In my last blog I covered why what’s in our blood is important for our gut health. If you didn’t get a chance to check that out, I suggest you do so as it’s important for what I’m discussing today.
People have an erroneous perception about the concept of aging. For most, aging is simply a time-based erosion of function brought about by accumulated damage to our body. Admittedly, I was guilty of this until I began reading up on aging research.
There’s a ton of data to contradict this paradigm dating back to the 1970s. Experiments involving heterochronic parabiosis, a process where an old and young mouse are attached to one another leading to a shared vascular system, found that components of young blood rejuvenated the old mouse while components of old blood caused the younger mouse to age. These results are some of the first to indicate that the aging process is actually amenable to change and isn’t simply based off the passage of time.
Since then, the data that blood holds keys to aging has only strengthened. Recent evidence indicates that we can hit aging from 2 sides: by adding in rejuvenating factors found in young blood and by filtering out components of old blood that promote aging.
We’ve also learned that aging as it pertains to an individual isn’t a single thing. In these studies, animals didn’t just look younger and listen to hipper music. The health of their organs also changed in a manner consistent with the age of the blood of their “parabiosed” chum.
This is important because blood is a systemic factor that all of your organs are exposed to. All of your organs and tissues age at different rates, with the organs associated with age-related diseases aging faster than organs less affected by aging. Interestingly, cardiovascular disease is the #1 age-related killer and the blood vessel walls are chronically exposed to the blood.
How does blood regulate aging?
I don’t want you to be under the impression that what I discussed in the last blog is a simple, straightforward process. We’re still teasing out the particulars of what’s in blood that regulates aging. When you introduce young blood in to old mice, you’re not only introducing proteins from the young blood, you’re also diluting the contents of the old blood.
An interesting theory for why experiments using heterochronic parabiosis yield changes in the function of tissues involves the stem cell pool. In every organ lies a pool of stem cells charged with the task of replenishing cells as they’re lost. These stem cells reside in microenvironments called niches that allow stem cells to respond to tissue demands. Factors within the local niche help determine stem cell fate, as do systemic signals found in the blood.
As we age, our tissues lose their ability to regenerate, at least in part due to a decline in the local stem cell pool(1). Some of this is due to changes in the local stem cell niche, with an increase in senescent cells and their secreted factors being one of many issues. However, systemic factors in the blood are also thought to affect stem cell function at the local level. Insulin, IGF-1, and inflammatory cytokines are big systemic factors that regulate stem cell function.
Stem cells and parabiosis
A recent study found that old blood may have a greater pro-aging effect than young blood has a rejuvenating effect. In this study, a single exchange of blood from an older or younger mouse caused an immediate change in the way stem cells behaved after an injury, depending on the tissue. Older mice given younger blood saw enhanced muscle regeneration while younger mice given older blood saw negative effects on the brain. The liver seemed to be equally affected by both scenarions(2).
The interesting thing about this study is that it’s dealing solely with the blood. In parabiosis studies, having the same circulatory system also means shared organs. The old mouse has a new liver to help out it’s old liver. It also has access to a new pancreas, while the organs of the young mouse are now bogged down pulling more weight for the old mouse. This study shows that there are factors in blood that regulate the aging process, and these factors likely involve modulating stem cell function. Note: For a comprehensive review on longevity pathways that regulate stem cell function from a calorie restriction perspective, check out this doozie of a review.
If this is indeed true, it will completely transform the way we deal with age-related diseases. Rather than targeting Type 2 diabetes, or Alzheimer’s disease, or cardiovascular disease, we can target one thing: the aging process. It’s also paradigm-shifting. If the systemic environment dictates how well our organs and tissues function by regulating the stem cell pool, aging could be amenable to change.
If you think about it, there’s some other interesting stuff you can pull from this, which brings us to the purpose of this blog. If blood contains factors that can rejuvenate or age an animal, it seems likely that blood may also contain information that indicates an organism’s well-being. Could blood contain usable information on how you’re doing at life, from an aging perspective?
Yes, it appears it does.
Aging biomarkers: getting the most out of your annual check-up?
On a regular basis, we use information from blood to determine how healthy we are. The routine use of comprehensive metabolic panels(CMPs) during annual physicals is typically a ho-hum process. Unless something is completely out of whack we don’t get useful information from these tests until something goes wrong.
All that recently changed when a company called InSilico Medicine got in to the aging biomarker game. The company uses artificial intelligence for drug development, but has recently introduced a program called Young.AI that is a fairly good predictor of human aging. All you do is input the results from any CMP and the program predicts your age.
The program is considered a fairly strong predictor of chronological age. A study in 2016 found that the old version of the program, Aging.AI, had a correlation of around .80 with chronological age(3). A perfect correlation is 1.0. One has to assume that it has only gotten better with more data.
The data also revealed which measures in a CMP are the strongest predictors of age. They are albumin, glucose, alkaline phosphatase, urea, and erythrocytes(RBCs). Conspicuously absent is cholesterol, given the chronic blame heaped upon it for cardiovascular disease, our biggest killer. Not really that surprising, though, given cholesterol drops with age while the risk of death increases.
Taken from: http://images.wisegeek.com/blood-donation.jpg
Taking Young.AI for a test spin
The thought process is that since Young.AI is predicting your chronological age, what it’s actually generating is your biological age in relation to the general population. In other words, it’s giving you an idea as to how you are aging in comparison to everyone else that comprises the data set. So, if it predicts your age as lower than it is, this means you’re aging more slowly. Conversely, if it predicts your age as higher, you are aging more quickly.
This is very useful if you value your health. If we buy in to the concept that the blood contains factors that regulate aging, which I feel is consistent with the data, we can use the age prediction from Young.AI as a measure of progress in lifestyle decisions. This is a pretty big game-changer given how much money people spend on supplements without any knowledge of whether or not they’re providing a benefit. Young.AI also has places for you to input diet, supplement, pharmaceutical drug, and exercise factors.
I decided to take Young.AI for a test spin to see if it could give me any perspective on lifestyle decisions I’ve made. Unfortunately, I only have 2 data points. Fortunately, I had blood drawn for very specific reasons and I know what I was doing from a diet perspective during both, for the most part.
My first data point was from 2012. At this point, I was eating a very strict/clean diet, I had abstained from alcohol for at least 3 months in that year, I was on the low end of carbohydrate consumption(<100g/day), and I weighed 172 lbs. Age prediction at age 35 was 36, not good. Too fast.
Fast-forward to April of this past year, my next data point. Low processed food intake but not complete avoidance, regular craft beer consumption, high carb(>300g/day), and I weighed 190lbs. I also played around with circadian rhythms and time-restricted feeding for a month prior to the test. Age prediction at age 40 was 39, better.
Based off these results, I was better served eating less clean, weighing 10lbs more, and drinking beer every week. Yay! Granted, these tests were not performed on the same day of the week, during the same month, or even at the same time of day. Moving forward, I plan on making an effort to schedule my tests to remove these extraneous variables.
Another factor that needs to be considered is that the predictive ability of Young.AI is based off the data it’s analyzing. In the first pass, Aging.AI, the data set came from over 62,000 sets of anonymous lab results provided by a Russian blood lab. This may not be indicative of general human aging. Nothing has been released regarding the data used for the newer version, Young.AI.
I think Young.AI is a very valuable tool for predicting age. More importantly to you, it can have some utility in helping you manage your lifestyle, if that’s something you like to do. Who wants to restrict their diet unnecessarily and spend ridiculous amounts of money on supplements without knowing if they’re getting any benefit out of it? I’ve changed a few things since my last CMP and I’m interested to see how it impacts my “aging”.
Overall, I’m a numbers guy and Young.AI is one of the better tools for assessing age that’s also accessible to the general public. And at $0 for the beta version, it’s light on the wallet. However, there’s another method for predicting age that has a stronger correlation than Young.AI. We’ll be covering that one shortly..