Rare genetic causes of autosomal dominant or recessive hypercholesterolaemia
Bibliographic record
Abstract
Familial hypercholesterolaemia (FH) is a human inherited disorder of metabolism characterised by increased serum low-density lipoprotein (LDL) cholesterol. It is caused by defects in the LDL-receptor pathway that impair normal uptake and clearance of LDL by the liver. The commonest cause of FH is mutations in LDLR, the gene for the LDL receptor, but defects also occur in APOB that encodes its major protein ligand. More recently, defects in two other genes, LDLRAP1 and PCSK9, have been found in patients with FH and investigation of these has shed new light on the functioning and complexity of the LDL receptor pathway. Cells from patients with autosomal recessive hypercholesterolaemia (ARH) fail to internalise the LDL receptor because they carry two defective alleles of LDLRAP1, a gene that encodes a specific clathrin adaptor protein. PCSK9 encodes proprotein convertase subtilisin kexin type 9, a secreted protein that binds to the LDL receptor and promotes its degradation. Gain-of function mutations in PCSK9 are autosomal dominant and cause hypercholesterolaemia because they increase the affinity of PCSK9 protein for the LDL receptor, whereas loss-of-function mutations reduce serum cholesterol because LDL-receptor protein is exposed to reduced PCSK9-mediated degradation. Thus, PCSK9 has become a new target for cholesterol-lowering drug therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".