As research in to human aging and the mechanisms behind it grow, there’s a need to address the big fat albatross around the neck of gerontology.  The albatross is that until we identify some valid biomarkers of human aging, we must rely on the data in animal models and epidemiological research in humans.

Currently, there are a few commercially available tests to assess your biological age, which differs from your chronological age in that chronological age focuses specifically on how much time has passed while biological age focuses on how your body functions.  A great illustration of this concept is that you can have a pair of 2009 Toyota Corrollas with vastly different mileage.  Since they’re both from 2009 their chronological age is the same while the car with the higher mileage likely has a greater functional or “biological” age than the lower mileage car.  Of course, cars aren’t biological entities, but you get the point.

Since humans live for so long, clinical trials are extremely difficult to do given the level of control you’d need to exert on participants in a valid and useful clinical trial.  Aging biomarkers provide utility here in that you don’t need to follow someone for 50 years to see if a therapy or lifestyle approach is working.  You can simply look at their rate of biological aging and determine if what they’re doing is speeding it up or slowing it down.

Currently, there are 3 fairly useful biomarkers of aging that we can use to determine if we’re aging faster or slower than our peers.  These biomarkers include telomere length, the epigenetic clock, and a new up and coming biomarker using artificial intelligence called Young.AI.  Of these biomarkers, the epigenetic clock and Young.AI appear to have a pretty substantial correlation to your chronological age, with the hope being that this means they are accurate assessing your biological age.

I’ve recently given all 3 of these a test run with pretty divergent results.  For the layperson, it may seem a bit confusing as to how you get different results even with 2 aging biomarkers that have a strong correlation with chronological age.  I intend to break that confusion and explain my results in this blog.

Taken from: http://www.mydochub.com/images/how-to-slow-down-aging.jpg

Different biomarkers measure different things

When we look at the different aging biomarkers, what we find is that they’re actually measuring different problems that contribute to aging.  So while they attempt to predict the same outcome, they’re actually doing so by looking at different things that affect that outcome.

Going back to our car analogy, we have the assumption that more miles means a greater drop in function with time.  However, this is a fairly simplistic view that ignores that there are many things that can cause a car to break down.

For example, if the car with fewer miles was driven more recklessly and under poorer conditions, there may be greater wear and tear on that engine.  And, of course, maybe the owner rode the brakes, wore down the tires, ruined the suspension and drivetrain, or did any number of things that could cause one of the many systems to go before the engine.

So, while on the surface we would say the higher mileage car has poorer function, that’s not always the case.  As you can see, taking a look at all of the systems gives you a more comprehensive view of the state of the vehicle.  The same could be said for divergent results in the different aging biomarkers.

So let’s take a look at the different aging biomarkers and what they’re measuring to assess biological age.  We’ll also take a glimpse in to my results.

Taken from: http://sphweb.bumc.bu.edu/otlt/mph-modules/ph/aging/paste_image2.jpg

Leukocyte telomere testing

Telomeres are protective caps on the ends of our DNA that prevent damage to the tips of DNA and the fusion of 2 neighboring chromosomes.  As we get older and our cells divide more, our telomeres get shorter.  Once our cells divide a certain number of times, called the Hayflick limit, our telomeres reach a critically short length and they stop dividing.

Thus, measuring telomere length can be useful to determine how many times a cell has divided and used to determine biological age.  The commercially available telomere length test measures the average length of telomeres on leukocytes, which are white blood cells.

While useful, there are some drawbacks to testing telomeres in this way.  For one, you’re only measuring one cell type, albeit a cell type that seems to correlate to what’s going on elsewhere in your body.  The bigger issue, and one that can be addressed in future iterations of telomere testing, is that average telomere length may not be as useful as looking at the shortest telomeres.  The cells with the shortest telomeres will enter a state called senescence sooner which prevents cell division and increases inflammation.

These 2 drawbacks may help explain the variation in how well telomere testing correlates with age(1).  Some studies showing a fairly strong correlation of around .45 with others showing little to no correlation.  An alternative hypothesis that’s recently been proposed is that average leukocyte telomere length is a meaningful measure of age acceleration caused by the gradual decline of the immune system(2).

So what did my leukocyte telomere length test show?  It actually predicted my age as 31 years old, a 10 year drop from my chronological age of 41.  This jibes with how I feel my immune system works.  I never get sick and when I do it’s over pretty quickly.

Note:You can order the telomere length test that I used at http://www.teloyears.com

DNA Methylation and the epigenetic clock

The epigenetic clock, on the other hand, is measuring a completely different process from telomere length called DNA methylation.  Our DNA contains the blueprint for how our body interacts with the environment.  Epigenetics is the study of how our genes are turned on or off based off the environment.  DNA methylation is one of the primary forms of epigenetic regulation that acts by silencing gene expression.

Research done in 2013 by Dr. Steve Horvath identified that as we age there’s a predictable change in the way our DNA is methylated(3).  There tends to be a global decrease in methylation, though some genes tend to be hypermethylated.  Dr. Horvath determined that we can predict biological age by looking at the way a specific set of genes is methylated, a set of genes now known as the epigenetic clock.

This research has provided some very interesting findings.  First, the epigenetic clock is tissue specific and can predict the age of different tissues in the body of the same person.  This has allowed us understand that different tissues in the same person age more rapidly than others. Of the tissues measured, blood and urine provide an accurate measure of of the organism’s age, aka you.

Another finding is that different people have clocks that tick at different rates(4).  This means that some people, no matter what they do, will ultimately live shorter lives than others based solely on how rapidly their clocks tick.  Eating more vegetables may give them more time than they’d otherwise have, but they’ll still have less time than someone with a clock that ticks slower, even if that person’s lifestyle isn’t as ideal.

Since Dr. Horvath’s initial study, further research has identified more genes that are predictive of biological age.  Even so, Dr. Horvath’s original set of genes predicted chronological age very accurately, with a correlation of .96 which is just about as strong of a correlation as you’re going to get.

So what did my DNA methylation test show?  Unfortunately, nowhere near as good as my telomere test.  According to my DNA methylation test my biological age is 48 years old, 7 years older than my actual age.  This is definitely not good, but since I took the test I’ve made some adjustments based off some interesting research that I’ve dug up.  If you want a tease of what I’m talking about, check out this paper.

I’ve adjusted some lifestyle factors and identified some genetic pathways that could be impacting my results, and I plan on taking another test in late January/early February after 3 months of implementing these changes. My primary goal is to find out if my lifestyle was out of whack or my clock just ticks faster than it should, which is the primary value of the biomarkers of aging.

It’s important to note that my telomere test actually came after I’d made a few of those changes, including a 3.5 day fast that more than likely improved my telomere score from what it would have been.  I’ll cover the mechanisms behind this in a future blog.

Note: You can purchase the DNA Methylation test I used from Epimorphy at http://www.myDNAge.com

Young.AI

Young.AI is a little different than the other tests I’ve mentioned.  The power behind Young.AI is that it uses artificial intelligence to integrate multiple measures to assess biological age.  Unfortunately, that means we really can’t determine which systems it’s assessing since it’s using as many as possible.

As I mentioned in a previous blog you can find here, the power behind Young.AI is that it’s free, and thus, accessible.  This allows the program to “learn” and improve over time.  So, as the platform analyzes more data, it gets better.  Furthermore, future plans for Young.AI will integrate both DNA methylation and telomere testing to provide about as comprehensive of a look at human aging as you could get.

Currently, Young.AI assesses biological age via 2 methods: blood tests and facial pictures.  While the facial pictures are interesting and something you can do far more often than take a blood test, I feel the blood test provides a better look at the way you function.

What sets Young.AI apart from the other forms of testing is that it’s free and works by entering the data you get from routine blood labs.  This means there’s currently no cost to users and you can enter past data to get a look at how you’re aging over time.  With the DNA methylation test costing $300 and the telomere test costing $100, this is a substantial benefit.

So what is my biological age based off Young.AI?  I actually have 2 data points that I entered, one from 2012 and one from April of 2017.  According to Young.AI, my biological age in 2012 was 36 when I was 36 and in 2017 it was 39 when I was 40.  So according to Young.AI, I’ve made improvements that have slowed my rate of aging.  Interestingly, the facial photos also predict my biological age as 39, the same as my most recent blood test.

Note: If you have blood tests or want to play around with the facial age prediction, go to http://www.young.ai to start your profile and upload your data.

Conclusion

The different biomarkers of aging attempt to assess your biological age through different means, so it’s reasonable for them to have some level of variation.  Of course, the measures that correlate more tightly to chronological age are better at predicting your mortality risk, but that can be for any number of reasons.

When it comes to DNA methylation, I feel that the loss of proper DNA methylation is more devastating than shorter average telomere length.  It also may be that aberrant DNA methylation is more common as we age based on our genes and how they interact with our environment.  Personally, I have some genetic polymorphisms that I’ve identified and corrected that may have impacted my results.  I’ve also improved my lifestyle a bit to goose the results.

Whether your personal results are due to how quickly your lifestyle causes your clock to tick or that your clock simply ticks faster than everyone else is useful information, particularly if its the former and not the latter.  This would indicate that you have some level of control over when your clock stops ticking.

While telomere testing has its warts, shortened telomeres are something that will need to be addressed as you age since the accumulation of senescent cells will hasten your demise.  So telomere shortening is something you want to prevent and assessing telomeres provides some value in doing this.

Of the currently available tests, young.AI shows the greatest promise because the goal is to integrate the information from multiple tests to come up with a comprehensive assessment of age.  As more data is collected from the different biomarkers, the machine will only get better at spitting out a biological age.

My plan of attack is for my next telomere and DNA methylation tests to be at the same time.  I’d love to do the same for Young.AI, but I’m not sure that will be possible given my schedule and getting in for bloodwork.