Abstract
Metabolomics as a field has gained attention due to its potential for biomarker discovery, namely because it directly reflects disease phenotype and is the downstream effect of posttranslational modifications. The field provides a “top-down,” integrated view of biochemistry in complex organisms, as opposed to the traditional “bottom-up” approach that aims to analyze networks of interactions between genes, proteins and metabolites. It also allows for the detection of thousands of endogenous metabolites in various clinical biospecimens in a high-throughput manner, including tissue and biofluids such as blood and urine. Of note, because biological fluid samples can be collected relatively easily, the time-dependent fluctuations of metabolites can be readily studied in detail.
In this chapter, we aim to provide an overview of (1) analytical methods that are currently employed in the field, and (2) study design concepts that should be considered prior to conducting high-throughput metabolomics studies. While widely applicable, the concepts presented here are namely applicable to high-throughput untargeted studies that aim to search for metabolite biomarkers that are associated with a particular human disease.
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Haznadar, M., Mathé, E.A. (2017). Experimental and Study Design Considerations for Uncovering Oncometabolites. In: Kasid, U., Clarke, R. (eds) Cancer Gene Networks. Methods in Molecular Biology, vol 1513. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6539-7_4
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DOI: https://doi.org/10.1007/978-1-4939-6539-7_4
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