Plasma-based microRNA biomarkers for depression in Romanian patients: preliminary findings
Bibliographic record
Abstract
Introduction Depressive disorders are one of the most disabling mental illnesses with a significant impact on society. In Romania the mean annual total costs per depression patient are EUR 5553, a much higher figure than the mean annual total costs per patient ranged worldwide. Even though their roles in depression have not been elucidated, a plethora of potential biomarkers in multiple body fluids for the early diagnosis of depression has been suggested. Blood circulating microRNAs (miRNAs) are potential biomarkers for several human diseases, including psychiatric disorders. Different studies have shown that micro RNAs are involved in a series of pathophysiological processes and could be useful markers for diagnosis and prognosis of depression. Objectives This preliminary case-control study was designed to identify putative blood circulating miRNAs associated with the diagnosis of depression in Romanian patients. Methods In this study, 20 patients with depression and 24 non-depressed controls were enrolled. All the individuals have been interviewed and screened using the following scales: the Hamilton Anxiety Scale (HAM-A), the Becks Depression Inventory (BDI) and the Perceived Stress Scale (PSS). The expression of 179 miRNAs in plasma have been evaluated by qRT- PCR. The difference in the expression of miRNAs between the two groups, as well as the correlations with the scores of the scales have been analyzed. Results A panel of 28 miRNAs was identified as differentially expressed between patients and controls. Only miRNAs showing a -2>FC>2.0 and p<0.05 have been considered significant. Seven miRNAs (miR-143-3p, miR-331-3p, let-7f-5, miR-502-3p, miR-145-5p, miR-7-1-3p, miR- 29a-3p) were found up-regulated in the depression group, while 21 miRNAs (miR-885-5p, miR- 425-3p, miR-32-5p, miR-23b-3p, miR-590-5p, miR-30a-5p, miR-132-3p, miR-376a-3p, miR-223-5p, miR-133b, miR-142-5p, miR-92b-3p, miR-140-3p, miR-16-2-3p, miR-28-3p, miR-27a-3p, miR-15b-3p, miR-106b-3p, miR-877-5p, miR-30e-3p, miR-140-5p) showed a down-regulation in the group of patients compared to the controls. Some of the significant correlations between miRNA expression and the scale scores are reported: a positive correlation between let-7f-5 and miR-7-1-3p with the BDI score (p=0.003 r=0.526, and p=0.008 r=0.477, respectively) and a negative correlation between miR-425-3p with BDI (p=0.002 r=-0.502) were found. Conclusions The results reported in this communication represent preliminary findings. Due to the nature and heterogeneity of depression, the number of patients and controls in the two cohorts will be enlarged to correlate these miRNAs with other patient features. Disclosure of Interest None Declared
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".