Abstract
BackgroundDNA methylation (DNAm) age constitutes a powerful tool to assess the molecular age and overall health status of biological samples. Recently, it has been shown that tissue-specific DNAm age predictors may present superior performance compared to the pan- or multi-tissue counterparts. The skin is the largest organ in the body and bears important roles, such as body temperature control, barrier function, and protection from external insults. As a consequence of the constant and intimate interaction between the skin and the environment, current DNAm estimators, routinely trained using internal tissues which are influenced by other stimuli, are mostly inadequate to accurately predict skin DNAm age.ResultsIn the present study, we developed a highly accurate skin-specific DNAm age predictor, using DNAm data obtained from 508 human skin samples. Based on the analysis of 2,266 CpG sites, we accurately calculated the DNAm age of cultured skin cells and human skin biopsies. Age estimation was sensitive to the biological age of the donor, cell passage, skin disease status, as well as treatment with senotherapeutic drugs.ConclusionsThis highly accurate skin-specific DNAm age predictor constitutes a holistic tool that will be of great use in the analysis of human skin health status/molecular aging, as well as in the analysis of the potential of established and novel compounds to alter DNAm age.
Highlights
Introduction to skin agingJ Tissue Viability. 2017;26:37–46. 34
The main characteristics of the cohort are described in Additional File 2–Supplementary Table S1
Data normalization and pre-selection of features Each dataset was individually processed for quality control and merged for preprocessing in order to build a machine learning algorithm able to accurately predict DNA methylation (DNAm) age
Summary
Introduction to skin agingJ Tissue Viability. 2017;26:37–46. 34. Dimri GP, Lee X, Basile G, Acosta M, Scott G, Roskelley C, et al A biomarker that identifies senescent human cells in culture and in aging skin in vivo. Genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication are considered the Recently, additional factors beyond time have been shown to influence DNAm age, such as genetic diseases [3, 4], infectious diseases [5], inflammatory disorders [6, 7], and lifestyle factors, such as exercise and obesity [8], to cite a few. DNAm of cultured cells can be used to predict cellular passage, regardless of donor chronological age [13] In this context, even though the mechanism by which cellular passage and time promote DNAm alterations in cells/tissues has not been clarified, a few functional correlations between DNA methylation and phenotype have been described. The possibility to study aging in vitro initiates the opportunity to apply DNAm age as a parameter to screen and/or validate potential investigational senotherapeutic compounds, defined as molecules targeting senescent cells, either by promoting their death (senolytics), or altering the senescence status (senomorphics) [15]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
