Strategies for data analyses in a high resolution 1H NMR based metabolomics study of a mouse model of Batten disease

Abstract

Using an NMR based approach, employing both solution state and high resolution magic angle spinning (HR MAS) H-1 NMR spectroscopy, in conjunction with an array of statistical methods, we report cerebral metabolic deficits in a mouse model of Batten disease (Cln3 null mutant mice). Batten disease is the most common progressive neurodegenerative disorder of childhood and is caused by mutations in the Cln3 gene. In particular, brain tissue from Cln3 mice was characterised by increased concentrations of glutamine, myo-inositol, scyllo-mositol, aspartate and lactate, alongside decreased concentrations of N-acetyl-L-aspartate (NAA), N-acetyl-L-glutamate (NAG), gamma-amino butyric acid (GABA), glutamate and creatine. Accompanying changes in lipid deposition were also detected in intact cortical tissue by HR MAS 1H NMR spectroscopy. To realise the true potential of metabolomic datasets necessitates a comprehensive analysis of the data, such that useful biological information can be extracted and used to generate hypotheses which can be further tested and refined. We found that using a combination of univariate and multivariate analyses, a maximal number of metabolic deficits were successfully identified. In particular the complementary nature of the statistical approaches allowed the definition of changes which were relative, absolute or simply a change in variance, allowing a greater understanding of the disease processes detected.