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Updated: Oct 5, 2026

Isometric and Eccentric Force Generation Assessment of Skeletal Muscles Isolated from Murine Models of Muscular Dystrophies
Published on: January 31, 2013
Integrated Approach to Diagnosing Limb-Girdle Muscular Dystrophies in Resource-Limited Settings
Hammad Yousaf1, Lubaba Bintee Khalid1, Affan Ahmed2
1Department of Biological and Biomedical Sciences The Aga Khan University Karachi Sindh Pakistan aku.edu.
Abstract:
Limb-girdle muscular dystrophies (LGMD) are a genetically heterogeneous group of neuromuscular disorders characterized by overlapping clinical features, including progressive muscle weakness and wasting, elevated creatine kinase (CK) levels, and motor and skeletal abnormalities. Due to phenotypic overlap and variable severity, clinical diagnosis alone is often unreliable. Incorporation of genetic investigations to aid diagnosis/differential diagnosis has accelerated the diagnostic process but remains largely limited to developed countries. Here, we employed genetic testing as a first-tier approach to simplify the diagnostic journey in a resource-limited setting, combined with preliminary functional analyses to identify the underlying genetic cause. Our cohort included 46 affected individuals (31 males, 15 females) from 29 families with a mean age of 23.59 ± 11.87 years and a mean age at onset of 14.8 ± 9.2 years. All individuals presented with progressive muscle weakness, elevated CK levels, movement difficulties, and gait abnormalities. Genetic testing identified pathogenic/likely pathogenic variants in CAPN3 (8 families), DYSF (15 families), LAMA2 (4 families), and SGCA (1 family), whereas a variant of uncertain significance was identified in COL12A1 (1 family). Preliminary functional investigations in patient-derived fibroblasts demonstrated that the COL12A1: p.(Val1051Leu) identified in Family 1 results in reduced mRNA and protein abundance. Overall, 25 unique variants were identified, including 17 novel variants. This study highlights the utility of integrating genetic and functional approaches to facilitate accurate diagnosis in low- and middle-income settings.
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