Metabolomic approach identifies predictive model for weight loss with New Nordic Diet
02 Aug 2023 --- A scientific model that predicts the likelihood of achieving a clinically significant weight loss on the New Nordic Diet (NND) has been identified by researchers from the University of Copenhagen, the College of Applied Medical Sciences in Saudi Arabia and the Novo Nordisk Foundation.
The NND, like the Mediterranean diet, focuses on whole foods typically found in the Nordic regions of Norway, Denmark and Iceland. This new study demonstrates that models based on an untargeted multi-platform metabolomics approach can optimize precision dietary treatment for obesity.
The NND is similar to the Mediterranean diet in that both include fresh, plant-based foods, fish and eggs and small amounts of dairy, red meat, sweets and processed foods. However, the NND advocates organic foods heavily and includes whole grains such as rye and barley, mushrooms and loganberries.
One major difference is the oil incorporated is mainly rapeseed oil, popularly known as canola.
The study used machine learning to build the predictive model, which serves as a biomarker signature and could be used to optimize weight loss success.
Finding the ideal model can be central to applying precision nutrition in practice, as the results show that the optimal diet for successful weight loss may differ between individuals.
What the metabolomics data says
According to the researchers, results from randomized controlled trials show that no single diet performs better in people with obesity. There is always large inter-individual variability in weight changes.
The current study combined clinical baseline data with baseline urine and plasma untargeted metabolomics data from two different analytical platforms. This resulted in a data set with 2,766 features to determine a “predictive” model. The findings were published in Frontiers in Nutrition.
In total, 181 Danish participants were assigned to the two diet groups, and after 26 weeks, 91 and 56 participants completed the study in the NND and the Average Danish Diet (ADD) arms. Participants were encouraged to maintain regular physical activity throughout the intervention period.
While individual responses to diet vary significantly, predictive models could help with weight loss in complex cases.
Diet responders maintained a weight loss of 4.3% in a 12-month follow-up period. Meanwhile, researchers from the Osaka Metropolitan University in Japan have investigated what stimulates the brain to cause overeating and discovered a genetic mechanism associated with high-calorie, food-fueled obesity.
Finding obesity solutions
Obesity has reached pandemic proportions over the last decades and is a significant risk factor for several chronic illnesses, including cardiovascular diseases, dyslipidemia, hypertension, insulin resistance, Type 2 diabetes, non-alcoholic fatty liver disease and cancer.
According to the WHO, more than half of the EU’s adult population is overweight or obese, prompting stronger calls for stricter regulations and better nutrition labeling.
Scientists have long searched for the optimal diet to treat obesity, and the view on which diet is best has shifted over time. The 1980s and 1990s have seen a focus on low-fat diets, whereas recently, the focus has been on reducing sugar consumption and carbohydrates and adopting a more plant-based and fiber-rich diet.
The current study demonstrates that models based on an untargeted multi-platform metabolomics approach can optimize precision dietary treatment for obesity.
Different individuals may succeed on other diets, emphasizing the need for precision nutrition. The researchers posit that inter-individual variability in weight loss responses likely has a metabolic nature.
Differences in metabolic processes might be reflected in the metabolome, as metabolites are the end-products of cellular regulatory processes. Their levels in different biological matrices reflect the biological response to genetic, microbial or environmental changes.
By Inga de Jong
