Clinical Expression of Familial Hypercholesterolemia in Patients from France and French Canada Carrying Identical by Descent Pathogenic LDLR Gene Variants: a Proof-of-Concept Study
Bibliographic record
Abstract
Background: Studying patients carrying identical by descent (IBD) pathogenic gene variants allows to control for the disease-causing genetic background and to more accurately document the impact of modifiers. Familial hypercholesterolemia (FH) is characterized by elevated LDL-c levels, premature atherosclerosis and is often caused by defects in the LDLR gene. There is a high prevalence of FH in French Canada carry IBD FH-causing due to a founder effect from France in the 17th Century. Several FH patients currently living in French Canada (founder population) and in France (colonizing population) carry IBD FH-causing variants. The expression of FH is affected by environmental and genetic modifiers and patients with IBD variants may present different characteristics. Methods: In this study, we compared FH clinical expression patients carrying IBD LDLR pathogenic variants living in France or Canada. Four IBD variants, namely c.259T>G p.(Trp87Gly); c.2000G>A p.(Cys667Tyr); c.682G>A p.(Glu228Lys); and c.1048C>T p.(Arg350*) were selected. Untreated plasma lipid profiles, APOE genotype, cardiovascular risk factors and occurrence of symptomatic ASCVD were compared in 105 adult carriers (30 from France and 75 from French Canada). Results: All parameters were similar between the two populations, except for untreated total cholesterol (10.14 ± 1.89 mmol/L vs 8.65 ± 1.84 mmol/L, p=0.0006) and LDL-c concentrations (7.94 ± 1.86 mmol/L vs 6.93 ± 1.78 mmol/L, p=0.016) that were significantly higher in FH patients living in France, a trend that was observed in all studied LDLR variants. Conclusion: This study illustrates that FH patients sharing IBD pathogenic LDLR variants that have evolved in different geographic, cultural and socio-economic environments for hundreds of years, differ in term of cholesterol levels highlighting the importance of better understanding the interplay between genetic and environmental modulators of FH expression.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".