Markers of aging
How to calculate the biological, "real" age of a person?
The Alpina non-fiction publishing house publishes the book "Counterclockwise" by the scientific journalist Polina Loseva.
TASS publishes an excerpt about how scientists are looking for signs of aging
"Counterclockwise: What is aging and how to deal with it" is the first book by Polina Loseva, whose articles probably came across to our regular readers. We heartily congratulate her on her debut!
It takes courage to tackle this topic. Everyone will get older, or at least hope to get older, but few people are looking forward to it. If you look more broadly, you can see that the proportion of able-bodied people in more or less developed countries is already dangerously low. In other words, aging is both a personal and a social problem. Of course, they promise to solve it, but every time a brisk PR man imposes an interview with another expert, it becomes uncomfortable: the text is revered, but is it worth believing this specialist? After all, not much is clear about aging. And a conversation with a serious scientist will require as many reservations as it will not fit into any article. You politely refuse and take on something simpler.
Attempts to calculate biological age show at what stage the science of aging is at. A lot of methods have been developed, and they do not agree well with each other. But this inconsistency will indicate where to look for answers next.
Collect them all
In 2001, the first "fragility index" appeared, one of the simplest markers of aging. The researchers tested a large sample of people for five signs of fragility: unintentional weight loss, weak hand grip strength, slow walking, feeling tired and low physical activity. Those who fit at least three criteria were considered fragile by the authors of the criterion. They really had a higher risk of deterioration of health, hospitalization and death. Those who matched only one or two signs were assigned the intermediate status of fragility. This first-of-its-kind criterion did not yet allow us to assess the exact risk for each of the subjects, but with its help it was already possible to measure the risks for the population as a whole and its individual groups.
Later, on the basis of this idea, a whole forest of fragility indices grew. The number of signs has since become significantly larger and can reach hundreds, but the principle remains the same. Each attribute is a parameter that:
a) is a health defect (and not a lifestyle property, such as smoking);
b) occurs more often with age;
c) occurs at least in 1% of people in the population.
The sum of the signs should cover different areas of the body's work, that is, not only the physical condition, but also the mental and psychological health of a person. In fact, these indices measure the number of defects/damages in the human body, which is why they are sometimes called defect indices. Each of the dozens or hundreds of signs is evaluated on a scale from 0 to 1, and the subject receives his "fragility score", which increases as the body ages.
The fragility index is the quintessence of the medical approach to aging, which considers old age as a set of age–related diseases. Therefore, such indices are often used in medical work, and they help to predict, for example, the need of an elderly person for intensive care. In rare cases, they also work for young people, because every defect, every age-related disease seriously impairs their survival. However, with their help, it is difficult to predict anything other than the risk of death, so they are of little use to relatively healthy people. In addition, the fragility indices do not tell us anything about the cause of aging and measure only its consequences.
Nevertheless, the principle itself – to use not one parameter, but the sum of markers – is certainly correct, because it takes into account the heterogeneity of the population. And now researchers are trying to build multifactorial models to estimate biological age.
For example, in the course of the American CALERIE study, which is devoted to calorie restriction, scientists track 18 different signs: from the amount of cholesterol and hemoglobin to the health of the mucous membranes. For each of them, they built a curve of changes from 26 to 38 years and built a model that predicts biological age based on the sum of changes in all parameters multiplied by certain coefficients. Attempts to estimate the biological age of each individual participant have shown that the population of even young people is highly heterogeneous. According to the calculations of the experimenters, the biological age of the subjects, who are 38 years old according to the passport, can be from 30 to 50. In this study, it is especially important that scientists work with young healthy people whose risk of death or the development of diseases is almost impossible to assess. Probably, such a complex age marker will appear in the near future. The only question is what specific parameters will be included in it.
He's counting us
What do 5, 10 or even 100 parameters mean in comparison with the complexity of the organization of the human body? In order not to suffer from choosing the most accurate biomarkers, a number of scientists use a fundamentally different approach to calculating biological age – artificial intelligence. Recently, many papers have been published in which doctors train neural networks to diagnose a variety of diseases, so why not apply them to aging?
In the USA, a group of researchers led by scientist Alex Zhavoronkov is doing this. They train artificial intelligence on a variety of signs of aging. For example, in 2018, they taught him to measure a person's age from a photo of a face. Recognizing the eye and the surrounding skin, the program determined the age with an accuracy of two to five years. At the same time, the most significant feature turned out to be wrinkles in the corner of the eye: as soon as they were covered in photographs, elderly people began to look like little children to the neural network.
In 2019, Zhavoronkov's group took up blood tests. The parameters they measured resemble a standard biochemical test: the number of different shaped blood elements, concentrations of proteins, fats, glucose and metabolic products – urea, creatinine (a metabolic product in muscles that is usually excreted by the kidneys), bilirubin (spent hemoglobin). And again, artificial intelligence determined the age of the subjects with an accuracy of six years.
Along the way, it turned out that for different genders and ethnicities, a different set of markers has to be taken into account. For example, the sodium concentration played an important role in calculating the age of South Koreans, but did not depend significantly on the age of Eastern Europeans. And this is another feature that needs to be kept in mind when we are dealing with biological age: it is worth checking every time on the basis of which sample a method for determining it has been developed. What makes a Chinese old will not necessarily work for a Hindu.
The next in line are microbes. Despite the fact that we are still not sure exactly how different representatives of the intestinal microflora affect human health, artificial intelligence has already counted them. By comparing the relative number of different types of bacteria in the intestines of people, the neural network has learned to determine the age with an accuracy of about four years.
Interestingly, the relationship of certain microbes with the determination of age did not depend on whether they favor health or, on the contrary, harm. In this sense, the "aging-friendly" bacteria seem particularly curious. Probably, these are the newly acquired inhabitants of the intestine, which we talked about in the chapter "Microbes" and which preserve the necessary diversity inside the aging organism and maintain inflammation at the right level. But another explanation is also possible: these microbes may be a reflection not so much of old age as of the lifestyle of the generation that has now entered old age: low physical activity, high consumption of sugars and semi-finished products. And if this is true, then in the future scientists will have to adjust the method of determining age not only depending on gender or race, but also on the generation and its lifestyle.
Works using artificial intelligence, of course, expand the field of view and allow you to discover what classical methods miss. At the same time, not all parameters that are measured at the same time meet the criteria of biomarkers. Therefore, a neural network capable of determining a person's age turns out to be very useful functionally, but raises many questions from a biological point of view.
Which of the parameters that artificial intelligence takes into account are really important? Which ones are relevant to the causes of aging, and which ones reflect only the lifestyle? Now artificial intelligence is guided by an algorithm incomprehensible to us and gives unsupported predictions, like a Greek soothsayer. In order to get reasons to believe his predictions, we have yet to identify and verify the main markers on which he relies.
…
Difficulties of recalculation
The list of potential markers of biological age does not end there. DNA fragments circulating in the blood, the amount of sugar residues on extracellular proteins, and even the features of the brain in MRI images are offered as candidates. In one recent study, the age of the brain was calculated by the amount of oxygen consumed per unit of glucose. Glucose cleavage without oxygen was considered a "childish" sign, and full oxygen respiration was considered "adult". This method predicted age with an accuracy of only 8.5 years, but the brains of women turned out to be on average four years younger than the brains of men. There are many similar examples, and the number of candidates for biomarkers continues to grow.
The problem is that their predictions do not agree well with each other. And if markers within each group can still be brought to a common denominator – for example, all types of epigenetic clocks can be calibrated equally – then the differences between the groups remain profound. In different studies, they behave differently: somewhere Hannam's watch (but not Horvath's) allows predicting the risk of a decrease in mental abilities and motor skills, in other work, only Horvath's watch is associated with the risk of developing cardiovascular diseases and obesity. In the third study, the fragility index determines biological age much more accurately than the methylation clock, and in the fourth, none of the markers could predict any of the age signs accurately enough.
Perhaps it's the narrow "specialization" of most biological markers, which turn out to be indicative only in their "own" field. Lipid concentrations are closely related to obesity, brain MRI is associated with mental abilities, telomere length is associated with regeneration, and so on. But if this is the case, can we judge the risks to the body as a whole by the age of one organ or organ system?
Strictly speaking, we are not sure that all parts of the human body age at the same pace, and to talk about it, you need to have a common aging parameter for all. For example, epigenetically, most tissues (though not all) are approximately the same age, but the number of senescent cells in them is different.
In this sense, it is interesting to observe patients who have undergone a blood transfusion or organ transplant – after that, cells of different biological ages are found in their bodies. As the measurements show, staying in the same body does not smooth out the age difference. And if the donor was younger than the recipient, then his cells continue to live in their own time, remaining younger than the surrounding tissues – at least, according to the epigenetic clock.
Anyway, there is no single standard for all organs yet, just as there is no single biomarker suitable for all experiments. Each parameter used solves its specific task; in some studies, researchers are specifically looking for individual markers for different areas of the body's life. And this has its own logic: the more specific a parameter we measure, the better we understand how it is formed and under the influence of what it can change.
When we try to find one marker for the whole organism, the question immediately arises: what exactly are we actually measuring? Telomeres indicate whether cells are ready to divide, epigenetic clocks indicate how well a cell repairs its DNA or how well it maintains genes in a hyped state. These two markers almost never coincide with each other in predictions. Perhaps this suggests that each marker measures the thickness of its own pillar of aging – and then it is pointless to try to link them together.
This is probably the trouble of biohackers who are trying to measure many parameters of their body and adjust them to "optimal" values. There are incredibly many markers, and each of them individually may mean nothing (just as each individual section of methylated DNA is practically unrelated to biological age) or give results that do not coincide with other predictions. Therefore, it is unlikely that one day we will be able to find one specific parameter that will answer all our questions.
We find ourselves at a dead end: it is impossible to find one marker, one for all, and many smaller markers still do not agree well with each other and do not give biological explanations. This is the same problem that faces the fighters against aging: it seems that we are no longer destined to open one magic pill, and it is unlikely that we will be able to fix everything in parts, as Aubrey de Grey suggests. The list of changes that we have compiled on the pages of this part leaves no hope for an easy repair. In the next part, we will try to find the golden mean and talk about how the search for the causes of aging helps to find out what can be done with it and which recipe for the "elixir of youth" seems most plausible today.
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