Abstract 336: Overrepresentation of Familial Hypercholesterolemia-causing Mutations in Patients with Familial Combined Hyperlipidemia
Bibliographic record
Abstract
Background_ Elevated plasma low-density lipoprotein (LDL) cholesterol is a feature of both familial hypercholesterolemia (FH) and familial combined hyperlipidemia (FCH). FH is predominantly a monogenic _autosomal dominant_ condition that results from mutations in the genes coding for low density lipoprotein receptor (LDLR), apolipoprotein B-100 (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9). In contrast, the genetic basis of FCH, a very common dyslipidemia in the human population, is less well understood, but is considered to be polygenic. Investigations in other polygenic lipid disorders indicate that genetic susceptibility is comprised of both common polymorphisms and rare heterozygous mutations. Re-sequencing technologies have identified greater accumulation of missense rare variants in candidate genes of diseased cohorts relative to healthy controls, thus indicating a potential role of candidate genes in disease etiology. Objective_ Our aim was to understand the genetic etiology of FCH. We hypothesized missense rare variants in the 3 known autosomal dominant FH-causing genes and the newly characterized inducible degrader of the low density lipoprotein receptor (IDOL), would accumulate in FCH patients (n=138) (cases) relative to controls (n=94). We tested this hypothesis using Sanger sequencing of coding sequences, intron-exon boundaries and some regulatory regions of the 4 candidate genes. Results & Discussion_ For cases vs controls, the total missense rare variant carrier counts were 7/138 vs 4/94 in LDLR and 14/138 vs 9/94 in APOB. Of all these missense rare variants found in our entire cohort, we found functionally verified FH-causing variants only in our cases and not in our controls (P =0.09), namely LDLR G314S, D333V, V806I and APOB R3500W variants. These variants likely explain hypercholesterolemia in those particular FCH patients. Conclusions_ This preliminary analysis of FCH candidate gene sequences supports the idea that rare FH-causing mutations are over-represented in FCH. The findings also support future expanded case-control and family studies to identify possible monogenic causes of FCH using various next-generation sequencing technologies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.006 | 0.001 |
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".