According to a new study published in Aging Cell in August 2016, methylation changes in skin DNA can be used to accurately predict age. Aging is a complex phenomenon, and scientists can now identify factors of aging and epigenetic drift from the epidermis. Methylation patterns in human skin become more heterogeneous across individuals over time, serving as markers for age.
Skin is made up of similar cells that contain similar genes. Its phenotype—the way it is displayed because of its genetic-environmental interaction—generally reflects its age. The cell homogeneity of adult human epidermis uniquely models epigenetic drift, the alteration of DNA methylation with age.
Changes in methylation to the epigenome, chemical compounds that modify the function of the genome, are termed “epigenetic drift”. Epigenetic drift teaches us a lot about aging because it represents changes to an organism over the span of its lifetime. These types of changes are localized and can be used to predict age. While age-related methylation has already been identified, this study seeks to identify specific characteristics of this phenomenon.
Largest Sample of Human Epidermis Methylomes
Scientists obtained epidermis samples from the outer forearms of 24 young (18-27 years of age) and 24 old (61-78 years of age) participants. This dataset was kept separate from a second, which contained 60 samples from a broad range of 20-79 year-olds and served to confirm results from the first. All participants were disease-free and of the same ethnicity and gender (Caucasian females). With these samples, scientists generated the largest current sample of human epidermis methylomes, a total of 450,000 methylation marks.
After analyzing and observing the skin samples, the scientists discovered less variation among samples of younger skin.
- Younger skin had more heterogeneity in individual methylation patterns but was generally more homogeneous across individuals.
- Older skin had less clearly defined samples that were more homogeneous individually but more heterogeneous across individuals.
While methylation patterns among individuals become more similar with age, variability among different people increases, representing a change that occurs with epigenetic drift. Using the information that they observed from the dataset, scientists were able to predict the ages of the samples from methylation changes with high accuracy.
An example of a methylation change to the epigenome is the hypermethylation of CpG islands in DNA, particularly apparent in older skin. Interestingly, this study observed two specific peaks of hypermethylation of CpG islands in middle-aged women at 40 and 55 years of age. It is believed that these changes are likely due to menopause, a phase known to accelerate aging that is reflected in the aging of the skin.
Overall, in this study, scientists were able to collect the largest current dataset of skin samples and use it to predict age and learn more about how methylation patterns affect aging and provides a powerful example of epigenetic drift.