Single‐nucleus transcriptomics and deep learning uncover alternative polyadenylation dysregulation in frontotemporal lobar degeneration and amyotrophic lateral sclerosis
Bibliographic record
Abstract
BACKGROUND: Frontotemporal lobar degeneration (FTLD) is a leading cause of dementia, often co-occurring with amyotrophic lateral sclerosis (ALS). Despite shared genetic and pathological features, the cell type-specific molecular mechanisms underlying FTLD in ALS remain poorly understood. METHOD: Excitatory neurons exhibited synaptic dysfunction in ALS with and without FTLD, while inhibitory neurons were more affected in ALS without FTLD. Microglia displayed a disease-associated state in both groups, with ALS with FTLD showing elevated JAK-STAT signaling, indicative of a proinflammatory phenotype. We identified widespread shifts toward distal 3'UTR usage in ALS with and without FTLD, implicating APA dysregulation. APA-Net revealed coordinated RBP interactions, including TDP-43, HNRNPA1, and MBNL1, as key regulators of APA in ALS with and without FTLD. These findings highlight distinct and overlapping molecular signatures between the two disease subtypes. RESULT: We identified cell type-specific transcriptional dysregulation, with excitatory neurons showing synaptic dysfunction in both C9-ALS and sALS, while inhibitory neurons were more affected in sALS. Microglia exhibited a disease-associated state, with C9-ALS microglia showing elevated JAK-STAT signaling, indicative of a proinflammatory phenotype. We detected widespread shifts toward distal 3'UTR usage in ALS/FTLD, implicating APA dysregulation. APA-Net revealed coordinated RBP interactions, including TDP-43, HNRNPA1, and MBNL1, as key regulators of APA in ALS/FTLD. These findings highlight distinct and overlapping molecular signatures in C9-ALS and sALS, with implications for FTLD pathogenesis. CONCLUSION: This study provides a comprehensive single-nucleus transcriptomic atlas of the frontal cortex in ALS with and without FTLD, uncovering cell type-specific dysregulation of APA and RBP interactions. Our findings offer new insights into the molecular mechanisms driving FTLD and provide a resource for future therapeutic development.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".