As Dr Susan Wopereis, principal scientist at Dutch applied research institute TNO, explained in her presentation, nutrition is becoming increasingly personal as the industry develops more tools to quantify the impact of lifestyle on health.
“There is growing recognition that lifestyle factors, including environment and diet, predispose people to chronic diseases such as type 2 diabetes and cardiovascular disease,” she said.
To that end, TMO has launched a research program focused on personalized health to combat lifestyle-related diseases, aiming to develop knowledge, methodologies and prototypes that public and private partners can use to enhance their services and products.
It leverages data and artificial intelligence (AI) to create customized lifestyle recommendations, delivered through various formats such as apps and wearables, providing real-time, actionable advice based on continuous monitoring.
“The ultimate goal is to reach different consumer groups and improve the overall health of society,” Wopereis noted.
Evolving understanding
Vimal Karami, professor of nutritional genetics and nutritional genomics, explained to the audience that the concept of personalized nutrition has evolved over the past decade.
Originally focused on developing dietary treatments based on an individual’s genetic makeup, known as nutrigenetics, the term “precision nutrition” is now used to reflect a more holistic approach.
Precision nutrition considers four key components — nutrigenomics, metabolomics, gut microbiome and changes in epigenetic markers — that work in parallel every time we eat food, highlighting the complexity and interconnectedness of how diet impacts the body, Karami explained.
While understanding the components is important, the next obstacle is combining all the information, and currently there is a lack of a single study that comprehensively synthesizes all this information.
“One of the biggest challenges is how to integrate all this information in one container and develop a so-called precision nutrition plate for personalized meals,” he said. “Because if we could do that, it would revolutionize the field of nutritional science.”
Deep phenotyping, which involves detailed analysis of genetic, epigenetic, gut microbiome and social factors such as age and sleep patterns, is essential to advance the field of precision nutrition, according to Karami.
Deep phenotyping requires integrating data through big data analytics and leveraging AI platforms to drive personalized health solutions.
“Though still in the development stage, precision nutrition holds promise as a customized dietary strategy to prevent cardiometabolic disease,” he said.
Next steps
Together with his research team, Karami is developing a comprehensive model aimed at predicting the onset of metabolic diseases in adulthood and suggesting precision nutrition solutions based on individual factors.
The study focused on 12,000 children in India, Ethiopia, Vietnam and Peru, looking at nutritional genetics, metabolic markers and social factors such as access to supermarkets and fast-food restaurants.
“Currently, such evidence is lacking in developing countries, and this continues to be a major barrier to providing personalized nutrition for all.
“We are the first to conduct a nutrigenomics study in a low- and middle-income country,” he said. “This is important because genetic makeup varies greatly between individuals and ethnicities, and this genetic diversity means that each person’s DNA is unique, making it very important to take ethnicity into account in genetic studies.”
Technological advances
As Wopereis explained, TNO aims to translate scientific evidence into real-world applications through prototyping, collaboration and showcasing clinical evidence, which relies heavily on technological developments.
“Our institute is focused on developing technologies, especially remote and continuous monitoring using wearable devices, with an emphasis on both laboratory and home measurements,” she said, explaining that personalized interventions are more effective than uniform routine monitoring.
“Furthermore, we are looking at developing artificial intelligence and algorithms to address the challenges we face.”
But she worries that technological advances could widen disparities in health outcomes between different socioeconomic groups.
“Of course I think there are opportunities in high tech, but I am also concerned about lifestyle diseases and the demographics that suffer from these lifestyle chronic diseases that often affect people from poor socio-economic backgrounds,” she noted. “In the Netherlands, on average, people with a higher socio-economic status live six years longer and spend 15 fewer years with chronic diseases.
“I think the big challenge is to take advantage of all of the high-tech development we have without creating even greater handicaps between higher and lower socioeconomic groups.”
