Loss-of-Function <i>CREB3L3</i> Variants in Patients With Severe Hypertriglyceridemia
Bibliographic record
Abstract
Objective: Genetic determinants of severe hypertriglyceridemia include both common variants with small effects (assessed using polygenic risk scores) plus heterozygous and homozygous rare variants in canonical genes directly affecting triglyceride metabolism. Here, we broadened our scope to detect associations with rare loss-of-function variants in genes affecting noncanonical pathways, including those known to affect triglyceride metabolism indirectly. Approach and Results: From targeted next-generation sequencing of 69 metabolism-related genes in 265 patients of European descent with severe hypertriglyceridemia (≥10 mmol/L or ≥885 mg/dL) and 477 normolipidemic controls, we focused on the association of rare heterozygous loss-of-function variants in individual genes. We observed that compared with controls, severe hypertriglyceridemia patients were 20.2× (95% CI, 1.11–366.1; P =0.03) more likely than controls to carry a rare loss-of-function variant in CREB3L3 , which encodes a transcription factor that regulates several target genes with roles in triglyceride metabolism. Conclusions: Our findings indicate that rare variants in a noncanonical gene for triglyceride metabolism, namely CREB3L3 , contribute significantly to severe hypertriglyceridemia. Secondary genes and pathways should be considered when evaluating the genetic architecture of this complex trait.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".