DNA hypermethylation of <i>Kiss1r</i> promoter and reduction of hepatic Kiss1r in female rats with type 2 diabetes
Bibliographic record
Abstract
Kisspeptin, produced from the brain and peripheral tissues, may constitute an important link in metabolic regulation in response to external cues, such as diet. The kisspeptin system is well described in the brain. However, its function and regulation in the peripheral tissues, especially in relation to metabolic disease and sex differences, remain to be elucidated. As Kiss1 and Kiss1r, encoding for kisspeptin and kisspeptin receptors, respectively, are altered by overnutrition/fasting and regulated by DNA methylation during puberty and cancer, epigenetic mechanisms in metabolic disorders are highly probable. In the present study, we experimentally induced type 2 diabetes mellitus (DM2) in female Wistar rats using high-fat diet/streptozocin. We analysed expression and DNA methylation of Kiss1 and Kiss1r in the peripheral tissues, using quantitative-reverse-transcription PCR (qRT-PCR) and pyrosequencing. We discovered differential expression of Kiss1 and Kiss1r in peripheral organs in DM2 females, as compared with healthy controls, and the profile differed from patterns reported earlier in males. DM2 in females was linked to the increased Kiss1 mRNA in the liver and increased Kiss1r mRNA in the liver and adipose tissue. However, Kiss1r promoter was hypermethylated in the liver, suggesting gene silencing. Indeed, the increase in DNA methylation of Kiss1r promoter was accompanied by a reduction in Kiss1r protein, implying epigenetic or translational gene repression. Our results deliver novel evidence for tissue-specific differences in Kiss1 and Kiss1r expression in peripheral organs in DM2 females and suggest DNA methylation as a player in regulation of the hepatic kisspeptin system in DM2.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".