Monosaccharide-induced lipogenesis regulates the human hepatic sex hormone–binding globulin gene
Bibliographic record
Abstract
The liver produces plasma sex hormone-binding globulin (SHBG), which transports sex steroids and regulates their access to tissues. In overweight children and adults, low plasma SHBG levels are a biomarker of the metabolic syndrome and its associated pathologies. Here, we showed in transgenic mice and HepG2 hepatoblastoma cells that monosaccharides (glucose and fructose) reduce human SHBG production by hepatocytes. This occurred via a downregulation of hepatocyte nuclear factor-4alpha (HNF-4alpha) and replacement of HNF-4alpha by the chicken OVA upstream promoter-transcription factor 1 at a cis-element within the human SHBG promoter, coincident with repression of its transcriptional activity. The dose-dependent reduction of HNF-4alpha levels in HepG2 cells after treatment with glucose or fructose occurred in concert with parallel increases in cellular palmitate levels and could be mimicked by treatment with palmitoyl-CoA. Moreover, inhibition of lipogenesis prevented monosaccharide-induced downregulation of HNF-4alpha and reduced SHBG expression in HepG2 cells. Thus, monosaccharide-induced lipogenesis reduced hepatic HNF-4alpha levels, which in turn attenuated SHBG expression. This provides a biological explanation for why SHBG is a sensitive biomarker of the metabolic syndrome and the metabolic disturbances associated with increased fructose consumption.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".