Associate Professor Morten Arendt Rasmussen from the Department of Food Science at the University of Copenhagen (UCPH FOOD) in Denmark is developing a model for a new personalized dietary profile. He hopes the model will one day be able to relieve the symptoms of inflammatory diseases.
“If we can determine which people have some unfortunate eating habits with regards to their body and health status, we will theoretically be able to change the dietary recommendations so that the individual will experience a healthier body If they follow the recommendations. This is the goal and framework for our research,” explained Rasmussen.
Eventually he hopes the findings of his work will result in an experiment in which the researchers will investigate whether a tailored diet can help improve the health of young people with conditions like asthma, allergies and eczema.
“It will be close to the healthy diet profile we already know, but it will have some modifications for the individual. The question then is how great of an effect the diet really has in relation to the inflammatory diseases – this research will give us an idea of that,” said Rasmussen.
Personalized nutrition for symptom relief
The researchers are using a cohort from the Danish – Copenhagen Prospective Studies on Asthma in Childhood (COPSAC project). While the project is centered on asthma, Rasmussen said they expect that the model could be applied to other inflammatory conditions such as multiple sclerosis, rheumatoid arthritis, allergies, eczema and more.
Rasmussen told Nutraingredients-USA that he was motivated to research this area after observing an overlap between immunological diseases such as asthma and metabolic conditions like obesity and type 2 diabetes.
Subjects
COPSAC2000 is a division of the COPSAC project, which is a prospective clinical mother-child cohort study of 411 children of asthmatic mothers. The study is designed to assess gene-environment interactions in the origin of atopic diseases with an aim to identify early-life exposures that can be modified to improve preventive strategies. The children attend the COPSAC clinical research unit from birth until adolescence at scheduled clinical investigations. Additional visits are arranged at onset of any respiratory or skin symptom.
Because these subjects have been studied since they were infants, the researchers were able to acquire a large amount of data and implement it into the calculations of their model.
“The group is similar to all others on a dietary level and the only thing that differentiates them is that they all have a mother that has asthma. In the cohort, there are some who are overweight and some who have eczema and asthma that compromise their quality of life. If we can examine their metabolism and determine whether there are any dietary components that aggravate their illness, or that they may be missing that would help them to improve their health, then it will be a huge gain – both for them and for society,’ said Rasmussen.
Rasmussen added that in order to create a personalized diet profile, users would conceivably just need to provide age, height, weight, gender, as well as some genetic information obtained from a hair or stool sample.
Methods
The researchers are looking at how the body digests food by using two different methods to find a standard while examining cause and effect relationships.
Method one is a standardized study that uses metabolomics measured in the lab while subjects avoid any physical activity that might aid the metabolism.
“They get a cocktail of stuff that is not particularly healthy but has a high content of both fat and sugar and contains half the calorie intake you would typically have in a whole day. The participants consume the cocktail over a period of 3-4 minutes, and thus we kick the digestion quite hard to see how the body reacts,” explained Rasmussen. “We then take regular blood and urine samples to see how the body reacts and how it orchestrates a return to the normal level.”
From there the researchers measure things like fat content, cholesterol, glucose, and amino acids, to follow the development of the digestive period.
The second method is an observational study in which the participants choose what they want to eat while researchers monitor eating habits via a continuous glucose monitor (CGM) and participant-provided photos.
The subjects provide photos of everything they eat and drink on cell phones—with researchers expecting to end up with as many as 16,000 pictures.
Between the two methods, researchers will acquire large data sets to paint a metabolic picture. The data sets will be compared to other information like genetics, metagenetics, lifestyle, and diseases to understand the reasons for the variation in the participants’ digestion and to see if the variation can be associated with the presence of specific diseases in the participants.
Rasmussen told NutraIngredients-USA that only the research will tell which method is best. “Clearly the CGM is better in terms of how tedious and costly the other is, but the standardized gives information on the entire metabolism not just the (most regulated part) glucose, but also lipids, lipoproteins, peptides, other carbohydrates, etc.”
Netflix style diet
Once the research wraps up and if proven effective, the food scientists are hoping to then develop a diet based on recommendations, similar to Netflix.
“Netflix is based on a recommender system. You evaluate whether the film you are watching is good or bad, and after some time the system – which now knows your preferences – will recommend new films to you. You can imagine that the films are the foods, and that the 1-5 stars assess your personal glucose level in the blood immediately after consuming the recommended foods. Then you will be able to learn which foods are good and bad for you,” said Rasmussen.
The research is funded by the Novo Nordisk Foundation, which awarded Rasmussen the Data Science Investigator grant. The grant runs through 2026, but as Rasmussen put it, "the research never really ends."
Source: First principal models, neural networks and functional graphical models for defining metabolic capacity as a tool for Personalized nutrition