Cascade screening for familial hypercholesterolemia-identification of the C308Y mutation in multiple family members and relatives for the first time in mainland China
Bibliographic record
Abstract
BACKGROUND: Familial hypercholesterolemia (FH), an autosomal dominant genetic disorder, is underdiagnosed and undertreated. The majority of FH cases are caused by low density lipoprotein receptor (LDL-R) gene mutations. The C308Y mutation in LDL-R results in approximately 70% loss of LDL-R activity, leading to the elevation of low density lipoprotein-cholesterol (LDL-C) and an increased risk of premature coronary heart disease (CHD). The aim of this study was to identify FH cases by cascade screening in family members and relatives of a 37-year old male with premature CHD and hypercholesterolemia. METHODS: Clinical exam, blood lipid profiling and genomic DNA sequencing of all exons of LDL-R were performed for the proband and his 14 family members and relatives. FH diagnosis was carried out using the Dutch Lipid Clinic Network (DLCN) criteria. RESULTS: Lipid profiling showed that 9 individuals, including the proband, had hypercholesterolemia. All these 9 subjects had a G > A substitution at nucleotide 986 in exon 7 resulting in the C308Y mutation as determined by DNA sequencing, and all those carrying the mutation were diagnosed as having definite FH under the DLCN criteria. However, most (7/9) did not have suggestive clinical manifestations of CHD. CONCLUSIONS: The C308Y mutation was discovered in multiple family members and relatives for the first time in mainland China. Cascade screening is key for the confirmatory diagnosis of FH. Our hypothesis that the C308Y is a common variant in the population of Southern China origin warrants further validation by screening for the C308Y mutation in a large population.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".