Transcriptional regulation of the 5-HT <sub>1A</sub> receptor: implications for mental illness
Bibliographic record
Abstract
The serotonin-1A (5-HT(1A)) receptor is an abundant post-synaptic 5-HT receptor (heteroreceptor) implicated in regulation of mood, emotion and stress responses and is the major somatodendritic autoreceptor that negatively regulates 5-HT neuronal activity. Based on animal models, an integrated model for opposing roles of pre- and post-synaptic 5-HT(1A) receptors in anxiety and depression phenotypes and response to antidepressants is proposed. Understanding differential transcriptional regulation of pre- versus post-synaptic 5-HT(1A) receptors could provide better tools for their selective regulation. This review examines the transcription factors that regulate brain region-specific basal and stress-induced expression of the 5-HT(1A) receptor gene (Htr1a). A functional polymorphism, rs6295 in the Htr1a promoter region, blocks the function of specific repressors Hes1, Hes5 and Deaf1, resulting in increased 5-HT(1A) autoreceptor expression in animal models and humans. Its association with altered 5-HT(1A) expression, depression, anxiety and antidepressant response are related to genotype frequency in different populations, sample homogeneity, disease outcome measures and severity. Preliminary evidence from gene × environment studies suggests the potential for synergistic interaction of stress-mediated repression of 5-HT(1A) heteroreceptors, and rs6295-induced upregulation of 5-HT(1A) autoreceptors. Targeted therapeutics to inhibit 5-HT(1A) autoreceptor expression and induce 5-HT(1A) heteroreceptor expression may ameliorate treatment of anxiety and major depression.
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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".