Cell Death and DiseaseNeurosciencePeer-reviewed journal article
Developmental demands contribute to early neuromuscular degeneration in CMT2D mice
James N. SleighiD, Aleksandra M. MechiD, Giampietro SchiavoiD
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Abstract
Dominantly inherited, missense mutations in the widely expressed housekeeping gene, GARS1, cause Charcot-Marie-Tooth type 2D (CMT2D), a peripheral neuropathy characterised by muscle weakness and wasting in limb extremities. Mice modelling CMT2D display early and selective neuromuscular junction (NMJ) pathology, epitomised by disturbed maturation and neurotransmission, leading to denervation. Indeed, the NMJ disruption has been reported in several different muscles; however, a systematic comparison of neuromuscular synapses from distinct body locations has yet to be performed. We therefore analysed NMJ development and degeneration across five different wholemount muscles to identify key synaptic features contributing to the distinct pattern of neurodegeneration in CMT2D mice. Denervation was found to occur along a distal-to-proximal gradient, providing a cellular explanation for the greater weakness observed in mutant Gars hindlimbs compared to forelimbs. Nonetheless, muscles from similar locations and innervated by axons of equivalent length showed significant differences in neuropathology, suggestive of additional factors impacting on site-specific neuromuscular degeneration. Defective NMJ development preceded and associated with degeneration, but was not linked to a delay of wild-type NMJ maturation processes. Correlation analyses indicate that muscle fibre type nor synaptic architecture explain the differential denervation of CMT2D NMJs, rather it is the extent of post-natal synaptic growth that predisposes to neurodegeneration. Together, this work improves our understanding of the mechanisms driving synaptic vulnerability in CMT2D and hints at pertinent pathogenic pathways.
- organism: mouse
- research focus: cell type annotation
- research focus: differential expression
- research focus: spatial domain detection
- approach: statistical model
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