Biological age of a person can be determined by the carotid artery
To determine the biological age of a person is possible on the condition of his cardiovascular system. According to scientists, the definition of this indicator will play a major role in the development of methods of anti-aging.
The article was published in the journal Aging. The research team included experts from the Institute of molecular biology RAS, Russian gerontological scientific clinical center, MIPT and other prestigious research centres, surveys were carried out at the National center for preventive medicine and the Center for gerontology.
Biological age — a concept that reflects the condition of the body.
For a healthy average person, it corresponds to his chronological age, i.e. age “passport”.
In the aging process, these two measures may differ due to various factors: the environment, bad habits, the manifestations of hereditary diseases.
The basis of the study lay the ultrasound of the carotid arteries and tonometry. With the help of machine learning the formula has been obtained, is able to predict age in healthy individuals with an accuracy of 6.9 years for men and 5.9 years for women.
The study also tests were conducted on patients with hypertension and type II diabetes. The test results showed that the biological age of those suffering from such diseases in average of three years above their actual age.
The authors of the study as a source of information about the body chose the cardiovascular system, namely parameters such as the minimum thickness of the middle layer of tissue in the carotid artery, pulse wave velocity, width of carotid artery (stenosis degree) and augmentation index — the ratio of pressure peaks in the pulse wave.
The researchers analyzed data on 303 patients aged 23 to 91 years, passing the examination in the Center for preventive medicine in Moscow in 2012. Among them 199 women and 104 men.
According to the results of work, scientists have deduced the formula in which biological age is expressed with certain coefficients using these four parameters.
The selection of coefficients was carried out using machine learning, namely, robust regression. Bioinformatic Alexander Fedenev, of the Institute of molecular biology. V. A. Engelgardt of RAS, first author, adds: “This model (robust regression — approx. Indicator.Ru), in addition to a good accuracy also demonstrates a simple interpretation of the result: you can definitely tell how to change the predicted age when the change of the measured parameters. It is worth noting that the most important role is still played by high-quality data. With an extensive database with a variety of biomarkers we were able to identify the strongest factors that helped to achieve a low prediction error even when using relatively simple and compact model.”
The method of robust regression is similar to that familiar to us at school using the least squares method is an attempt to approximate the experimental dependence of a certain formula that is to choose the variables in the formula so that the resulting curve is the most consistent with experimental data.
To check the correctness of the new technique, the scientists decided to compare computed their indices of biological age with other methods of assessing the condition of the body. The correlation between the calculated biological age and the “Framingham CVD score” — the risk assessment of cardiovascular diseases based on ultrasound of the aorta — was higher than the correlation with chronological age.
It was also compared with other methods of processing the same data used by scientists in their study: the results of the work compared with the statistical method Clemery-Dubula. Again, the correlation of results with biological age was higher than chronological.
Together with the fact that according to statistics from the world health organization is cardiovascular disease becomes the leading cause of death in the aging process, it can be argued that scientists developed technique is an effective method of determining the biological age. And the ability to quickly and reliably identify biological age is the key to successful development of anti-aging.