학술논문

Blood-derived biomarkers correlate with clinical progression in Duchenne muscular dystrophy
Document Type
Source
JOURNAL OF NEUROMUSCULAR DISEASES. 7(3):231-246
Subject
Affinity-based proteomics
protein biomarkers
Duchenne muscular dystrophy
disease progression
serum and plasma
Language
English
ISSN
2214-3599
2214-3602
Abstract
Background: Duchenne Muscular Dystrophy is a severe, incurable disorder caused by mutations in the dystrophin gene. The disease is characterized by decreased muscle function, impaired muscle regeneration and increased inflammation. In a clinical context, muscle deterioration, is evaluated using physical tests and analysis of muscle biopsies, which fail to accurately monitor the disease progression. Objectives: This study aims to confirm and asses the value of blood protein biomarkers as disease progression markers using one of the largest longitudinal collection of samples. Methods: A total of 560 samples, both serum and plasma, collected at three clinical sites are analyzed using a suspension bead array platform to assess 118 proteins targeted by 250 antibodies in microliter amount of samples. Results: Nine proteins are confirmed as disease progression biomarkers in both plasma and serum. Abundance of these biomarkers decreases as the disease progresses but follows different trajectories. While carbonic anhydrase 3, microtubule associated protein 4 and collagen type I alpha 1 chain decline rather constantly over time, myosin light chain 3, electron transfer flavoprotein A, troponin T, malate dehydrogenase 2, lactate dehydrogenase B and nestin plateaus in early teens. Electron transfer flavoprotein A, correlates with the outcome of 6-minutes-walking-test whereas malate dehydrogenase 2 together with myosin light chain 3, carbonic anhydrase 3 and nestin correlate with respiratory capacity. Conclusions: Nine biomarkers have been identified that correlate with disease milestones, functional tests and respiratory capacity. Together these biomarkers recapitulate different stages of the disorder that, if validated can improve disease progression monitoring.