Reduced Abundance and Subverted Functions of Proteins in Prion-Like Diseases: Gained Functions Fascinate but Lost Functions Affect Aetiology
Bibliographic record
Abstract
Prions have served as pathfinders that reveal many aspects of proteostasis in neurons. The recent realization that several prominent neurodegenerative diseases spread via a prion-like mechanism illuminates new possibilities for diagnostics and therapeutics. Thus, key proteins in Alzheimer Disease and Amyotrophic lateral sclerosis (ALS), including amyloid-β precursor protein, Tau and superoxide dismutase 1 (SOD1), spread to adjacent cells in their misfolded aggregated forms and exhibit template-directed misfolding to induce further misfolding, disruptions to proteostasis and toxicity. Here we invert this comparison to ask what these prion-like diseases can teach us about the broad prion disease class, especially regarding the loss of these key proteins’ function(s) as they misfold and aggregate. We also consider whether functional amyloids might reveal a role for subverted protein function in neurodegenerative disease. Our synthesis identifies SOD1 as an exemplar of protein functions being lost during prion-like protein misfolding, because SOD1 is inherently unstable and loses function in its misfolded disease-associated form. This has under-appreciated parallels amongst the canonical prion diseases, wherein the normally folded prion protein, PrPC, is reduced in abundance in fatal familial insomnia patients and during the preclinical phase in animal models, apparently via proteostatic mechanisms. Thus while template-directed misfolding and infectious properties represent gain-of-function that fascinates proteostasis researchers and defines (is required for) the prion(-like) diseases, loss and subversion of the functions attributed to hallmark proteins in neurodegenerative disease needs to be integrated into design towards effective therapeutics. We propose experiments to uniquely test these ideas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".