A targeted epigenetic clock for simultaneous assessment of biological aging and cancer-associated methylation drift

As a key tool for assessing aging, DNA methylation clocks are mostly constructed based on European and American populations and rely on the high-cost Infinium MethylationEPIC microarray. These factors limit their widespread application in the Chinese population. This study included two independent cohorts: the Fuyang cohort (n = 610, age range 2–89 years) for model development, and the Hefei cohort (n = 188, age range 15–86 years) for external validation. Using a multiplex PCR-based targeted capture sequencing technology, we examined 74 CpG sites located in seven age-associated genes, including ELOVL2, FHL2, C1orf132, KLF14, TRIM59, CCDC102B and PDE4C, to construct a DNA methylation-based age prediction model suitable for the Chinese population. The performance of our model was consistent with that reported in the literature for this field. In the Fuyang cohort, the training set achieved R2=0.95, MAE = 3.39 years; the test set achieved R2 = 0.93, MAE = 4.04 years. External validation yielded R2 = 0.89, MAE = 4.11 years. Compared with age-prediction models based on biochemical markers, our methylation clock demonstrated superior performance. Further analysis revealed non-linear aging rates and sex-specific differences. In addition, blood samples from cancer patients displayed DNA methylation patterns distinct from those associated with physiological aging, suggesting that they are associated with epigenetic alterations that lead to an overestimation of DNA methylation age. This study developed a cost-effective, targeted methylation clock for the full age spectrum in the Chinese population. Its strong response to both physiological aging and tumor status underscores its potential for large-scale aging assessment and for translational applications.