sPLA2-IIA modifies progranulin deficiency phenotypes in mouse models
Bibliographic record
Abstract
BACKGROUND: Haploinsufficiency of the progranulin (PGRN) protein is a leading cause of frontotemporal lobar degeneration (FTLD). Mouse models have been developed to study PGRN functions. However, PGRN deficiency in the commonly used C57BL/6 mouse strain background leads to very mild phenotypes, and pathways regulating PGRN deficiency phenotypes remain to be elucidated. METHODS: We generated PGRN-deficient mice in the FVB/N background and compared PGRN deficiency phenotypes between C57BL/6 and FVB/N backgrounds via immunostaining, western blot, RNA-seq, and proteomics approaches. We demonstrated a novel pathway in modifying PGRN deficiency phenotypes using inhibitor treatment and AAV-mediated overexpression in mouse models. RESULTS: We report that PGRN loss in the FVB/N mouse strain results in earlier onset and stronger FTLD-related and lysosome-related phenotypes. We found that PGRN interacts with sPLA2-IIA, a member of the secreted phospholipase A2 (sPLA2) family member and a key regulator of inflammation, that is expressed in FVB/N but not C57BL/6 background. sPLA2-IIA inhibition rescues PGRN deficiency phenotypes, while sPLA2-IIA overexpression drives enhanced gliosis and lipofuscin accumulation in PGRN-deficient mice. Additionally, RNA-seq and proteomics analysis revealed that mitochondrial pathways are upregulated in the PGRN-deficient C57BL/6 mice but not in the FVB/N mice. CONCLUSIONS: Our studies establish a better mouse model for FTLD-GRN and uncover novel pathways modifying PGRN deficiency phenotypes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".