Glycogen synthase GYS1 overactivation contributes to glycogen insolubility and malto-oligoglucan-associated neurodegenerative disease
Bibliographic record
Abstract
Polyglucosans are glycogen molecules with overlong chains, which are hyperphosphorylated in the neurodegenerative Lafora disease (LD). Brain polyglucosan bodies (PBs) cause fatal neurodegenerative diseases including Lafora disease and adult polyglucosan body disease (ABPD), for which treatments, biomarkers, and good understanding of their pathogenesis are currently missing. Mutations in the genes for the phosphatase laforin or the E3 ubiquitin ligase malin can cause LD. By depleting PTG, an activator of the glycogen chain-elongating enzyme glycogen synthase (GYS1), in laforin- and malin-deficient LD mice, we show that abnormal glycogen chain lengths and not hyperphosphorylation underlie polyglucosan formation, and that polyglucosan bodies induce neuroinflammation. We provide evidence indicating that a small pool of overactive GYS1 contributes to glycogen insolubility in LD and APBD. In contrast to previous findings, metabolomics experiments using in situ-fixed brains reveal only modest metabolic changes in laforin-deficient mice. These changes are not replicated in malin-deficient or APBD mice, and are not normalized in rescued LD mice. Finally, we identify a pool of metabolically volatile malto-oligoglucans as a polyglucosan body- and neuroinflammation-associated brain energy source, and promising candidate biomarkers for LD and APBD, including malto-oligoglucans and the neurodegeneration marker CHI3L1/YKL40.
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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) | 0.001 | 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 | 0.001 |
| 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".