Excess of Rare Variants in Non–Genome-Wide Association Study Candidate Genes in Patients With Hypertriglyceridemia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Rare variant accumulation studies can implicate genes in disease susceptibility when a significant burden is observed in patients versus control subjects. Such analyses might be particularly useful for candidate genes that are selected based on experiments other than genome-wide association studies (GWAS). We sought to determine whether rare variants in non-GWAS candidate genes identified from mouse models and human mendelian syndromes of hypertriglyceridemia (HTG) accumulate in patients with polygenic adult-onset HTG. METHODS AND RESULTS: We resequenced protein coding regions of 3 genes with established roles (APOC2, GPIHBP1, LMF1) and 2 genes recently implicated (CREB3L3 and ZHX3) in TG metabolism. We identified 41 distinct heterozygous rare variants, including 29 singleton variants, in the combined sample; in total, we observed 47 rare variants in 413 HTG patients versus 16 in 324 control subjects (odds ratio=2.3; P=0.0050). Post hoc assessment of genetic burden in individual genes using 3 different tests suggested that the genetic burden was most prominent in the established genes LMF1 and APOC2, and also in the recently identified CREB3L3 gene. CONCLUSIONS: These extensive resequencing studies show a significant accumulation of rare genetic variants in non-GWAS candidate genes among patients with polygenic HTG, and indicate the importance of testing specific hypotheses in large-scale resequencing studies.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it