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Limb-girdle muscular dystrophies (LGMDs) are genetically heterogeneous and the diagnostic work-up including conventional genetic testing using Sanger sequencing remains complex and often unsatisfactory. We performed targeted sequencing of 23 LGMD-related genes and 15 genes in which alterations result in a similar phenotype in 58 patients with genetically unclassified LGMDs. A genetic diagnosis was possible in 19 of 58 patients (33 %). LGMD2A was the most common form, followed by LGMD2L and LGMD2I. In two patients, pathogenic mutations were identified in genes that are not classified as LGMD genes (glycogen branching enzyme and valosin-containing protein). Thus, a focused next-generation sequencing-based gene panel is a rather satisfactory tool for the diagnosis in unclassified LGMDs.

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BACKGROUND: Extensive genetic screening results in the identification of thousands of rare variants that are difficult to interpret. Because of its sheer size, rare variants in the titin gene (TTN) are detected frequently in any individual. Unambiguous interpretation of molecular findings is almost impossible in many patients with myopathies or cardiomyopathies. OBJECTIVE: To refine the current classification framework for TTN-associated skeletal muscle disorders and standardize the interpretation of TTN variants. METHODS: We used the guidelines issued by the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) to re-analyze TTN genetic findings from our patient cohort. RESULTS: We identified in the classification guidelines three rules that are not applicable to titin-related skeletal muscle disorders; six rules that require disease-/gene-specific adjustments and four rules requiring quantitative thresholds for a proper use. In three cases, the rule strength need to be modified. CONCLUSIONS:We suggest adjustments are made to the guidelines. We provide frequency thresholds to facilitate filtering of candidate causative variants and guidance for the use and interpretation of functional data and co-segregation evidence. We expect that the variant classification framework for TTN-related skeletal muscle disorders will be further improved along with a better understanding of these diseases.

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