Molecular Behavior of α-Synuclein Is Associated with Membrane Transport, Lipid Metabolism, and Ubiquitin–Proteasome Pathways in Lewy Body Disease
Bibliographic record
Abstract
Lewy body diseases (LBDs) feature α-synuclein (α-syn)-containing Lewy bodies, with misfolded α-syn potentially propagating as seeds. Using a seeding amplification assay, we previously reported distinct α-syn seeding in LBD cases based on the area under seeding curves. This study revealed that LBD cases showing different α-syn seeding kinetics have distinct proteomics profiles, emphasizing disruptions in mitochondria and lipid metabolism in high-seeder cases. Though the mechanisms underlying LBD development are intricate, the factors influencing α-syn seeding activity remain elusive. To address this and complement our previous findings, we conducted targeted transcriptome analyses in the substantia nigra using the nanoString nCounter assay together with histopathological evaluations in high (n = 4) and low (n = 3) nigral α-syn seeders. Neuropathological findings (particularly the substantia nigra) were consistent between these groups and were characterized by neocortical LBD associated with Alzheimer's disease neuropathologic change. Among the 1811 genes assessed, we identified the top 20 upregulated and downregulated genes and pathways in α-syn high seeders compared with low seeders. Notably, alterations were observed in genes and pathways related to transmembrane transporters, lipid metabolism, and the ubiquitin-proteasome system in the high α-syn seeders. In conclusion, our findings suggest that the molecular behavior of α-syn is the driving force in the neurodegenerative process affecting the substantia nigra through these identified pathways. These insights highlight their potential as therapeutic targets for attenuating LBD progression.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".