Back

Unraveling the spatial landscape of Dystrophinopathies: a transcriptomic approach to Becker and Duchenne muscular dystrophies

Heezen, L. G. M.; Mao, Q.; Nicolau, S.; Novella Rausell, C.; van der Weerd, J. M. L.; Kueckelhaus, J.; Gokul Nath, R.; Diaz- Manera, J.; Kan, H.; Niks, E. H.; van Putten, M.; Aartsma-Rus, A.; Flanigan, K. M.; Mahfouz, A.; Spitali, P.

2025-05-31 neurology
10.1101/2025.05.30.25328395 medRxiv
Show abstract

Dystrophinopathies are caused by pathogenic variants in the DMD gene resulting in partial (Becker) or complete loss (Duchenne) of dystrophin. Becker (BMD) and Duchenne muscular dystrophy (DMD), are characterized by progressive muscle wasting, fatty replacement, fibrosis, and loss of function. To study histopathological changes, we used spatial transcriptomics to profile skeletal muscle biopsies of BMD, DMD patients and healthy controls (N = 4 per group). We estimated the proportion of cell types and their spatial localization across samples applying a deconvolution strategy using single-nuclei RNA-sequencing data. We identified genes enriched in fat patches and cell types such as fibroadipogenic progenitor cells (FAPs) in areas of active pathology. Using expression data of ligand receptor pairs, we highlight cell-cell communications leading to fibrotic and adipogenic lesions. Finally, analysis of gene expression gradients in areas of adjacent muscle and fat, allowed the identification of genes associated with muscle areas committed to become fat. Significance statementThis study investigates the cellular and molecular changes that occur in muscles affected by Becker and Duchenne muscular dystrophy (BMD and DMD). These diseases are caused by mutations in the DMD gene, leading to muscle degeneration and the replacement of muscle tissue with fibrotic and fatty tissue causative for an early death. By using spatial transcriptomics, the researchers analyzed muscle biopsies from BMD, DMD patients, and healthy controls. They identified specific genes and cell types, such as fibroadipogenic progenitor cells, that are involved in disease progression. The study also revealed how different cells communicate with each other to drive muscle degeneration and fat accumulation. These findings provide new insights into the mechanisms of disease and potential targets for future therapies.

Published in The Journal of Pathology (predicted rank #2) · training set

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Journal of Cachexia, Sarcopenia and Muscle
33 papers in training set
Top 0.1%
18.8%
The Journal of Pathology · published here
26 papers in training set
Top 0.1%
15.3%
3
eLife
5828 papers in training set
Top 12%
8.0%
4
Neuropathology and Applied Neurobiology
15 papers in training set
Top 0.1%
5.6%
5
Communications Biology
993 papers in training set
Top 2%
4.9%
50% of probability mass above
6
Nature Communications
5641 papers in training set
Top 30%
4.4%
7
The FASEB Journal
194 papers in training set
Top 1%
2.8%
8
Journal of Translational Medicine
57 papers in training set
Top 0.7%
1.8%
9
iScience
1154 papers in training set
Top 16%
1.8%
10
Acta Neuropathologica Communications
89 papers in training set
Top 1%
1.8%
11
Cells
249 papers in training set
Top 3%
1.8%
12
Scientific Reports
3612 papers in training set
Top 55%
1.7%
13
Journal of Cell Science
393 papers in training set
Top 3%
1.5%
14
eBioMedicine
183 papers in training set
Top 3%
1.5%
15
Acta Neuropathologica
58 papers in training set
Top 1%
1.4%
16
JCI Insight
277 papers in training set
Top 5%
1.4%
17
Human Molecular Genetics
141 papers in training set
Top 2%
1.1%
18
Cell Reports
1498 papers in training set
Top 23%
1.1%
19
Advanced Science
286 papers in training set
Top 6%
1.1%
20
Muscle & Nerve
10 papers in training set
Top 0.2%
1.1%
21
Frontiers in Immunology
638 papers in training set
Top 8%
1.1%
22
Science Advances
1243 papers in training set
Top 27%
1.1%
23
Science Translational Medicine
127 papers in training set
Top 3%
1.0%
24
Disease Models & Mechanisms
119 papers in training set
Top 2%
0.9%
25
The Journal of Physiology
150 papers in training set
Top 2%
0.9%
26
American Journal of Physiology-Cell Physiology
39 papers in training set
Top 0.9%
0.6%
27
Nucleic Acids Research
1281 papers in training set
Top 14%
0.6%
28
Annals of the Rheumatic Diseases
36 papers in training set
Top 0.5%
0.6%
29
Frontiers in Cell and Developmental Biology
233 papers in training set
Top 6%
0.6%
30
Frontiers in Neuroscience
256 papers in training set
Top 7%
0.6%