15. Monitoring Metabolic Disease States Using a Combined Flow Injection LC-MSMS Assay
Mon 12:12 PM - PosterSplash Track 2
Sascha Dammeier
Cornelia Roehring, Ralf Bogumil, Mattias Bair, Klaus M. Weinberger, Sascha Dammeier.

Biocrates Life Sciences AG, 6020 Innsbruck, Austria
Due to the almost epidemic growth rates of diabetes mellitus during the last decade, metabolic diseases draw full attention of the pharmaceutical industry, medical research initiatives and public health organizations. Moreover, it is anticipated that the percentage of worldwide deaths caused by diabetes mellitus will increase to 3.1% in the next 20 years, thereby ranking as the sixth most common cause of death in the world and becoming a severe widespread disease. Hence, means for prevention, treatment and diagnosis need to be improved urgently. Since most of the current therapies primarily alleviate the symptoms more in-depth research is necessary to investigate and understand the underlying mechanisms of the disease.

Apart from many inborn disorders, the onset and progression of metabolic diseases, e.g. the metabolic syndrom, is often vague but differentially characterized by stages that are normally defined by a multitude of different physiological and biochemical parameters. To improve the efficiency and throughput of medical and clinical studies about metabolic diseases it is vital to have quick and robust multiparametric tests available.
We have conceived and developed a reliable mass spectrometric assay system that detects and quantifies more than 170 key metabolites like acylcarnitines, biogenic amines, hexoses, glycerophospholipids and amino acids. Most of those metabolites are well described in the progression of the metabolic syndrome and can also be used to differentially characterize secondary disorders like diabetic nephropathy, fatty acid metabolism disorders and others.

The assay system consists of a straight-forward sample extraction system for either human plasma and serum or urine. Up to 75 samples can be processed in parallel. The extracts, to which internal standards have been added during the preparation process, were subsequently analyzed by direct flow injection mass spectrometry followed by a reverse-phase HPLC MSMS run. Rapid data analysis was performed using the commercially available MetIQ software, which has integrated a new module that immediately calculates and displays biochemically relevant ratio and sum parameters using the collected metabolite concentrations.

Using this new assay we were able to comprehensively characterize a study set of samples from healthy and hypertriglyceridaemic individuals (75 in summa) with respect to their metabolic disease state.