ArticleArchives of dermatological research2024
A miRNA-based epigenetic molecular clock for biological skin-age prediction.
Article in Archives of dermatological research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed.
- Skin aging: mechanisms, evaluation, and rejuvenation.The EMBO journal · 2026Review
- From the lab to lifestyle: epigenetic clocks in personalized aging and health.Biogerontology · 2026Review
- From skin aging biomarkers to precision esthetic longevity: a translational diagnostic framework.Frontiers in medicine · 2026Article
- Article
- A State-of-the-Art Overview on (Epi)Genomics and Personalized Skin Rejuvenating Strategies.Pharmaceutics · 2025Review
- Toward precision interventions and metrics of inflammaging.Nature aging · 2025Review
- A Sex-Specific Minimal CpG-Based Model for Biological Aging UsingInternational journal of molecular sciences · 2025Article
- Global research trends on the link between skin ageing and antioxidants: a visualization analysis.Archives of dermatological research · 2025Article
- Epigenetic Mechanisms, Assessment and Therapeutics of Epidermal Stem Cells in Skin Aging.Stem cells international · 2025Review
- Contextualizing aging clocks and properly describing biological age.Aging cell · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Skin aging is one of the visible characteristics of the aging process in humans. In recent years, different biological clocks have been generated based on protein or epigenetic markers, but few have focused on biological age in the skin. Arrest the aging process or even being able to restore an organism from an older to a younger stage is one of the main challenges in the last 20 years in biomedical research. We have implemented several machine learning models, including regression and classification algorithms, in order to create an epigenetic molecular clock based on miRNA expression profiles of healthy subjects to predict biological age-related to skin. Our best models are capable of classifying skin samples according to age groups (18-28; 29-39; 40-50; 51-60 or 61-83 years old) with an accuracy of 80% or predict age with a mean absolute error of 10.89 years using the expression levels of 1856 unique miRNAs. Our results suggest that this kind of epigenetic clocks arises as a promising tool with several applications in the pharmaco-cosmetic industry.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.