Epigenetic clocks: monitoring aging through DNA methylation

Highlights

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• Our biological age differs from our chronological age, and most existing clinical biomarkers fail to capture this difference. Biological age describes the actual aging state of our bodies.
• DNA methylation was robustly linked to an array of age-related changes
• Large-scale data on DNA methylation, advanced experimental techniques, and advances in statistical modeling allowed the creation of precise biological age estimators called epigenetic clocks
• Different types of epigenetic clocks, such as single- and multi-tissue, exist and have varying degrees of accuracy and areas of applicability
• Employing epigenetic testing can be a valuable addition to monitoring changes in biological age based depending on the introduced lifestyle modifications or any other interventions

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Introduction 

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As research shows, the number of lived years (our chronological age) frequently differs from the actual aging state of our bodies (biological age). But how can we assess the biological age? Most clinical biomarkers fail to capture the fundamental mechanisms of aging and, thus, cannot serve as an indicator. However, the recently developed 'epigenetic clocks' biomarkers aim to link developmental and health maintenance processes to biological aging. This article discusses the scientific basis behind epigenetic clocks, their applications, and perspectives for supporting healthy longevity.

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How do the epigenetic clocks work?

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Deoxyribonucleic acid (DNA) is a key macromolecule that contains genetic information. However, DNA does not remain immutable during the course of life  and can undergo dynamic changes, known as epigenetic alterations. The epigenetic alterations change the DNA's chemical structure without changing the sequence. The primary mechanism behind these alterations is called DNA methylation – a process in which a methyl group is transferred to the cytosine residue in DNA. DNA methylation is able to regulate gene expression and cell differentiation. In most cases, so-called CpG methylation occurs when methylated modified cytosine residues lie next to a guanine base.

The connection between DNA methylation and aging has been recognized since the 1980s (1), sparking the search for reliable ways to measure it. However, no significant progress was made until the emergence of multiple technical and scientific advances, such as the completion of the Human Genome Project (2), advances in microarray technology (an experimental technique that allows simultaneously sequencing  of  large numbers of genes) (3), next generation sequencing (high-throughput DNA sequencing technology), and the development of powerful machine learning techniques for data processing (4). Last but not the least, the emergence of large publicly available datasets enabled the creation of multi-tissue biomarkers of aging. 

Since these technological advances, the methylation states of the almost 30 million CpGs in the human genome have been linked to age-related changes (5).  These data, coupled with the machine learning algorithms, allowed for the creation of epigenetic age estimators, widely known as the epigenetic clocks, due to their accuracy. The estimated age, also known as DNAm age, reflects the biological age of the DNA source, which can be from various cells, tissues, and organs.

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Types of epigenetic clocks

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Existing epigenetic clocks can be divided into two groups:

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• Single-tissue,
• Multi-tissue.

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Single-tissue biological age estimators employ fewer CpGs, mainly from a single tissue. A well-known example of this type of clock is Hannum's clock, derived on the basis of 71 CpGs from blood combined with a couple of parameters from other tissues. As this clock was trained on adult whole-blood samples, it produces biased estimates for non-blood tissue or children. Though single-tissue DNAm age estimators can still provide high accuracy (e.g., for predicting all-cause mortality (6)), they are still less accurate than muti-tissue clocks.

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A multi-tissue epigenetic clock should ideally apply to all tissues in the human body and provide valid results throughout the lifespan. Ideally, if such an epigenetic clock existed, it would become an invaluable tool for diagnostics and research. This  would allow us to directly link developmental and maintenance processes to aging. Though existing multi-tissue clocks have not yet reached perfection, they still provide valuable insights. The most known example of this type is Horvath's clock (7), developed based on samples from more than 30 different tissues and cell types from prenatal age till centenarians. Horvath's clock uses selected 353 CpGs to produce a composite multivariate biomarker. Since its creation, Horvath's clock has been employed in multiple studies, revealing that most tissues and organs in the body have the same biological age (with exceptions, such as the cerebellum (8)). It was also shown that aging accelerates at a different rate at different stages in life (speed is much higher at developmental stages).

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While both types of clocks mentioned above show high accuracy regarding disease risks and mortality, their association with clinical measures (such as glucose levels or blood pressure (9)) was weak. These clinical measures, in turn, are strongly associated with lifestyle factors. To better incorporate these lifestyle factors into the DNAm age estimation, Levine et al. developed the DNAm PhenoAge clock based on 513 CpG (10). They incorporated ten additional features, including the following:

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• Chronological age, 
• Albumin levels,
• Creatinine levels, 
• Glucose levels, 
• C-reactive protein levels,
• Lymphocyte percentage,
• Mean cell volume,
• Red blood cells distribution, 
• Alkaline phosphatase levels,
• And white blood cell count.

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Employing phenotypical features allowed this clock to improve predictive ability in adults. However (similar to Hannum's clock), the results can be biased in non-blood samples or children. Using a similar approach, Lu et al. developed the GrimAge clock (11). It is based on chronological age, sex, and ensemble predictions from eight other epigenetic clocks. 

Generally, clocks associated with chronological age better reflect age-related changes caused by the intrinsic aging process, while phenotypical clocks capture both intrinsic and external influences (6). Also, phenotypical clocks seem to be better suited to track differences within the same individual. There are multiple epigenetic clocks developed up to date, and the following table provides a brief summary of the major ones:

What does our biological age say?

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As mentioned above, the epigenetic clocks demonstrate high predictive ability regarding morbidity and mortality risk estimations. The studies show that these estimations  are associated with a vast number of age-related conditions and diseases, such as Parkinson's disease (17), coronary heart disease (18), and several cancers (19–21). Additionally, the epigenetic clocks were shown to be linked to physical and cognitive fitness (22,23), white matter integrity in the brain (24), and centenarian status (25). Such all-encompassing nature makes the epigenetic clock an ideal approach for complex assessment of personal health status and longevity prospects. 

But the age estimators are not limited to that. One of the greatest promises of DNAm age biomarkers is the identification and assessment of anti-aging interventions in humans. The finding supports the point that a healthy diet, physical exercise, and general fitness show a strong association with slower epigenetic age acceleration. Lower ages of Hannum and GrimAge clocks were reported to be associated with diets rich in fish, fruits, and vegetables (11,26). There is also evidence for a beneficial effect of exercise, but it might be lower amongst older individuals (26). Currently, there is  limited amount of data that supports the "slowing down" of the biological clock through pharmacological means. For example, Fahy et al. were able to decrease the age acceleration in humans for four clocks by 2.5 years, employing the thymus rejuvenation protocol (27).

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Suggestions for professionals

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Biological age assessment can be recommended both for health risk assessment as well as for monitoring the beneficial effects of lifestyle changes. If you would like to suggest an epigenetic clock to your clients, there are several things you could do:

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• Explain to your client the concept of biological age and how it differs from chronological age,
• Point out that multiple age-related diseases, as well as health- and lifespan, are linked to biological age,
• Help your client understand how introducing epigenetic testing might be beneficial for their longevity routine,
• Multiple vendors (such as Elysium Health, Zymo Research, TruDiagnostic, and DoNotAge) provide direct-to-consumer epigenetic tests, which can be done at home and sent back to the laboratory for the results. Help your client choose an appropriate test for them based on reliability, price, and data privacy provided by a vendor.
• While monitoring your client's progress, ensure that the tests are taken at the appropriate time intervals, so that the changes can be captured. The same time range depends on the test. In most cases, changes cannot be observed earlier than in five to six month after the start of the intervention.

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Conclusions – the DNA ticks count

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Epigenetic clocks provide one of the most robust and easy ways to assess the real age of a human body. Also, they demonstrate encouraging results in the area of anti-aging intervention assessment. However, more studies are needed for the field to get closer to the "ideal" multi-tissue test. Research shows that, in some cases, an interplay between gene expression and DNA methylation might be too complicated for the existing clocks to capture. And the future might bring even more precise biological age estimators. Nevertheless,  the already accessible tests can be used as a powerful tool on the longevity path.

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References

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