Mineralocorticoid and glucocorticoid receptor heterodimers mediate cortisol-induced behavioural changes via modulation of glutamatergic signalling
Bibliographic record
Abstract
Stress is both an underlying and exacerbating factor in a wide range of neuropsychiatric disorders, from anxiety to major depressive disorder. Such stress-related behaviours are thought to be modulated, in part, by the receptors for the stress hormone cortisol. These receptors, namely the mineralocorticoid receptor (MR) and glucocorticoid receptor (GR), are highly conserved transcription factors that bind as homodimers to response elements in target genes. Although it has been shown that MR and GR can act as heterodimers as well, little is known regarding the physiological relevance of MR/GR heterodimerization. Here we tested the hypothesis that MR/GR heterodimerization is essential to mediate the behavioural effects of cortisol. For this purpose, we established mutant MRs and GRs that could selectively homo- or heterodimerize and expressed these receptors in zebrafish from an MR/GR double knockout line. Subsequent behavioural analysis revealed that cortisol induced hyperactivity, but only under conditions of MR/GR heterodimerization. To investigate the molecular targets of these heterodimers, we next performed RNA-sequencing, which showed that MR/GR heterodimers regulated the expression of genes involved in glutamatergic signalling. This was confirmed by CRISPR/Cas9-mediated gene editing of a response element in the gene encoding the metabotropic glutamate receptor 3, which abolished the cortisol-induced hyperactivity. Furthermore, pharmacological treatments showed that besides glutamatergic signalling, GABAergic and serotonergic signalling are involved as well. Taken together, this study establishes the physiological relevance of MR/GR heterodimerization, which appears to play a central role in eliciting behavioural alterations upon stress, by altering the activity of crucial neurotransmitter systems.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".