MiR-34a rs2666433 and cognitive function in major depressive disorder: a clinical correlation analysis
Bibliographic record
Abstract
Background Genetic factors play a crucial role in the development of major depressive disorder (MDD).Objectives This study aimed to investigate the association between the microRNA (miR)-34a rs266643 polymorphism and MDD, as well as its impact on cognitive function.Materials and methods Clinical data and blood samples were collected from 302 MDD patients and 306 healthy controls who met the predefined inclusion and exclusion criteria. The severity of MDD in patients was assessed using the Hamilton Rating Scale for Depression (HRSD). Cognitive function in MDD patients was evaluated using the Mini-Mental State Examination (MMSE), Stroop Color-Word Test (Stroop-C and Stroop-CW), and Montreal Cognitive Assessment (MoCA). Gene typing was performed using the Sanger sequencing method, while the relative expression level of miR-34a was quantified by RT-qPCR.Results The MDD group exhibited a significantly higher miR-34a expression fold change compared to the control group (p < 0.001). Among the genotypes, the AA genotype demonstrated the highest expression, followed by GA, with both being significantly greater than GG. The expression of miR-34a was positively correlated with HRSD, Stroop-C, and Stroop-CW scores but negatively correlated with MMSE and MoCA scores (p < 0.001). Carrying the A allele (OR = 1.468, p = 0.002) or the AA genotype (OR = 2.382, p = 0.001) was associated with an increased risk of MDD. Furthermore, patients with the AA genotype exhibited significantly poorer cognitive function compared to other genotypes.Conclusion The gene polymorphism of miR-34a rs2666433 was significantly associated with the severity of MDD as well as cognitive function.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".