 18 years, N=94) from the Montreal Cohort, without known diabetes, and on healthy individuals (N=19). The levels of PCSK9 and lipid markers were quantified and all subjects underwent a 2 h oral glucose tolerance test. RESULTS: No significant differences in PCSK9 levels were found between healthy individuals and patients with CF, or between the groups with different degrees of glucose tolerance. No association was found between PCSK9 and markers of lipid metabolism; however, a positive correlation was found between PCSK9 and total insulin secretion and a negative one with insulin sensitivity in CF patients who had normal glucose tolerance. CONCLUSION: Circulating levels of PCSK9 in the CF population are comparable to those in the healthy population. There are no associations between PCSK9 levels and either glucose or lipid homeostasis parameters. Nevertheless, a statistically significant link was observed between PCSK9 and markers of insulin homeostasis, solely in CF patients who presented normal glucose tolerance. Further exploration of the relationship between PCSK9 and insulin homeostasis in CF patients with normal glucose tolerance is warranted.
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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 | 0.001 |
| 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) | 0.002 | 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".