Degeneration of dopaminergic circuitry influences depressive symptoms in Lewy body disorders
Bibliographic record
Abstract
AIMS: Depression is commonly observed even in prodromal stages of Lewy body disorders (LBD), and is associated with cognitive impairment and a faster rate of cognitive decline. Given the role of dopamine in the development of movement disorders, but also in motivation and reward, we investigated neurodegenerative pathology in dopaminergic circuitry in Parkinson's disease (PD), PD with dementia (PDD) and dementia with Lewy bodies (DLB) patients in relation to depressive symptoms. METHODS: α-synuclein, hyperphosphorylated tau and amyloid-beta pathology was assessed in 17 DLB, 14 PDD and 8 PD cases within striatal and midbrain subregions, with neuronal cell density assessed in substantia nigra and ventral tegmental area. Additionally, we used a structural equation modeling (SEM) approach to investigate the extent to which brain connectivity might influence the deposition of pathological proteins within dopaminergic pathways. RESULTS: A significantly higher α-synuclein burden was observed in the substantia nigra (P = 0.006), ventral tegmental area (P = 0.011) and nucleus accumbens (P = 0.031) in LBD patients with depression. Significant negative correlations were observed between cell density in substantia nigra with Lewy body (LB) Braak stage (P = 0.013), whereas cell density in ventral tegmental area showed negative correlations with LB Braak stage (P = 0.026) and neurofibrillary tangle Braak stage (P = 0.007). CONCLUSIONS: Dopaminergic α-synuclein pathology appears to drive depression. Selective targeting of dopaminergic pathways may therefore provide symptomatic relief for depressive symptoms in LBD patients.
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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 | 0.001 |
| 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) | 0.001 | 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".