Decoding the muscle transcriptome of patients with late-onset Pompe disease reveals markers of disease progression
Bibliographic record
Abstract
Late-onset Pompe disease (LOPD) is a rare genetic disorder caused by the deficiency of acid alpha-glucosidase leading to progressive cellular dysfunction owing to the accumulation of glycogen in the lysosome. The mechanism of relentless muscle damage (a classic manifestation of the disease) has been studied extensively by analysing the whole-muscle tissue; however, little, if anything, is known about transcriptional heterogeneity among nuclei within the multinucleated skeletal muscle cells. This is the first report of application of single-nucleus RNA sequencing to uncover changes in the gene expression profile in muscle biopsies from eight patients with LOPD and four muscle samples from age- and sex-matched healthy controls. We matched these changes with histological findings using GeoMx spatial transcriptomics to compare the transcriptome of control myofibres from healthy individuals with non-vacuolated (histologically unaffected) and vacuolated (histologically affected) myofibres of LODP patients. We observed an increase in the proportion of slow and regenerative muscle fibres and macrophages in LOPD muscles. The expression of the genes involved in glycolysis was reduced, whereas the expression of the genes involved in the metabolism of lipids and amino acids was increased in non-vacuolated fibres, indicating early metabolic abnormalities. Additionally, we detected upregulation of autophagy genes and downregulation of the genes involved in ribosomal and mitochondrial function leading to defective oxidative phosphorylation. Upregulation of genes associated with inflammation, apoptosis and muscle regeneration was observed only in vacuolated fibres. Notably, enzyme replacement therapy (the only available therapy for the disease) showed a tendency to restore dysregulated metabolism, particularly within slow fibres. A combination of single-nucleus RNA sequencing and spatial transcriptomics revealed the landscape of the normal and diseased muscle and highlighted the early abnormalities associated with disease progression. Thus, the application of these two new cutting-edge technologies provided insight into the molecular pathophysiology of muscle damage in LOPD and identified potential avenues for therapeutic intervention.
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 | 0.000 |
| 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) | 0.000 | 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".