Back

The muscle atrophic phenotype of MuSK myasthenia gravis: Insights from a preclinical rat model

Jakobsgaard, J. E.; Thomasen, P. B.; Wang, J.; Kristiansen, T. H.; Johnsen, P.; Riisager, A.; Huus, N.; Broch-Lips, M.; Skov, M. B.; Palmfeldt, J.; Pedersen, T. H.; Vissing, K.

2026-03-16 molecular biology
10.64898/2026.03.13.709755 bioRxiv
Show abstract

Myasthenia gravis with muscle-specific kinase antibodies (MuSK-MG) is an autoimmune disorder marked by neuromuscular junction (NMJ) disruption and selective muscle atrophy, yet its intrinsic myocellular mechanisms remain unclear. Using a rat model generated by active immunization with the N-terminal MuSK60 peptide, we characterized muscle pathology, NMJ morphology, and whole-muscle proteome remodeling across anatomically distinct skeletal muscles. Anti-MuSK rats developed seropositivity, body-mass loss, fragmented and denervated NMJs, and pronounced atrophy restricted to slow-twitch/type I fibers, particularly in the soleus muscle. Quantitative proteomics identified extensive muscle-specific alterations, most prominent in soleus, with fewer in diaphragm and sternohyoideus. Gene set enrichment analysis revealed coordinated downregulation of mitochondrial, ribosomal, and myosin-complex proteins in soleus, partial mitochondrial involvement in diaphragm, and compensatory upregulation of translational and proteasomal pathways in diaphragm. Correlation analysis linked soleus mass loss to elevated abundance of ubiquitin-proteasome and calcium-handling proteins, implicating proteolytic and bioenergetic stress mechanisms. The consistent upregulation of NCAM1 and MUSTN1 suggests generalized myocellular responses to MuSK dysfunction. Together, these data demonstrate that MuSK autoimmunity elicits fiber-type-selective atrophy and profound proteome remodeling beyond NMJ impairment, highlighting disrupted mitochondrial and translational homeostasis as central features of the MuSK-MG muscle phenotype.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.