Back

Rewiring Fibroblast-Muscle Axis Drives Progressive Pathology in Bethlem Myopathy

Shivaraman, S.; Gilquin, L.; Sohm, F.; Fareh, R.; Legeai-Mallet, L.; Forlino, A.; Dambroise, E.; Bretaud, S.; Ruggiero, F.

2026-05-18 developmental biology
10.64898/2026.05.14.725126 bioRxiv
Show abstract

Collagen VI-related myopathies, including Bethlem myopathy (BM), are progressive muscle disorders, but the mechanisms driving age-dependent disease progression remain poorly understood. Here, we used a zebrafish BM model carrying an exon-skipping mutation that generates a shorter collagen VI 1 chain and disrupts supramolecular assembly, recapitulating key features of the human disease. We further demonstrated that this model reproduces disease progression, with worsening muscle wasting, increased myofiber size variability, and age-associated skeletal deformities consistent with secondary consequences of muscle dysfunction rather than intrinsic bone defects. Single-nucleus RNA sequencing of trunk skeletal muscle revealed an early shift in cellular composition, with reduced myonuclei and increased fibroblast abundance, indicative of disease-associated aging. Myonuclei activated stress and quality control pathways, including autophagy and mitophagy, along with metabolic rewiring. In contrast, fibroblasts displayed early translational activation followed by progressive proteostatic and endoplasmic reticulum stress. At later stages, fibroblasts adopted a pro-fibrotic state, driving extracellular matrix remodeling and enhanced muscle-fibroblast communication. Consistently, analyses at the protein level confirmed early intracellular retention of the mutant protein, along with increased extracellular matrix deposition and fibrotic tissue formation in BM muscle. Among the three tested drugs targeting ER-stress and protein degradation, only TUDCA significantly ameliorated collagen VI deposition in the extracellular space in larvae. These findings identify fibroblasts as key drivers of disease progression and potential therapeutic targets.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Nature Communications
4913 papers in training set
Top 4%
21.9%
2
Aging Cell
144 papers in training set
Top 0.5%
14.3%
3
Developmental Cell
168 papers in training set
Top 1%
14.0%
50% of probability mass above
4
Cell Reports
1338 papers in training set
Top 12%
4.2%
5
eLife
5422 papers in training set
Top 27%
3.5%
6
Science
429 papers in training set
Top 11%
2.8%
7
EMBO Molecular Medicine
85 papers in training set
Top 0.9%
2.5%
8
Nature Aging
51 papers in training set
Top 0.7%
2.5%
9
Science Translational Medicine
111 papers in training set
Top 2%
2.4%
10
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 27%
2.3%
11
Molecular Therapy
71 papers in training set
Top 1%
1.8%
12
Advanced Science
249 papers in training set
Top 12%
1.6%
13
Science Advances
1098 papers in training set
Top 19%
1.6%
14
Cell Death & Differentiation
48 papers in training set
Top 0.3%
1.6%
15
Cell Research
49 papers in training set
Top 1%
1.6%
16
Communications Biology
886 papers in training set
Top 11%
1.4%
17
Cell Reports Medicine
140 papers in training set
Top 6%
0.9%
18
EMBO reports
136 papers in training set
Top 5%
0.9%
19
Cell Stem Cell
57 papers in training set
Top 2%
0.9%
20
PLOS Genetics
756 papers in training set
Top 13%
0.9%
21
Human Molecular Genetics
130 papers in training set
Top 3%
0.8%
22
Nature
575 papers in training set
Top 15%
0.8%
23
Nature Cell Biology
99 papers in training set
Top 5%
0.7%
24
Nature Metabolism
56 papers in training set
Top 3%
0.7%
25
Development
440 papers in training set
Top 4%
0.7%
26
Cell
370 papers in training set
Top 18%
0.7%
27
Journal of Clinical Investigation
164 papers in training set
Top 8%
0.6%
28
JCI Insight
241 papers in training set
Top 9%
0.6%