Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca.

Inefficient muscle long-chain fatty acid (LCFA) combustion is associated with insulin resistance, but molecular links between mitochondrial fat catabolism and insulin action remain controversial. We hypothesized that plasma acylcarnitine profiling would identify distinct metabolite patterns reflective of muscle fat catabolism when comparing individuals bearing a missense G304A uncoupling protein 3 (UCP3 g/a) polymorphism to controls, because UCP3 is predominantly expressed in skeletal muscle and g/a individuals have reduced whole-body fat oxidation. MS analyses of 42 carnitine moieties in plasma samples from fasting type 2 diabetics (n = 44) and nondiabetics (n = 12) with or without the UCP3 g/a polymorphism (n = 28/genotype: 22 diabetic, 6 nondiabetic/genotype) were conducted. Contrary to our hypothesis, genotype had a negligible impact on plasma metabolite patterns. However, a comparison of nondiabetics vs. type 2 diabetics revealed a striking increase in the concentrations of fatty acylcarnitines reflective of incomplete LCFA beta-oxidation in the latter (i.e. summed C10- to C14-carnitine concentrations were approximately 300% of controls; P = 0.004). Across all volunteers (n = 56), acetylcarnitine rose and propionylcarnitine decreased with increasing hemoglobin A1c (r = 0.544, P < 0.0001; and r = -0.308, P < 0.05, respectively) and with increasing total plasma acylcarnitine concentration. In proof-of-concept studies, we made the novel observation that C12-C14 acylcarnitines significantly stimulated nuclear factor kappa-B activity (up to 200% of controls) in RAW264.7 cells. These results are consistent with the working hypothesis that inefficient tissue LCFA beta-oxidation, due in part to a relatively low tricarboxylic acid cycle capacity, increases tissue accumulation of acetyl-CoA and generates chain-shortened acylcarnitine molecules that activate proinflammatory pathways implicated in insulin resistance.