Targeted Therapies for Metabolic Myopathies Related to Glycogen Storage and Lipid Metabolism: a Systematic Review and Steps Towards a ‘Treatabolome’

Abstract

Background: Metabolic myopathies are a heterogenous group of muscle diseases typically characterized by exercise intolerance, myalgia and progressive muscle weakness. Effective treatments for some of these diseases are available, but while our understanding of the pathogenesis of metabolic myopathies related to glycogen storage, lipid metabolism and β-oxidation is well established, evidence linking treatments with the precise causative genetic defect is lacking. Objective: The objective of this study was to collate all published evidence on pharmacological therapies for the aforementioned metabolic myopathies and link this to the genetic mutation in a format amenable to databasing for further computational use in line with the principles of the “treatabolome” project. Methods: A systematic literature review was conducted to retrieve all levels of evidence examining the therapeutic efficacy of pharmacological treatments on metabolic myopathies related to glycogen storage and lipid metabolism. A key inclusion criterion was the availability of the genetic variant of the treated patients in order to link treatment outcome with the genetic defect. Results: Of the 1,085 articles initially identified, 268 full-text articles were assessed for eligibility, of which 87 were carried over into the final data extraction. The most studied metabolic myopathies were Pompe disease (45 articles), multiple acyl-CoA dehydrogenase deficiency related to mutations in the ETFDH gene (15 articles) and systemic primary carnitine deficiency (8 articles). The most studied therapeutic management strategies for these diseases were enzyme replacement therapy, riboflavin, and carnitine supplementation, respectively. Conclusions: This systematic review provides evidence for treatments of metabolic myopathies linked with the genetic defect in a computationally accessible format suitable for databasing in the treatabolome system, which will enable clinicians to acquire evidence on appropriate therapeutic options for their patient at the time of diagnosis.