The development of global metabolic profiling and the study of the metabolomics are particularly important in human disease where small molecules such as endogenous metabolites or lipids play fundamental signaling roles. The metabolic profile is perturbed in a characteristic fashion in disease, and this shift in position can be readily visualized and modeled using chemometric techniques. The metabolic profile of biofluids or tissues shows changes of their composition in response to disease-induced stress due to the system's attempt to maintain homeostasis. Profiling strategies aim to comprehensively measure and quantify such biomarkers in a fast, cost-effective and clinically informative manner. Techniques tend to be applied in an unbiased fashion, with advanced statistical methods allowing for identification of signature profiles in particular cohorts. In this manner, metabolomics profiling has the potential to identify new pathophysiological pathways, and thus therapeutic targets, as well as assist in improved risk-stratification and personalized medicine.

Analytical platforms, including NMR and Mass spectrometry, were used to generate a molecular fingerprint of biofluid or tissue samples, and then pattern recognition technique was applied to identify molecular signatures associated with the specific diseases or drug efficiency. Several metabolites that differentiate disease samples from the control were thoroughly characterized and the metabolic changes in human and animal model were investigated using analytical platforms. Spectral data were applied to targeted profiling and spectral binning method, and then multivariate statistical data analysis was used to examine in detail the modulation of small molecule candidate biomarkers. The metabolomic profiling process generates accurate metabolite concentration data, and provides data that can be used to help understand metabolic differences between healthy and disease or drug treated models. Such metabolic signatures could provide diagnostic markers for a disease state or biomarkers for drug response phenotypes, and mechanistic information on cellular perturbations and pathways associated with diseases.