Clinico-genetic spectrum of limb-girdle muscular weakness in Austria: A multicentre cohort study

Background and purpose Hereditary myopathies with limb-girdle muscular weakness (LGW) are a genetically heterogeneous group of disorders, in which molecular diagnosis remains challenging. Our aim was to present a detailed clinical and genetic characterization of a large cohort of patients with LGW. Methods This nationwide cohort study included patients with LGW suspected to be associated with hereditary myopathies. Parameters associated with specific genetic aetiologies were evaluated, and we further assessed how they predicted the detection of causative variants by conducting genetic analyses. Results Molecular diagnoses were identified in 62.0% (75/121) of the cohort, with a higher proportion of patients diagnosed by next-generation sequencing (NGS) than by single-gene testing (77.3% vs. 22.7% of solved cases). The median (interquartile range) time from onset to genetic diagnosis was 8.9 (3.7-19.9) and 17.8 (7.9-27.8) years for single-gene testing and NGS, respectively. The most common diagnoses were myopathies associated with variants in CAPN3 (n = 9), FKRP (n = 9), ANO5 (n = 8), DYSF (n = 8) and SGCA (n = 5), which together accounted for 32.2% of the cohort. Younger age at disease onset (p = 0.043), >10x elevated creatine kinase activity levels (p = 0.024) and myopathic electromyography findings (p = 0.007) were significantly associated with the detection of causative variants. Conclusions Our findings suggest that an earlier use of NGS in patients with LGW is needed to avoid long diagnostic delays. We further present parameters predictive of a molecular diagnosis that may help to select patients for genetic analyses, especially in centres with limited access to sequencing.

Automated summary

The study focused on hereditary myopathies with limb-girdle muscular weakness (LGW) and found that using next-generation sequencing (NGS) earlier in the diagnostic process is necessary to avoid long delays in diagnosis. Parameters predictive of a molecular diagnosis were identified, which can help select patients for genetic analyses, especially in centers with limited access to sequencing technology.