Plasma PCSK9 Is Associated with Age, Sex, and Multiple Metabolic Markers in a Population-Based Sample of Children and Adolescents
Bibliographic record
Abstract
BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a protein convertase that posttranslationally promotes the degradation of the low-density lipoprotein receptor (LDLR) in hepatocytes and increases plasma LDL cholesterol (LDL-C). Heterozygote gain-of-function mutations of PCSK9 are associated with the familial hypercholesterolemia phenotype, whereas loss-of-function variants are associated with reduced LDL-C concentrations and lower coronary risk. Plasma PCSK9 correlates with body mass index, triglyceridemia, total cholesterol, and LDL-C in adults, but no data are available in youth. METHODS: We studied 1739 French Canadian youth ages 9, 13, and 16 years who participated in the Quebec Child and Adolescent Health and Social Survey, a province-wide school-based survey conducted in 1999. An ELISA assay was used to measure plasma PSCK9. RESULTS: The mean (SD) plasma PCSK9 concentration was 84.7 (24.7) microg/L in the sample. In boys, plasma PCSK9 decreased with age, whereas the inverse was true for girls. There were statistically significant positive associations between PCSK9 and fasting glucose, insulin, and HOMA-IR (homeostasis model assessment of insulin resistance). In multivariable analysis, a 10% higher fasting insulin was associated with a 1%-2% higher PCSK9 in both sexes. There were also positive associations between PCSK9 and total cholesterol, LDL-C, and triglycerides, as well as with HDL-C and apolipoproteins A1 and B. CONCLUSIONS: PCSK9 is associated with age, sex, and multiple metabolic markers in youth. A novel finding is that PCSK9 is associated with fasting insulinemia, which suggests that PCSK9 could play a role in the development of dyslipidemia associated with the metabolic syndrome. .
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".