We report a chemical
isotope labeling (
CIL) liquid chromatography mass spectrometry (LC-MS) method generally applicable for tracking metabolomic changes from samples collected in an animal model for studying disease development and treatment. A rat model of surgically induced
osteoarthritis (OA) was used as an example to illustrate the workflow and technical performance. Experimental duplicate analyses of 234 plasma samples were carried out using dansylation labeling LC-MS targeting the
amine/
phenol submetabolome. These samples composed of 39 groups (6 rats per group) were collected at multiple time points with
sham operation, OA control group, and OA rats with treatment, separately, using
glucosamine/
Celecoxib and three traditional Chinese medicines (
Epimedii folium, Chuanxiong Rhizoma and
Bushen-Huoxue). In total, 3893 metabolites could be detected and 2923 of them were consistently detected in more than 50% of the runs. This high-coverage submetabolome dataset could be used to track OA progression and treatment. Many differentiating metabolites were found and 11 metabolites including
2-aminoadipic acid,
saccharopine and
GABA were selected as potential
biomarkers of OA progression and OA treatment. This study illustrates that
CIL LC-MS is a very useful technique for monitoring incremental metabolomic changes with high coverage and accuracy for studying
disease progression and treatment in animal models.