Development of an epigenetic clock to predict visual age progression of human skin

• Published in: Frontiers in aging Vol. 4; p. 1258183
• Main Authors: Bienkowska, Agata, Raddatz, Günter, Söhle, Jörn, Kristof, Boris, Völzke, Henry, Gallinat, Stefan, Lyko, Frank, Kaderali, Lars, Winnefeld, Marc, Grönniger, Elke, Falckenhayn, Cassandra
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 11.01.2024
• Subjects: Aging; biological age; DNA methylation; epigenetic age clock; skin aging; wrinkles; wrinkles; biological age; epigenetic age clock; DNA methylation; skin aging; aging; visual age; age progression
• ISSN: 2673-6217; 2673-6217
• DOI: 10.3389/fragi.2023.1258183

Aging is a complex process characterized by the gradual decline of physiological functions, leading to increased vulnerability to age-related diseases and reduced quality of life. Alterations in DNA methylation (DNAm) patterns have emerged as a fundamental characteristic of aged human skin, closely linked to the development of the well-known skin aging phenotype. These changes have been correlated with dysregulated gene expression and impaired tissue functionality. In particular, the skin, with its visible manifestations of aging, provides a unique model to study the aging process. Despite the importance of epigenetic age clocks in estimating biological age based on the correlation between methylation patterns and chronological age, a second-generation epigenetic age clock, which correlates DNAm patterns with a particular phenotype, specifically tailored to skin tissue is still lacking. In light of this gap, we aimed to develop a novel second-generation epigenetic age clock explicitly designed for skin tissue to facilitate a deeper understanding of the factors contributing to individual variations in age progression. To achieve this, we used methylation patterns from more than 370 female volunteers and developed the first skin-specific second-generation epigenetic age clock that accurately predicts the skin aging phenotype represented by wrinkle grade, visual facial age, and visual age progression, respectively. We then validated the performance of our clocks on independent datasets and demonstrated their broad applicability. In addition, we integrated gene expression and methylation data from independent studies to identify potential pathways contributing to skin age progression. Our results demonstrate that our epigenetic age clock, VisAgeX, specifically predicting visual age progression, not only captures known biological pathways associated with skin aging, but also adds novel pathways associated with skin aging.