The elevation of plasma concentrations of apoB-48-containing lipoproteins in familial hypercholesterolemia is independent of PCSK9 levels
Bibliographic record
Abstract
BACKGROUND: Previous studies have reported high plasma concentrations of both intestinal apolipoprotein (apo) B-48-containing lipoproteins and PCSK9 in subjects with familial hypercholesterolemia (FH). However, the extent to which LDL receptor deficiency and PCSK9 levels influence plasma apoB-48 concentrations in humans remains to be fully characterized. The objective of the study was to assess the independent association between FH, PCSK9 concentrations and plasma apoB-48 levels in a large cohort of genetically defined FH heterozygotes (HeFH) and homozygotes (HoFH). METHODS: A total of 118 HeFH, 6 HoFH, and 117 controls were included in the study. Plasma PCSK9 and apoB-48 concentrations were measured in the fasting state. RESULTS: Plasma PCSK9 and apoB-48 levels were higher in FH subjects compared with controls (PCSK9: HoFH: 642.6 ± 246.9 vs. HeFH: 324.9 ± 119.8 vs. CONTROLS: 194.5 ± 65.9 ng/mL, P < 0.0001; apoB-48: HoFH: 14.71 ± 4.36 vs. HeFH: 6.55 ± 4.24 vs. CONTROLS: 3.03 ± 2.07 μg/mL; P < 0.0001). There were no correlations between apoB-48 and PCSK9 plasma levels in both controls (ρ = 0.06, P = 0.5) and HeFH subjects (ρ = 0.07, P = 0.4). Multiple linear regression analysis showed that the FH status was the only independent factor associated with apoB-48 levels, contributing to 28.7% of the variance (P < 0.0001). CONCLUSIONS: These data indicate that the elevation in plasma apoB-48 levels associated with FH is independent of PCSK9 levels. TRIAL REGISTRATION: NCT02225340 .
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".