Diagnostic Algorithm for Glycogenoses and Myoadenylate Deaminase Deficiency Based on Exercise Testing Parameters: A Prospective Study.

• Main Authors: Fabrice Rannou, Arnaud Uguen, Virginie Scotet, Cédric Le Maréchal, Odile Rigal, Pascale Marcorelles, Eric Gobin, Jean-Luc Carré, Fabien Zagnoli, Marie-Agnès Giroux-Metges
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2015-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC4514803?pdf=render

Our aim was to evaluate the accuracy of aerobic exercise testing to diagnose metabolic myopathies.From December 2008 to September 2012, all the consecutive patients that underwent both metabolic exercise testing and a muscle biopsy were prospectively enrolled. Subjects performed an incremental and maximal exercise testing on a cycle ergometer. Lactate, pyruvate, and ammonia concentrations were determined from venous blood samples drawn at rest, during exercise (50% predicted maximal power, peak exercise), and recovery (2, 5, 10, and 15 min). Biopsies from vastus lateralis or deltoid muscles were analysed using standard techniques (reference test). Myoadenylate deaminase (MAD) activity was determined using p-nitro blue tetrazolium staining in muscle cryostat sections. Glycogen storage was assessed using periodic acid-Schiff staining. The diagnostic accuracy of plasma metabolite levels to identify absent and decreased MAD activity was assessed using Receiver Operating Characteristic (ROC) curve analysis.The study involved 51 patients. Omitting patients with glycogenoses (n = 3), MAD staining was absent in 5, decreased in 6, and normal in 37 subjects. Lactate/pyruvate at the 10th minute of recovery provided the greatest area under the ROC curves (AUC, 0.893 ± 0.067) to differentiate Abnormal from Normal MAD activity. The lactate/rest ratio at the 10th minute of recovery from exercise displayed the best AUC (1.0) for discriminating between Decreased and Absent MAD activities. The resulting decision tree achieved a diagnostic accuracy of 86.3%.The present algorithm provides a non-invasive test to accurately predict absent and decreased MAD activity, facilitating the selection of patients for muscle biopsy and target appropriate histochemical analysis.