Microglial lysosome dysfunction contributes to white matter pathology and TDP-43 proteinopathy in GRN-associated FTD
Bibliographic record
Abstract
Loss-of-function mutations in the progranulin gene (GRN), which encodes progranulin (PGRN), are a major cause of frontotemporal dementia (FTD). GRN-associated FTD is characterized by TDP-43 inclusions and neuroinflammation, but how PGRN loss causes disease remains elusive. We show that Grn knockout (KO) mice have increased microgliosis in white matter and an accumulation of myelin debris in microglial lysosomes in the same regions. Accumulation of myelin debris is also observed in white matter of patients with GRN-associated FTD. In addition, our findings also suggest that PGRN insufficiency in microglia leads to impaired lysosomal-mediated clearance of myelin debris. Finally, Grn KO mice that are deficient in cathepsin D (Ctsd), a key lysosomal enzyme, have augmented myelin debris and increased neuronal TDP-43 pathology. Together, our data strongly imply that PGRN loss affects microglial activation and lysosomal function, resulting in the accumulation of myelin debris and contributing to TDP-43 pathology.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".