A miR‐29a‐driven negative feedback loop regulates peripheral glucocorticoid receptor signaling
Bibliographic record
Abstract
The glucocorticoid receptor (GR) represents the crucial molecular mediator of key endocrine, glucocorticoid hormone-dependent regulatory circuits, including control of glucose, protein, and lipid homeostasis. Consequently, aberrant glucocorticoid signaling is linked to severe metabolic disorders, including insulin resistance, obesity, and hyperglycemia, all of which also appear upon chronic glucocorticoid therapy for the treatment of inflammatory conditions. Of note, long-term glucocorticoid exposure under these therapeutic conditions typically induces glucocorticoid resistance, requiring higher doses and consequently triggering more severe metabolic phenotypes. However, the molecular basis of acquired glucocorticoid resistance remains unknown. In a screen of differential microRNA expression during glucocorticoid-dependent adipogenic differentiation of human multipotent adipose stem cells, we identified microRNA 29a (miR-29a) as one of the most down-regulated transcripts. Overexpression of miR-29a impaired adipogenesis. We found that miR-29a represses GR in human adipogenesis by directly targeting its mRNA, and downstream analyses revealed that GR mediates most of miR-29a's anti-adipogenic effects. Conversely, miR-29a expression depends on GR activation, creating a novel miR-29-driven feedback loop. miR-29a and GR expression were inversely correlated both in murine adipose tissue and in adipose tissue samples obtained from human patients. In the latter, miR-29a levels were additionally strongly negatively correlated with body mass index and adipocyte size. Importantly, inhibition of miR-29 in mice partially rescued the down-regulation of GR during dexamethasone treatment. We discovered that, in addition to modulating GR function under physiologic conditions, pharmacologic glucocorticoid application in inflammatory disease also induced miR-29a expression, correlating with reduced GR levels. This effect was abolished in mice with impaired GR function. In summary, we uncovered a novel GR-miR-29a negative feedback loop conserved between mice and humans, in health and disease. For the first time, we elucidate a microRNA-related mechanism that might contribute to GR dysregulation and resistance in peripheral tissues.-Glantschnig, C., Koenen, M., Gil-Lozano, M., Karbiener, M., Pickrahn, I., Williams-Dautovich, J., Patel, R., Cummins, C. L., Giroud, M., Hartleben, G., Vogl, E., Blüher, M., Tuckermann, J., Uhlenhaut, H., Herzig, S., Scheideler, M. A miR-29a-driven negative feedback loop regulates peripheral glucocorticoid receptor signaling.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".