The microbioma, that is, all the bacteria that inhabit the intestinal system, have revealed surprising properties in recent years. If scientists still do not know how it is evolving or if there are typical bacterial configurations, a team of researchers who studied the microbiome of thousands of different people discovered that it functions as a biological clock, making it possible to accurately determine an individual's age.
To find out how the microbiome changes over time, Alex Zhavoronkov, a longevity researcher, and his colleaguesInSilic Medicine, an Artificial Intelligence startup based in Rockville, Md., examined more than 3,600 samples of intestinal bacteria in 1165 healthy people worldwide. About a third of the samples came from people aged 20 to 39, another third from 40 to 59 years and the last third from 60 to 90 years.
Scientists then used machine learning to analyze the data. First, they trained their computer program – a deep learning algorithm called the neural network – in 95 different species of bacteria from 90% of the samples, as well as in the age of the people from whom they originated. .
Then they asked the algorithm to predict the age of the people who provided the remaining 10%. Its program made it possible to accurately predict the age of a person with a margin of error of +/- 4 years. Of the 95 species of bacteria, 39 were the most important to predict age. The search results were published to the pre-release server bioRxiv.
Zhavoronkov and his colleagues found that some bacteria became more abundant as they grew, Eubacterium hallii, which is considered important for intestinal metabolism. Others declined, as Bacteroides vulgatus, which has been associated with ulcerative colitis, a type of inflammation of the digestive tract.
Changes in diet, sleep patterns and physical activity are likely to contribute to these changes in bacterial species, says Vadim Gladyshev, a Harvard biologist who studies aging.
According to Zhavoronkov, this "microbiome aging watch" can be used as a basis for testing the speed or slowness of a person's intestinal aging and whether factors such as alcohol, antibiotics, probiotics or diet have an effect on longevity. It can also be used to compare healthy people with people with certain diseases, such as Alzheimer's disease, to determine if your microbiome has abnormalities.
About the same subject: Is the brain the second dive of intestinal bacteria?
If the idea is validated, it will join other biomarkers used by scientists to predict biological age, including the length of telomeres (the ends of the chromosomes involved in aging) and changes in the expression of telomeres. DNA in the course of life. The combination of this new watch with these other methods could provide a much more accurate picture of a person's true age and biological health.
It could also help researchers see if certain protocols, including medications and other treatments, affect the aging process. " There is no need to expect people to die from experiences of longevity Zhavoronkov says.
According to Robin Knight, a computer scientist and microbioma researcher, the idea of being able to predict a person's age according to their intestinal microbiome is "very plausible" and of "considerable interest" to scientists studying aging. Your group reviews 15,000 sampleAmerican Gut Project, a global microbiome study he founded, to develop similar age-related signatures.
But one of the challenges in developing such a watch, he adds, is that there are very large differences in the presence of bacteria in the intestines of people around the world. " It is extremely important to replicate this type of study in very different populations To determine if there are distinct signs of aging between different groups of people, says Knight.
He also does not know whether changes in the microbiome result in a faster aging of the population or whether those changes are simply a side effect of aging. InSilic Medicine constructed several machine-learning bio-clocks, which could be combined with that of the microbiome. " Age is such an important parameter in all types of diseases. Every second we change Zhavoronkov concludes.