Regional and cellular iron deposition patterns predict clinical subtypes of multiple system atrophy
Bibliographic record
Abstract
Abstract Background Multiple system atrophy (MSA) is a primary oligodendroglial synucleinopathy, characterized by elevated iron burden in early-affected subcortical nuclei. Although neurotoxic effects of brain iron deposition and its reciprocal relationship with α-synuclein pathology have been demonstrated, the exact role of iron dysregulation in MSA pathogenesis is unknown. In this regard, advancing the understanding of iron dysregulation at the cellular level is critical, especially in relation to α-synuclein cytopathology. Methods We performed the first cell type (α-synuclein-affected and -unaffected neurons, astroglia, oligodendrocytes, and microglia)-specific evaluation of MSA iron deposition in the globus pallidus (GP), putamen, and the substantia nigra (SN), using a combination of iron staining with immunolabelling on human post-mortem MSA brains. We evaluated selective regional and cellular vulnerability patterns to iron deposition distinctly in MSA-parkinsonian (MSA-P) and cerebellar (MSA-C) subtypes and explored possible underlying molecular pathways by mRNA expression analysis of key iron- and the closely related oxygen-homeostatic genes. Results MSA-P and MSA-C showed a distinct pattern of regional iron burden across the subcortical nuclei. We identified microglia as the major cell type accumulating iron in these regions of MSA brains, which was more distinct in MSA-P. MSA-C showed a more heterogenous cellular iron accumulation, in which astroglia showed greater or similar accumulation of iron. Notably, iron deposition was found outside the cellular bodies in the same regions and cellular iron burden minimally correlated with α-synuclein cytopathology. Gene expression analysis revealed dysregulation of oxygen, rather than of cellular iron, homeostatic genes. Importantly, hierarchal cluster analysis revealed pattern of cellular vulnerability to iron accumulation, rather than of α-synuclein pathology load in the subtype-related systems, to distinguish MSA subtypes. Conclusions We identified distinct regional, and for the first time, cellular distribution of subcortical iron deposition in MSA-P and MSA-C, and revealed cellular vulnerability pattern to iron deposition as a novel neuropathological characteristic that predicts MSA subtypes, distinctly from α-synuclein pathology. These findings support the role of iron dysregulation as an early effector of disease pathology in MSA. Our findings suggesting distinct iron-related pathomechanisms in MSA subtypes inform current efforts in iron chelation therapies at the disease and cellular-specific levels.
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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) | 0.002 | 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".