INSIG1 influences obesity-related hypertriglyceridemia in humans
Bibliographic record
Abstract
In our analysis of a quantitative trait locus (QTL) for plasma triglyceride (TG) levels [logarithm of odds (LOD) = 3.7] on human chromosome 7q36, we examined 29 single nucleotide polymorphisms (SNPs) across INSIG1, a biological candidate gene in the region. Insulin-induced genes (INSIGs) are feedback mediators of cholesterol and fatty acid synthesis in animals, but their role in human lipid regulation is unclear. In our cohort, the INSIG1 promoter SNP rs2721 was associated with TG levels (P = 2 x 10(-3) in 1,560 individuals of the original linkage cohort, P = 8 x 10(-4) in 920 unrelated individuals of the replication cohort, combined P = 9.9 x 10(-6)). Individuals homozygous for the T allele had 9% higher TG levels and 2-fold lower expression of INSIG1 in surgical liver biopsy samples when compared with individuals homozygous for the G allele. Also, the T allele showed additional binding of nuclear proteins from HepG2 liver cells in gel shift assays. Finally, the variant rs7566605 in INSIG2, the only homolog of INSIG1, enhances the effect of rs2721 (P = 0.00117). The variant rs2721 alone explains 5.4% of the observed linkage in our cohort, suggesting that additional, yet-undiscovered genes and sequence variants in the QTL interval also contribute to alterations in TG levels in humans.
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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) | 0.000 | 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) | 0.003 | 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".