Combined hyperlipidemia is genetically similar to isolated hypertriglyceridemia
Bibliographic record
Abstract
BACKGROUND: Combined hyperlipidemia (CHL) is a common disorder defined by concurrently elevated low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) levels. Despite decades of study, the genetic basis of CHL remains unclear. OBJECTIVE: To characterize the genetic profiles of patients with CHL and compare them to those in patients with isolated hypercholesterolemia and isolated hypertriglyceridemia (HTG). METHODS: DNA from 259, 379 and 124 patients with CHL, isolated hypercholesterolemia and isolated HTG, respectively, underwent targeted sequencing. We assessed: 1) rare variants disrupting canonical LDL-C or TG metabolism genes; and 2) two polygenic scores-for elevated LDL-C and TG-calculated using common trait-associated single-nucleotide polymorphisms (SNPs). Genetic profiles were compared against 1000 Genomes Project controls. RESULTS: Both CHL and isolated HTG patients had significantly increased odds of a high polygenic score for TG: 2.50 (95% confidence interval [CI] 1.61-3.88; P < 0.001) and 3.72 (95% CI 2.24-6.19; P < 0.001), respectively. CHL patients had neither a significant accumulation of rare variants for LDL-C or TG, nor a high polygenic score for LDL-C. In contrast, patients with isolated hypercholesterolemia had a 3.03-fold increased odds (95% CI 2.22-4.13; P < 0.001) of carrying rare variants associated with familial hypercholesterolemia, while patients with isolated HTG had a 2.78-fold increased odds (95% CI 1.27-6.10; P = 0.0136) of carrying rare variants associated with severe HTG. CONCLUSION: CHL is genetically similar to isolated HTG, a known polygenic trait. Both cohorts had a significant accumulation of common TG-raising variants. Elevated LDL-C levels in CHL are not associated with common or rare LDL-C-related genetic variants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".