ABSTRACT
BACKGROUND: The objective of this study was to investigate cellular bioenergetics in primary skin fibroblasts derived from patients with amyotrophic lateral sclerosis (ALS) and to determine if they can be used as classifiers for patient stratification. METHODS: We assembled a collection of unprecedented size of fibroblasts from patients with sporadic ALS (sALS, n = 171), primary lateral sclerosis (PLS, n = 34), ALS/PLS with C9orf72 mutations (n = 13), and healthy controls (n = 91). In search for novel ALS classifiers, we performed extensive studies of fibroblast bioenergetics, including mitochondrial membrane potential, respiration, glycolysis, and ATP content. Next, we developed a machine learning approach to determine whether fibroblast bioenergetic features could be used to stratify patients. RESULTS: Compared to controls, sALS and PLS fibroblasts had higher average mitochondrial membrane potential, respiration, and glycolysis, suggesting that they were in a hypermetabolic state. Only membrane potential was elevated in C9Orf72 lines. ATP steady state levels did not correlate with respiration and glycolysis in sALS and PLS lines. Based on bioenergetic profiles, a support vector machine (SVM) was trained to classify sALS and PLS with 99% specificity and 70% sensitivity. CONCLUSIONS: sALS, PLS, and C9Orf72 fibroblasts share hypermetabolic features, while presenting differences of bioenergetics. The absence of correlation between energy metabolism activation and ATP levels in sALS and PLS fibroblasts suggests that in these cells hypermetabolism is a mechanism to adapt to energy dissipation. Results from SVM support the use of metabolic characteristics of ALS fibroblasts and multivariate analysis to develop classifiers for patient stratification.
Subject(s)
Amyotrophic Lateral Sclerosis/classification , Amyotrophic Lateral Sclerosis/metabolism , Fibroblasts/metabolism , Adult , Aged , Aged, 80 and over , Amyotrophic Lateral Sclerosis/pathology , Energy Metabolism , Female , Humans , Machine Learning , Male , Middle Aged , SkinABSTRACT
Energy metabolism could influence amyotrophic lateral sclerosis (ALS) and progressive lateral sclerosis (PLS) pathogenesis and the response to therapy. We developed a novel assay to simultaneously assess mitochondrial content and membrane potential in patients' skin fibroblasts. In ALS and PLS fibroblasts, membrane potential was increased and mitochondrial content decreased, relative to healthy controls. In ALS higher mitochondrial membrane potential correlated with age at diagnosis, and in PLS it correlated with disease severity. These unprecedented findings in ALS and PLS fibroblasts could shed new light onto disease pathogenesis and help in developing biomarkers to predict disease evolution and the individual response to therapy in motor neuron diseases.
