The Relationship between Body Composition, Fatty Acid Metabolism and Diet in Spinal Muscular Atrophy
Spinal muscular atrophy (SMA) is an autosomal recessive condition that results in pathological deficiency of the survival motor neuron (SMN) protein. SMA most frequently presents itself within the first few months of life and is characterized by progressive muscle weakness. As a neuromuscular condit...
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Published in: | Brain sciences Vol. 11; no. 2; p. 131 |
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Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
Switzerland
MDPI AG
20-01-2021
MDPI |
Subjects: | |
Online Access: | Get full text |
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Summary: | Spinal muscular atrophy (SMA) is an autosomal recessive condition that results in pathological deficiency of the survival motor neuron (SMN) protein. SMA most frequently presents itself within the first few months of life and is characterized by progressive muscle weakness. As a neuromuscular condition, it prominently affects spinal cord motor neurons and the skeletal muscle they innervate. However, over the past few decades, the SMA phenotype has expanded to include pathologies outside of the neuromuscular system. The current therapeutic SMA landscape is at a turning point, whereby a holistic multi-systemic approach to the understanding of disease pathophysiology is at the forefront of fundamental research and translational endeavours. In particular, there has recently been a renewed interest in body composition and metabolism in SMA patients, specifically that of fatty acids. Indeed, there is increasing evidence of aberrant fat distribution and fatty acid metabolism dysfunction in SMA patients and animal models. This review will explore fatty acid metabolic defects in SMA and discuss how dietary interventions could potentially be used to modulate and reduce the adverse health impacts of these perturbations in SMA patients. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-1 |
ISSN: | 2076-3425 2076-3425 |
DOI: | 10.3390/brainsci11020131 |