Severe hypertriglyceridemia is primarily polygenic
Bibliographic record
Abstract
BACKGROUND: Hypertriglyceridemia (HTG) is a complex trait defined by elevated plasma triglyceride levels. Genetic determinants of HTG have so far been examined in a piecemeal manner; understanding of its molecular basis, both monogenic and polygenic, is thus incomplete. OBJECTIVE: The objective of this study was to characterize genetic profiles of patients with severe HTG, and quantify the genetic determinants and molecular contributors. METHODS: We concurrently assessed rare and common variants in two independent cohorts of 251 and 312 Caucasian patients with severe HTG. DNA was subjected to targeted next-generation sequencing of 73 genes and 185 SNPs associated with dyslipidemia. LPL, APOC2, GPIHBP1, APOA5, and LMF1 genes were screened for rare variants, and a polygenic risk score was used to assess the accumulation of common variants. RESULTS: As there were no significant differences in the prevalence of genetic determinants between cohorts, data were combined for all 563 patients: 1.1% had biallelic (homozygous or compound heterozygous) rare variants, 14.4% had heterozygous rare variants, 32.0% had an extreme accumulation of common variants (ie, high polygenic risk), and 52.6% remained genetically undefined. Patients with HTG were 5.77 times (95% CI [4.26-7.82]; P < .0001) more likely to carry one of these types of genetic susceptibility compared with controls. CONCLUSIONS: We report the most in-depth, systematic evaluation of genetic determinants of severe HTG to date. The predominant feature was an extreme accumulation of common variants (high polygenic risk score), whereas a substantial proportion of patients also carried heterozygous rare variants. Overall, 46.3% of patients had polygenic HTG, whereas only 1.1% had biallelic or homozygous monogenic HTG.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".