摘要：SummaryEpigenetic aging clocks are computational models that use DNA methylation sites to predict age. Since cheek swabs are non-invasive and painless, collecting DNA from buccal tissue is highly desirable. Here, we review 11 existing clocks that have been applied to buccal tissue. Two of these were exclusively trained on adults and, while moderately accurate, have not been used to capture health-relevant differences in epigenetic age. Using 130 common CpGs utilized by two or more existing buccal clocks, we generate a proof-of-concept predictor in an adult methylomic dataset. In addition to accurately estimating age (r = 0.95 and mean absolute error = 3.88 years), this clock predicted that Down syndrome subjects were significantly older relative to controls. A literature and database review of CpG-associated genes identified numerous genes (e.g.,CLOCK,ELOVL2, andVGF) and molecules (e.g., alpha-linolenic acid, glycine, and spermidine) reported to influence lifespan and/or age-related disease in model organisms.Graphical abstractDisplay OmittedHighlights•130 CpGs have been used by two or more aging clocks applied to human buccal tissue•Common CpG genes are linked to the adaptive immune system and telomere maintenance•Common CpGs can be used to build a novel, proof-of-concept epigenetic aging clock•Several compounds associated with common CpG genes regulate lifespan in animalsEpigenetics; Chronobiology; Bioinformatics; Artificial intelligence
