Regulatory role of miRNAs in polyamine gene expression in the prefrontal cortex of depressed suicide completers
Bibliographic record
Abstract
MicroRNAs (miRNAs) are small, non-coding RNA molecules that play an important role in the post-transcriptional regulation of mRNA. These molecules have been the subject of growing interest as they are believed to control the regulation of a large number of genes, including those expressed in the brain. Evidence suggests that miRNAs could be involved in the pathogenesis of neuropsychiatric disorders. Alterations in metabolic enzymes of the polyamine system have been reported to play a role in predisposition to suicidal behaviour. We have previously shown the expression of the polyamine genes SAT1 and SMOX to be down-regulated in the brains of suicide completers. In this study, we hypothesized that the dysregulation of these genes in depressed suicide completers could be influenced by miRNA post-transcriptional regulation. Using a stringent target prediction analysis, we identified several miRNAs that target the 3'UTR of SAT1 and SMOX. We profiled the expression of 10 miRNAs in the prefrontal cortex (BA44) of suicide completers (N = 15) and controls (N = 16) using qRT-PCR. We found that several miRNAs showed significant up-regulation in the prefrontal cortex of suicide completers compared to psychiatric healthy controls. Furthermore, we demonstrated a significant correlation between these miRNAs and the expression levels of both SAT1 and SMOX. Our results suggest a relationship between miRNAs and polyamine gene expression in the suicide brain, and postulate a mechanism for SAT1 and SMOX down-regulation by post-transcriptional activity of miRNAs.
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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".