The association of single-nucleotide polymorphism rs6265 of the brain-derived neurotrophic factor gene with clinical features in Parkinson’s disease
Bibliographic record
Abstract
Objective. To evaluate the frequency and severity of various clinical symptoms of Parkinson’s disease (PD) depending on the BDNF rs6265 polymorphism. Material and methods. The study included 533 patients with PD. The stage of PD was assessed using the Hoehn and Yahr scale (1967), motor symptoms were evaluated with MDS-UPDRS. Assessment of non-motor symptoms (NMS) in PD was conducted using the Beck Depression Inventory II (BDI-II); the Hospital Anxiety and Depression Scale (HADS); the Apathy Scale; the Montreal Cognitive Assessment (MoCA test); the Questionnaire for Impulsive-Compulsive Disorders in PD -Rating Scale (QUIP-RS). Genotyping of the BDNF variant (rs6265) was performed using real-time PCR with TaqMan probes. Results. Most PD patients have a combination of NMS increasing as the disease progresses and is determined by molecular-genetic individual characteristics. There are significant differences in the severity of motor symptoms and NMS: individuals with the AA genotype showed significantly pronounced motor symptoms (p<0.0001); emotional-affective symptoms (p<0.0001); cognitive and impulsive behavioral disorders (p<0.0001). Conclusion. The rs6265 BDNF allele A is associated with a wide range of NMS, increasing the risk of their development in patients with PD, thus playing the important role in the etiopathogenesis of this pathology.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 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".