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American Academy of Neurology (AAN), Neurology, 4(60), p. 665-673, 2003

DOI: 10.1212/01.wnl.0000046585.81304.bc

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Clinical course correlates poorly with muscle pathology in nemaline myopathy

This paper is available in a repository.
This paper is available in a repository.

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Abstract

Objective: To report pathologic findings in 124 Australian and North American cases of primary nemaline myopathy.Methods: Results of 164 muscle biopsies from 124 Australian and North American patients with primary nemaline myopathy were reviewed, including biopsies from 19 patients with nemaline myopathy due to α-actin (ACTA1) mutations and three with mutations in α-tropomyosinSLOW (TPM3). For each biopsy rod number per fiber, percentage of fibers with rods, fiber-type distribution of rods, and presence or absence of intranuclear rods were documented.Results: Rods were present in all skeletal muscles and diagnosis was possible at all ages. Most biopsies contained nemaline bodies in more than 50% of fibers, although rods were seen only on electron microscopy in 10 patients. Rod numbers and localization correlated poorly with clinical severity. Frequent findings included internal nuclei and increased fiber size variation, type 1 fiber predominance and atrophy, and altered expression of fiber type specific proteins. Marked sarcomeric disruption, increased glycogen deposition, and intranuclear rods were associated with more severe clinical phenotypes. Serial biopsies showed progressive fiber size variation and increasing numbers of rods with time. Pathologic findings varied widely in families with multiple affected members.Conclusions: Very numerous nemaline bodies, glycogen accumulation, and marked sarcomeric disruption were common in nemaline myopathy associated with mutations in skeletal α-actin. Nemaline myopathy due to mutations in α-tropomyosinSLOW was characterized by preferential rod formation in, and atrophy of, type 1 fibers. Light microscopic features of nemaline myopathy correlate poorly with disease course. Electron microscopy may correlate better with disease severity and genotype.