MicroRNA-137 regulates a glucocorticoid receptor–dependent signalling network: implications for the etiology of schizophrenia
Bibliographic record
Abstract
BACKGROUND: Schizophrenia is a highly heritable neurodevelopmental disorder. A genetic variant of microRNA-137 (miR-137) has yielded significant genome-wide association with schizophrenia, suggesting that this miRNA plays a key role in its etiology. Therefore, a molecular network of interacting miR-137 targets may provide insights into the biological processes underlying schizophrenia. METHODS: We first used bioinformatics tools to obtain and analyze predicted human and mouse miR-137 targets. We then determined miR-137 levels in rat barrel cortex after environmental enrichment (EE), a neuronal plasticity model that induces upregulation of several predicted miR-137 targets. Subsequently, expression changes of these predicted targets were examined through loss of miR-137 function experiments in rat cortical neurons. Finally, we conducted bioinformatics and literature analyses to examine the targets that were upregulated upon miR-137 downregulation. RESULTS: Predicted human and mouse miR-137 targets were enriched in neuronal processes, such as axon guidance, neuritogenesis and neurotransmission. The miR-137 levels were significantly downregulated after EE, and we identified 5 novel miR-137 targets through loss of miR-137 function experiments. These targets fit into a glucocorticoid receptor-dependent signalling network that also includes 3 known miR-137 targets with genome-wide significant association with schizophrenia. LIMITATIONS: The bioinformatics analyses involved predicted human and mouse miR-137 targets owing to lack of information on predicted rat miR-137 targets, whereas follow-up experiments were performed with rats. Furthermore, indirect effects in the loss of miR-137 function experiments cannot be excluded. CONCLUSION: We have identified a miR-137-regulated protein network that contributes to our understanding of the molecular basis of schizophrenia and provides clues for future research into psychopharmacological treatments for schizophrenia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".