This piece of research work was motivated by a genome-wide epigenetic study, where epigenetic changes from pre- to post-adolescence was of interest due to their potential connection to allergic diseases. We focused on one type of epigenetic assessment, DNA methylation at a certain number of CpG sites (i.e., measurements for a certain number of variables). To efficiently and effectively characterize DNA methylation at different CpG sites, we developed a Bayesian two-stage clustering method to 1) determine whether DNA methylation at a CpG site was stable over time, and 2) assign each unstable CpG site into a specific cluster based on temporal trend of DNA methylation at that site. Simulations were used to demonstrate and assess the developed method. We then applied the approach to a real data set composed of DNA methylation at 2,000 CpG sites measured at 10 and 18 years, respectively, for each of 325 subjects.