High-resolution, liquid state nuclear magnetic resonance (NMR) spectroscopy is a popular platform for metabolic profiling because the technique is nondestructive, quantitative, reproducible, and the spectra contain a wealth of biochemical information. Because of the large dynamic range of metabolite concentrations in biofluids, statistical analyses of one-dimensional (1D) proton NMR data tend to be biased toward selecting changes in more abundant metabolites. Although two-dimensional (2D) proton-proton experiments can alleviate spectral crowding, they have been mainly used for structural determination. In this study, 2D total correlation spectroscopy NMR was used to compare the global metabolic profiles of urine obtained from wild-type and Abcc6-knockout mice. The 2D data were compared to an improved 1D experiment in which signal contributions from macromolecules and the urea peak have been spectroscopically removed for more accurate quantitation of low-abundance metabolites. Although statistical models from both 1D and 2D data could differentiate samples acquired from the two groups of mice, only the 2D spectra allowed the characterization of statistically relevant changes in the low-abundance metabolites. While acquisition of the 2D data require more time, the data obtained resulted in a more meaningful and comprehensive metabolic profile, aided in metabolite identifications, and minimized ambiguities in peak assignments.