Aging and aging related diseases, characterized by gradual deterioration of functional capabilities and ultimate death, have been a fi eld attracting intense interest over centuries. Epigenetics is the study of hereditable phenotypic changes that regulate genetic information without DNA sequence alterations including DNA methylation, histone modifications, chromatin remodeling and non-coding RNAs. Interestingly, a growing body of evidence supported a strong correlation between aging and epigenetic regulation. It was suggested that epigenetic mechanism played a critical role in aging and aging related diseases and was even perceived as a candidate hallmark of aging (Lopez-Otin et al., 2013). In particular, alterations in DNA methylation pattern have been reported to be linked with chronological aging process in human studies. For instance, a longitudinal study revealed a global loss of DNA methylation particularly in the repetitive elements (such as Alu) during aging (Bollati et al., 2009). Subsequent study further discovered that DNA was hypermethylated located near tissue-specifi c CpG islands; whereas hypomethylation was significantly associated with none CpG-island region during aging by looking at the methylation profi les (Christensen et al., 2009). A more detailed study on methylome of CD4 + T cells in newborns and centenarians confi rmed Christensen et al.'s fi nding and added that there was a less DNA methylation content and a reduced correlation of neighboring CpG methylation status in centenarians relative to newborns (Heyn et al., 2012). Moreover, Gentilini et al.'s study indicated a delay of global methylation decrease in the centenarians' offspring in comparison with those of non-lived parents. More interestingly, those two groups also exhibited different methylation profiles in genes involved in RNA/DNA biosynthesis, metabolism, and signal transmission (Gentilini et al., 2012). The above evidence suggests that changes to DNA methylation landscape were associated with aging. Nevertheless, systematic description and quantitative measurement of DNA methylome as well as how it affects aging are yet-to-be revealed.Hannum et al. made noteworthy progress in addressing these questions. In order to fi nd methylation markers related to aging, the group built a quantitative model among 485,577 CpG markers to describe the aging rate of individuals. They found 15% of these markers were related to aging, and then they compared their result with Heyn et al.'s study and screened 53,670 sites. To pick out more relevant aging-related markers, the group applied predictive model of Elastic Net (Zou and Hastie, 2005) along with bootstrap approaches, and identifi ed 71 methylation markers. Then, the group built their aging model with these 71 markers and employed various tissue samples to validate it. The authors specifi cally noted that nearly all these markers are located nearby or within genes that have known functions in aging or aging-related diseases. The group made a thorough analysis of these markers on both ge...