A Review of DNA Methylation Based Epigenetic Clocks as a Measure of Aging

Epigenetic clocks measure DNA methylation of sites on the genome that are patterned in much the same way in every individual of a given age. DNA methylation is an epigenetic marker that serves to regulate the production of protein from a specific gene. A range of different clocks have been constructed based on weighted assessments of methylation at various points on the genome, and the best of them can measure age quite accurately, to within a few years.

The clocks were built by working backwards from DNA methylation and age data, and it was discovered along the way that people with methylation patterns characteristic of an older age have a worse prognosis for age-related disease and mortality, or have a greater tendency to already exhibit age-related diseases. It is unclear, however, as to what exactly epigenetic clocks really are measuring. Which of the underlying forms of damage and consequent dysfunction, outlined in the SENS rejuvenation research proposals, lead to these DNA methylation changes? Some of them? All of them? No-one can presently say, and that is a challenge if the research community is to use epigenetic clocks to assess potential rejuvenation therapies.

The development of tools to diagnose and predict age-dependent risks has enormous significance in preventing age-related diseases and improving the health status of the elderly. The process of aging results in multiple changes at both the molecular and cellular level, including cellular senescence, telomere attrition, and epigenetic alterations. Among these hallmarks, telomere length, which experiences progressive shortening during replication of somatic cells, is a remarkable characteristic of aging and linked with age-related health status. However, recent evidence has revealed that the correlation between telomere length and age-related outcomes of individuals is low. Thus, investigators are still searching for other biomarkers that can be used in the prediction of age-related outcomes with higher accuracy.

Current studies have indicated that epigenetic changes comprise a significant component of the aging process. Epigenetics refer to the modulation of gene activity without any change in the genomic sequence. Well-studied epigenetic modifications include DNA methylation, histone modification, and non-coding RNA, with changes in dynamic DNA methylation found to be most associated with the aging process. In general, age-dependent changes in DNA methylation include global hypomethylation and region-specific hypermethylation.

Abundant studies have demonstrated a close relationship between DNA methylation and aging and longevity. These findings have impelled researchers to develop age predictors based on the correlation between methylation changes and chronological age. DNA methylation age, evaluated by these predictors, reflects the biological age of a person, which has a close association with individuals' health status and can be changed by multiple risk factors, such as smoking and obesity. Therefore, the difference between DNA methylation age and chronological age may be a promising tool in predicting disease risk and longevity potential in early life.

Link: https://doi.org/10.3389/fgene.2019.00107


As in the last year, hopefully there will be more understanding on this topic in the coming Undoing Aging conference. I think in the meantime we had the DNAm PhenoAge, Phenotypic Age and DNAm GrimAge studies. Also it would be good to know more about AI/ML driven tools.

Posted by: albedo at March 17th, 2019 12:09 PM
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