Impact of lipoprotein apheresis with dextran‐sulfate adsorption on the expression of genes involved in cardiovascular health in the blood of patients with homozygous familial hypercholesterolemia
Bibliographic record
Abstract
Lipoprotein apheresis (LA) with dextran sulfate adsorption (DSA) is a reliable method to decrease LDL-cholesterol (C) concentrations in patients with homozygous familial hypercholesterolemia (HoFH). The objective of the present study was to investigate the impact of LA with DSA on the mRNA expression of genes associated with cardiovascular health in the whole blood of HoFH patients. Blood samples were collected before and after LA treatment with DSA in 9 HoFH patients. Microarray analyses were performed to measure the whole blood expression of >30 000 annotated genes pre- and post-LA. Concomitant reductions in LDL-C (median -73.8%, range: -55.9 to -82.0, P = .0001) and lipoprotein (a) concentrations (median -74.1%, range -65.6 to -84.1, P = .003) were induced with LA treatment. LA with DSA did not impact the whole blood mRNA expression of most key genes involved in cardiovascular health, including those associated with cholesterol, fatty acid and lipoprotein metabolism. However, LA with DSA significantly upregulated the whole blood expression of early growth response protein (EGR)1 (1.94-fold, P = .02), EGR3 (1.56-fold, P = .0008) and B-cell lymphoma 3-encoded protein (BCL3; 1.25-fold, P = .03). In conclusion, this study demonstrated that a single LA treatment with DSA has very limited impact on the whole blood expression of a broad spectrum of genes associated with cardiovascular health. Our results suggest that contact between blood cells and the primary membrane or extracorporeal circulation could upregulate the expression of EGR1, EGR3, BCL3, and MMP9 in blood cells.
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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) | 0.000 | 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) | 0.001 | 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".