Associations between brain-derived neurotrophic factor gene polymorphisms and cognitive disorder in depression
Bibliographic record
Abstract
Objective To explore the relationship between polymorphisms of brain-derived neurotrophic factor(BDNF) gene (rs6265 and rs12273539) and cognitive impairment in depressive disorder. Methods All participants including 73 depressed patients and 71 healthy controls were received clinical and cognitive assessments at admission, and then the depression group was divided into two groups by the score of Beijing version of the Montreal Cognitive Assessment (MoCA-BJ). One was depression with cognitive dysfunction group, and the other was depression without cognitive dysfunction group, with 36 and 37 cases respectively. The polymorphisms of BDNF gene was identified by PCR-RFLP. Results No significant difference for rs6265 gene types(χ2=5.18, P=0.27), A allele carries(χ2=4.28, P=0.12) and G allele carries(χ2=1.95, P=0.38) among the three groups.There was no significant difference for rs12273539 gene types, allele carries between patients without cognitive dysfunction and controls groups(P>0.05). There was much more C-allele carries(χ2=5.40, P=0.02)and less T-allele(χ2=6.06, P=0.01) in patients with cognitive disorder than those in health and it was different in rs12273539 gene types between the two groups(χ2=8.38, P=0.02). CC/CT/CT gene type performed different on attention function(P<0.01). Conclusion BDNF rs12273539(T/C) gene type has relationship with the onset of cognitive disorder in depressed patients, and there are more C-allele carries in depressive patients. The depression patients with CC gene type are worse on the attention function impairement. Key words: Depression; Cognitive dysfunction; Brain-derived neurotrophic factor; Single nucleotide polymorphism
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".