We report a new quantitative metabolome profiling technique based on differential (12)C-/(13)C-isotope dansylation labeling of metabolites, fast liquid chromatography (LC) separation and electrospray ionization Fourier-transform ion cyclotron resonance mass spectrometry (ESI-FTICR MS) detection. An isotope reagent, (13)C-dansyl chloride, can be readily synthesized. This reagent, along with (12)C-dansyl chloride, provides a simple and robust means of labeling metabolites containing primary amine, secondary amine, or phenolic hydroxyl group(s). It is shown that dansylation labeling offers 1-3 orders of magnitude ESI signal enhancement over the underivatized counterparts. Dansylation alters the chromatographic behaviors of polar and ionic metabolites normally not retainable on a reversed phase (RP) column to an extent that they can be retained and separated by RPLC with high efficiency. There is no isotopic effect on RPLC separation of the differential isotope labeled metabolites, and (12)C-/(13)C-labeled isoforms of metabolites are coeluted and detected by MS for precise and accurate quantification and confident metabolite identification. It is demonstrated that, in the analysis of 20 amino acids, a linear response of over 2 orders of magnitude is achieved for relative metabolite quantification with an average relative standard deviation (RSD) of about 5.3% from replicate experiments. A dansylation standard compound library consisting of 121 known amines and phenols has been constructed and is proven to be useful for absolute metabolite quantification and MS-based metabolite identification in biological samples. As an example, the absolute concentrations of 93 metabolites, ranging from 30 nM to 2510 microM, can be determined from a pooled sample of human urines collected in 5 consecutive days labeled with (12)C-dansylation and spiked with the 121 (13)C-dansylated standards. Relative concentration variations of these metabolites in individual urine samples can also be monitored by mixing the (13)C-dansylated pooled urine sample with the (12)C-dansylated individual sample. With a 12 min fast LC separation combined with FTICR MS, 672 metabolites were detected in a human urine sample with each metabolite peak having a signal-to-noise ratio of greater than 20; the identities of most of the metabolites remain to be determined. This work illustrates that dansylation labeling and fast LC/FTICR MS can be a powerful technique for quantitative profiling of at least 672 metabolites in urine samples in 12 min.