Long Noncoding RNA TRIBAL Links the 8q24.13 Locus to Hepatic Lipid Metabolism and Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: Genome-wide association studies identified a 20-Kb region of chromosome 8 (8q24.13) associated with plasma lipids, hepatic steatosis, and risk for coronary artery disease. The region is proximal to TRIB1 , and given its well-established role in lipid regulation in animal models, TRIB1 has been proposed to mediate the contribution of the 8q24.13 locus to these traits. This region overlaps a gene encoding the primate-specific long noncoding RNA transcript TRIBAL / TRIB1AL ( TRIB1 -associated locus), but the contribution of TRIBAL to coronary artery disease risk remains untested. METHODS: Using recently available expression quantitative trait loci data and hepatocyte models, we further investigated this locus by Mendelian randomization analysis. Following antisense oligonucleotide targeting of TRIBAL, transcription array, quantitative reverse transcription polymerase chain reaction, and enrichment analyses were performed and effects on apoB and triglyceride secretion were determined. RESULTS: Mendelian randomization analysis supports a causal relationship between genetically determined hepatic TRIBAL expression and markers of hepatic steatosis and coronary artery disease risk. By contrast, expression data sets did not support expression quantitative trait loci relationships between coronary artery disease–associated variants and TRIB1 . TRIBAL suppression reduced the expression of key regulators of triglyceride metabolism and bile acid synthesis. Enrichment analyses identified patterns consistent with impaired metabolic functions, including reduced triglyceride and cholesterol handling ability. Furthermore, TRIBAL suppression was associated with reduced hepatocyte secretion of triglycerides. CONCLUSIONS: This work identifies TRIBAL as a gene bridging the genotype-phenotype relationship at the 8q24.13 locus with effects on genes regulating hepatocyte lipid metabolism and triglyceride secretion.
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 | 0.000 |
| 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) | 0.003 | 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".