Resequencing Genomic DNA of Patients With Severe Hypertriglyceridemia (MIM 144650)
Bibliographic record
Abstract
OBJECTIVE: The genetic determinants of severe hypertriglyceridemia (HTG; MIM 144650) in adults are poorly defined. We therefore resequenced 3 candidate genes, namely LPL, APOC2, and APOA5, to search for accumulation of missense mutations in patients with severe HTG compared with normolipidemic subjects. METHODS AND RESULTS: We resequenced >2 million base pairs of genomic DNA from 110 nondiabetic patients with severe HTG and determined the prevalence of coding sequence variants compared with 472 age- and sex-matched normolipidemic controls. We found: (1) heterozygous mutations (LPL p.Q-12E >11X, p.D25H, p.W86R, p.G188E, p.I194T and p.P207L; APOC2 p.K19T and IVS2-30G>A) in 10.0% of severe HTG patients compared with 0.2% of controls (carrier odds ratio [OR] 52, 95% confidence interval [CI] 8.6 to 319); and (2) an association of the APOA5 p.S19W missense variant with severe HTG (carrier OR 5.5 95% CI 3.3 to 9.1). Furthermore, either rare mutations or the APOA5 p.S19W variant were found in 41.8% of HTG subjects compared with 8.9% of controls (carrier OR 7.4, 95% CI 4.5 to 12.0). Also, heterozygotes for rare mutations had a significantly reduced plasma triglyceride response to fibrate monotherapy. CONCLUSIONS: Both common and rare DNA variants in candidate genes were found in a substantial proportion of severe HTG patients. The findings underscore the value of candidate gene resequencing to understand the genetic contribution in complex lipoprotein and metabolic disorders.
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 | 0.000 | 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) | 0.001 | 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".