Multi-platform investigation of the metabolome in a leptin receptor defective murine model of type 2 diabetes.

We describe a multi-platform ((1)H NMR, LC-MS, microarray) investigation of metabolic disturbances associated with the leptin receptor defective (db/db) mouse model of type 2 diabetes using novel assignment methodologies. For the first time, several urinary metabolites were found to be associated with diabetes and/or diabetes progression and confirmed in both NMR and LC-MS datasets. The confirmed metabolites were trimethylamine-n-oxide (TMAO), creatine, carnitine, and phenylalanine. TMAO and phenylalanine were both elevated in db/db mice and decreased in these mice with age. Levels of both creatine and carnitine increase in diabetic mice with age and creatine was also significantly decreased in db/db mice. Additionally, many metabolic markers were found by either NMR or LC-MS, but could not be found in both, due to instrumental limitations. This indicates that the combined use of NMR and LC-MS instrumentation provides complementary information that would be otherwise unattainable. Pathway analyses of urinary metabolites and liver, muscle, and adipose tissue transcripts from the db/db model were also performed to identify altered biochemical processes in the diabetic mice. Metabolite and liver transcript levels associated with the TCA cycle and steroid processes were altered in db/db mice. In addition, gene expression in muscle and liver associated with fatty acid processing was altered in the diabetic mice and similar evidence was observed in the LC-MS data. Our findings highlight the importance of a number of processes known to be associated with diabetes and reveal tissue specific responses to the condition. When studying metabolic disorders such as diabetes, multiple platform integrated profiling of metabolite alterations in biofluids can provide important insights into the processes underlying the disease.