Measuring aging, the epigenome and biomarkers

Highlights:

• Age-qualifying tools are called biomarkers
• Biomarkers are molecular markers of e.g. epigenetic or proteomic changes that occur with age and that would respond to an intervention that also improves health
• The areas where the most progress so far has happened is the so-called epigenetic clocks
  

Introduction

Imagine a scenario that could be likely to occur in a relatively near future, where the doctor accurately is able to monitor exactly how well you are aging and prescribe medicines that are known to affect these markers. As the medicine works they subsequently bring you back to a younger biological state that not only makes you feel better, but can be measured by a simple blood test. The area of aging biomarkers is new and still largely at an experimental stage, however fascinating possibilities exist with vast applications for the future of medicine. 

Age-qualifying tools

In order to provide the best possible measurements that an intervention is affecting aging it is first important to have good tools to quantify what aging actually is. In order to know a process that causes disease it is necessary to track it and separate it from the physical symptoms that appear (Galkin et al 2020).

Something that measures a change in the body is called a biomarker, a marker of either a normal process or something pathological occurring in the body. Biomarkers have been used as diagnostic tools for many diseases, for example to detect cancer early before the symptoms appear or to measure the risk of cardiovascular disease in asymptomatic people.

As science progresses towards being able to work on multiple diseases related to aging and intervene before they start, this is where the area of aging biomarkers comes into the picture.

There are many ways of quantifying health however many of them are tied to physiology and may not measure aging in general but rather end stage disease processes. For example there may be changes in the brain long before a person shows symptoms of Alzheimer’s, senescent cells accumulate in the body and make it more aged but without causing a specific severe illness until the person lives into their later decades.

Biological aging efers to the tissue damage that occurs with age and ultimately leads to the general diseased state of the elderly, but until recently it has been extremely hard for science to track it. A small child with no medical education whatsoever can easily determine who is the healthy 20-year old and who is the sick 90-year old, but when it comes to markers that can be tracked in e.g the blood the area has been much more difficult. For example an older person who is not in their final stage of a particular disease may have similar blood pressure and cholesterol as a younger person, making such traditionally used markers at doctors offices relatively useless when it comes to quantifying the aging that still happens despite having a healthy lifestyle.
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Biomarkers

So in order to more precisely and robustly measure an anti-aging intervention it would be better to have biomarkers on a smaller level - molecular markers, for example epigenetic or proteomic changes that occur with age and that would respond upon an intervention that also improves health.

This type of predictive and personalized medicine is the future, where people instead of getting sick have their diseases tracked and prevented in their early stages. It is also an absolute necessity to know that something has an effect early on when for example doing clinical studies on an age-related disease and to measure how well someone is responding to a therapy. 

The areas where the most progress so far has happened is the so-called epigenetic clocks. These clocks measure the epigenome, which are the heritable changes to the genome that in contrast to the genome are acquired by environmental factors. These changes can be for example histone modifications (the proteins that our DNA is wrapped around) as well as methylation patterns (methyl groups added to our genome in response to the physiologic environment and passage of time, so called CpG islands). Epigenetics is constantly changing as opposed to genetics and subsequently can also reflect lifestyle changes as well as improvements in disease conditions. The epigenome in itself affects how genes are expressed in the body and subsequently alterations in the epigenome will affect many disease states, outside of aging this is an important area of research in cancer. Since cancer is abnormal cell growth there is a wide range of epigenetic alterations that turn cells malignant driving aberrant proliferation (Jones et al 2016).

By looking at large-scale human data from cohorts one can measure changes in the epigenome occurring with time and that reliably are correlated with disease outcomes and death. Using artificial intelligence one can analyze this data and correlate it with age to more and more accurately predict how well individuals in the cohort are aging. 

Epigenetic aging

With aging there is also a variation in the epigenetic landscape across the body, for example it is established that there are variations between different tissues when it comes to aging which is reflected in the epigenome. For example the lungs of a smoker may have a higher chronological age as reflected in the epigenome than other tissues that have been less directly exposed. The area around a tumour is also likely to show alterations that aren’t present in healthier tissue, so epigenetic clocks measure the tissue quality across the systems. 

The area of epigenetic measurement of age has been pioneered by scientists such as Steve Horvath and Morgan Levine among others. They have constructed epigenetic measuring tools that have been validated and normalized on large numbers of people and found to correlate with aging. The GrimAge and Levine (DnamAge) clock have subsequently turned into among the most well known of the field, despite that there are now many competitors upcoming.

Grimage and PhenoAge have been assessed and validated on nearly 10 000 individuals of different ages and shown to correlate with general deterioration in physiology. Disease states they have been correlated with include decreasing walking speed in elderly, memory problems and grip strengths as well as the ultimate endpoint which is mortality (Lu et al 2019).

These findings have spurred the growth of the field as even simple things that are actionable today, such as exercise and healthy eating, can produce measurable outcomes on the epigenetic level and it therefore becomes an area that is actionable. 

Epigenetic clocks are nowadays on the market for customers but  should be taken with a grain of salt since they are still at an experimental stage and not part of mainstream medicine to diagnose a particular disease condition. For a person who is interested in longevity and wants to try and quantify their age with the best available diagnostics today it would make sense to take several epigenetic tests and combine them, forming a composite epigenetic score to approximate one's health (Belsky et al 2018).

A good biomarker of aging needs to correlate with disease and generalized frailty to determine which people have the highest biological age, it would also need to be robust and predictive and respond to future therapies that would truly reverse aspects of aging. It is already well established that people do age at different rates even in the absence of very specific disease conditions and that those who age the slowest tend to survive the longest.

For example supercentenarians (people who survive to the age of 110 years or more) tend to look younger than other people of the same age earlier in life. Most supercentenarians do not only avoid or delay specific diseases such as cancer and heart disease until late in life, they also retain their general ability to function much longer (Schoenhoefen et al 2006).

A typical person surviving to 110-115 years of age is often fully independent until the age of 105 and subsequently spend a similar amount of time needing care as many older people who only survive until their 90s. In order to understand the processes of aging it is often useful to look at the extremes, and tissue samples of supercentenarians have shown that they do age at a slower speed than others having a lower epigenetic age (Horvath et al 2015). So in many ways it could be said that the oldest people in the world die while being in similar physiological states as people who are a couple decades younger than them, they just accumulate that aging damage and get sick from it at a slower rate which makes them live longer. 

It remains for science to quantify exactly how it occurs when it happens, and how to use this knowledge to develop therapies that benefit all of humanity.

In the meantime, the best things that can be done is to advance the research of tools to quantify the aging processes in the body and be able to get epigenetic clocks and other  markers accurate enough to become part of any baseline medical checkup. 

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2. Jones, P., Issa, JP. & Baylin, S. Targeting the cancer epigenome for therapy. Nat Rev Genet 17, 630–641 (2016). https://doi.org/10.1038/nrg.2016.93
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4. Belsky DW, Moffitt TE, Cohen AA, et al. Eleven Telomere, Epigenetic Clock, and Biomarker-Composite Quantifications of Biological Aging: Do They Measure the Same Thing?. Am J Epidemiol. 2018;187(6):1220-1230. doi:10.1093/aje/kwx346
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