Publication Details

AFRICAN RESEARCH NEXUS

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medicine

Early onset collagen VI myopathies: Genetic and clinical correlations

Annals of Neurology, Volume 68, No. 4, Year 2010

Objective Mutations in the genes encoding the extracellular matrix protein collagen VI (ColVI) cause a spectrum of disorders with variable inheritance including Ullrich congenital muscular dystrophy, Bethlem myopathy, and intermediate phenotypes. We extensively characterized, at the clinical, cellular, and molecular levels, 49 patients with onset in the first 2 years of life to investigate genotype-phenotype correlations. Methods Patients were classified into 3 groups: early-severe (18%), moderate-progressive (53%), and mild (29%). ColVI secretion was analyzed in patient-derived skin fibroblasts. Chain-specific transcript levels were quantified by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), and mutation identification was performed by sequencing of complementary DNA. Results ColVI secretion was altered in all fibroblast cultures studied. We identified 56 mutations, mostly novel and private. Dominant de novo mutations were detected in 61% of the cases. Importantly, mutations causing premature termination codons (PTCs) or in-frame insertions strikingly destabilized the corresponding transcripts. Homozygous PTC-causing mutations in the triple helix domains led to the most severe phenotypes (ambulation never achieved), whereas dominant de novo in-frame exon skipping and glycine missense mutations were identified in patients of the moderate-progressive group (loss of ambulation). Interpretation This work emphasizes that the diagnosis of early onset ColVI myopathies is arduous and time-consuming, and demonstrates that quantitative RT-PCR is a helpful tool for the identification of some mutation-bearing genes. Moreover, the clinical classification proposed allowed genotype-phenotype relationships to be explored, and may be useful in the design of future clinical trials. © 2010 American Neurological Association.

Statistics
Citations: 115
Authors: 38
Affiliations: 23
Identifiers
Research Areas
Cancer
Disability
Genetics And Genomics
Health System And Policy
Maternal And Child Health
Study Approach
Quantitative