SFPQ and Tau: critical factors contributing to rapid progression of Alzheimer’s disease
Bibliographic record
Abstract
Dysfunctional RNA-binding proteins (RBPs) have been implicated in several neurodegenerative disorders. Recently, this paradigm of RBPs has been extended to pathophysiology of Alzheimer's disease (AD). Here, we identified disease subtype specific variations in the RNA-binding proteome (RBPome) of sporadic AD (spAD), rapidly progressive AD (rpAD), and sporadic Creutzfeldt Jakob disease (sCJD), as well as control cases using RNA pull-down assay in combination with proteomics. We show that one of these identified proteins, splicing factor proline and glutamine rich (SFPQ), is downregulated in the post-mortem brains of rapidly progressive AD patients, sCJD patients and 3xTg mice brain at terminal stage of the disease. In contrast, the expression of SFPQ was elevated at early stage of the disease in the 3xTg mice, and in vitro after oxidative stress stimuli. Strikingly, in rpAD patients' brains SFPQ showed a significant dislocation from the nucleus and cytoplasmic colocalization with TIA-1. Furthermore, in rpAD brain lesions, SFPQ and p-tau showed extranuclear colocalization. Of note, association between SFPQ and tau-oligomers in rpAD brains suggests a possible role of SFPQ in oligomerization and subsequent misfolding of tau protein. In line with the findings from the human brain, our in vitro study showed that SFPQ is recruited into TIA-1-positive stress granules (SGs) after oxidative stress induction, and colocalizes with tau/p-tau in these granules, providing a possible mechanism of SFPQ dislocation through pathological SGs. Furthermore, the expression of human tau in vitro induced significant downregulation of SFPQ, suggesting a causal role of tau in the downregulation of SFPQ. The findings from the current study indicate that the dysregulation and dislocation of SFPQ, the subsequent DNA-related anomalies and aberrant dynamics of SGs in association with pathological tau represents a critical pathway which contributes to rapid progression of AD.
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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 | 0.000 | 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 | 0.000 |
| 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".