As a consequence a person’s phenotype is considered dynamic and resilience becomes a key parameter. Resilience is best evaluated during a system response, so challenge-tests will become more common in metabolomics research
[9•]. A classic example is the oral glucose tolerance test, but also high fat challenges, exercise, stress or mixed diets are used. Phenotype dynamics will differ between individuals, and concepts as homeostasis and allostasis can be considered (Figure 1). However, a precise (dynamic) description of the clinical phenotype Target Selective Inhibitor Library cell line is currently missing, which is of utmost importance to guide the discovery of diagnostic and mechanistic biochemical biomarkers. Another challenge is that mostly body fluids such as blood and urine are available, but most studied biochemical networks
are at the cellular level and not at the systems regulatory level. Therefore, we need to address cross-compartment communication and system organization more than only the pathways within cells. We expect that with the proper phenotyping/genotyping, metabolomics will play an important role in systems diagnosis, with an emphasis on following the changes over time of an individual , and on PLX-4720 chemical structure a somewhat longer term on integrated interventions and Immune system personalized wellness (Figure 2). The analytical strategy needed to be developed for achieving this is discussed below. In metabolomics the general tendency is to analyze as many low-molecular weight compounds (less than 2000 Da) as possible in a given biological sample at a certain point in time with the aim to obtain maximal biochemical information. The most recent version of the Human Metabolome Database contains 40 335 metabolite entries, of which a major part consists of lipids . This number does
not only include endogenous metabolites but also exogenous compounds originating from nutrients, microbiota, drugs and other sources. However, it is our opinion that this number is still an underestimation of the actual size of the human metabolome. Despite the fact that advanced analytical techniques like nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) hyphenated to gas chromatography (GC), liquid chromatography (LC) and/or capillary electrophoresis (CE) have become well-established tools for metabolomics studies [17, 18••, 19, 20 and 21], they still can only capture a part of the human metabolome and, therefore, provide inherently biased results. We expect that new developments or further refinements of analytical technologies, especially with regards to sensitivity, will significantly increase the coverage of metabolites.