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Published on: September 29, 2014
Genetic and Clinical Spectrum of Limb-Girdle Muscular Dystrophies in Western Sicily
Nicasio Rini1, Antonino Lupica1, Paolo Alonge1
1Department of Biomedicine, Neuroscience, and Advanced Diagnostic (BIND), University of Palermo, 90129 Palermo, Italy.
Abstract:
Background and Objectives: Limb-girdle muscular dystrophies (LGMDs) are a group of muscular dystrophies characterized by predominantly proximal-muscle weakness, with a highly heterogeneous genetic etiology. Despite recent efforts, the epidemiology of LGMDs is still under-evaluated. However, a better understanding of the distribution and genetic characteristics of LGMDs is required to optimize the diagnostic process and to address future research. Therefore, the aim of the present study is to investigate and identify new pathogenic variants, to better characterize LGMDs in Sicily. Methods: We enrolled patients with genetic and clinical diagnosis of LGMD referred to our clinic between the years 2019 and 2025. A targeted next-generation-sequencing (NGS) panel was performed, based on the reported disease frequency. A retrospective analysis of the clinical, laboratory, electrophysiological, and histological features was performed. Results: A total of 28 LGMDs patients aged 56.6 years (47.2-60.5 IQR) were identified (16 males, 57%). A molecular diagnosis was achieved in 24 (85.7%) of patients, most commonly carrying mutations in CAPN3 (14 patients, 50%), followed by DYSF, LAMA2, ANO5, FKTN and TTN genes. Pathogenic variants in CAPN3 and LAMA2 were associated with earlier onset and longer disease duration, whereas ANO5 presented later with a milder course. Cardiac involvement was observed more frequently in patients with LAMA2 and FKTN mutations. Association between heterozygous mutations in the CAPN3 and DYSF, as well as between CAPN3 and DMD variants were reported. Discussion: The findings of this study provide valuable insights into the epidemiology of LGMDs in the Western Sicily, offering important contributions to genotype-phenotype correlations. Our analysis highlights the role of genetic diagnosis in achieving accurate classification of the disease and optimizing clinical management.
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