4.4 Article

Prediction of death in the SMNΔ7 mouse model of spinal muscular atrophy: Insight into disease stage and progression

期刊

JOURNAL OF NEUROSCIENCE METHODS
卷 209, 期 2, 页码 259-268

出版社

ELSEVIER
DOI: 10.1016/j.jneumeth.2012.06.020

关键词

Tissue lactate level; Respiratory rate; Prediction of death; Dichloroacetate; Neonate oral gavages; Motor function; Modeling body weight; Moribund

资金

  1. PsychoGenics Inc.
  2. Spinal Muscular Atrophy Foundation

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Proximal Spinal Muscular Atrophy (SMA) is a debilitating neuromuscular disease and a leading inherited genetic cause of infant death. To date, there is no effective treatment for SMA. The SMN Delta 7 neonatal mouse model of SMA recapitulates key features of the severe form of SMA and remains a valuable tool in preclinical drug discovery. At any particular postnatal age (P), the disease progression in the SMN Delta 7 mouse model is not universal, as some animals die as early as the day of birth and others live for up to three weeks. Identification of the disease stage in SMN Delta 7 mice, independent of age, would aid in the design and interpretation of preclinical studies. We developed a score (CD score), derived from body weight analysis, that allowed us to gain insight into the disease progression and predict death. Respiratory complication is a leading cause of mortality in the SMA patient and this phenotype has been reported in severe mouse models of SMA. We subsequently measured muscle and brain tissue lactate levels, an indirect measure of hypoxia, in SMN Delta 7 mice at P10 and correlated these measures to respiratory rate. SMN Delta 7 mice showed a significant increase in tissue lactate and a decrease in respiratory rate in comparison to control. The CD score correlates linearly with tissue lactate level and respiratory rate. The finding of lactate buildup in the SMN Delta 7 mouse and the correlation with a score that is predictive of disease stage provide an interesting insight into the disease pathophysiology and a possible biomarker for SMA. (c) 2012 Elsevier B.V. All rights reserved.

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