A Pattern Recognition Approach to Myopathy

OBJECTIVEThis article reviews the clinical elements, muscle involvement patterns, and diagnostic tools that can facilitate the diagnosis of muscle diseases, highlighting their heterogeneity and diagnostic challenges.LATEST DEVELOPMENTSIncreased access to genetic testing, the development of disease biomarkers, and research are expanding the spectrum of inherited and acquired muscle diseases. Muscle disease can exist in isolation or be part of a multisystem proteinopathy affecting other tissues outside skeletal muscle. Pathogenic variants in the same gene can lead to myopathy or peripheral neuropathy, in isolation or combination. This poses diagnostic challenges, especially when the myopathy manifests with distal weakness, mimicking a peripheral neuropathy. Therefore, diagnosis requires a rigorous characterization of the patient's phenotype and correlation with genetic findings. The ever-growing number of gene-specific and pathogenic variant-specific therapies, as well as drugs targeting pathogenic mechanisms of immune-mediated muscle diseases, underscore the importance of providing patients with a specific diagnosis to accelerate care and prevent potential complications. Artificial intelligence technologies in the neuromuscular field are further optimizing the diagnostic process and care of patients with muscle disease.ESSENTIAL POINTSClinical assessment and the integration of clinical and laboratory findings remain key elements for the diagnosis and treatment of most muscle diseases. While genetic testing has replaced muscle biopsy in the diagnosis of many genetic myopathies, muscle biopsy remains crucial for the diagnosis of many acquired muscle diseases and is a tool to investigate the pathogenicity of genetic variants of uncertain significance and clarify disease mechanisms. All efforts should be made to provide patients with the diagnosis of their specific muscle disease as this has a huge impact on patient care and prognosis.