Using computer analysis to create diets that prevent disease
New research has used computer analysis to help design specially tailored diets that could help prevent disease.
Researchers of Chalmers University of Technology in Sweden, have developed a new mathematical model for the interaction of gut bacteria that could help design new probiotics and specially adapted diets to prevent disease.
The studies, published in the journal PNAS, involved regular measurements of health indicators, which the researchers compared to predictions made from their mathematical model, which was found to be very accurate in predicting several variables, including how the transition from liquid food to a solid food in Swedish infants affected their intestinal bacterial composition.
Modeling of regimes
The article describes the performance of the model when making predictions for two clinical studies, one involving Swedish infants and the other involving obese adults in Finland. In addition to accurately predicting several variables, the team also measured how the gut bacteria of obese adults changed after switching to a more restricted diet, which was also found to be reliably accurate.
“Gut bacteria have an important role to play in health and disease development, and our new mathematical model could be extremely useful in these areas,” says Jens Nielsen, professor of systems biology at Chalmers, who led the research .
“These are very encouraging results, which could allow the computerized design of a very complex system. Our model could therefore be used to create personalized healthy diets, with the ability to predict how adding specific bacteria as new probiotics could impact a patient’s health.
How different bacteria grow and function in the intestinal system is influenced by a variety of factors such as what other bacteria are already present and how they interact with each other, as well as how they interact with the host and environmental factors such as the diet we eat. To make predictions about the behavior of bacteria, one must first understand how these bacteria are likely to act when they enter the gut or how a change in diet will affect gut composition, for example whether they will be able to break down. develop there, how they interact. with and possibly affect the bacteria that are already present in the gut, and how different diets affect the gut microbiome.
“The model we have developed is unique because it takes all these variables into account. It combines data on individual bacteria as well as how they interact. He also includes data on how food moves through the gastrointestinal tract and affects bacteria along the way in his stones. These can be measured by looking at blood samples and looking at metabolites, the end products that form when bacteria break down different types of food, ”says Nielsen.
The data to build the model was gathered from many years of pre-existing clinical studies. As more data becomes available in the future, the model may be updated with new features, such as descriptions of hormonal responses to food intake.
Working with a bacterial composition offers the potential to influence disease progression and overall health through treatment with probiotics, which are carefully selected bacteria that are believed to help improve health.
Neilson said, “Changes in bacterial makeup can be associated with or signify a large number of diseases, such as obesity, diabetes or cardiovascular disease. It can also affect the way the body responds to certain types of cancer treatments or specially developed diets. “
Nielsen and her research group will use the model directly in clinical studies and are already participating in a study with Sahlgrenska University Hospital in Sweden, where elderly women are being treated for osteoporosis with the bacteria. Lactobacillus reuteri.
Treating cancer with antibodies is another area where the model could be used to analyze the microbiome, helping to understand its role in why some patients respond well to immunotherapy and others do not.