Nestlé research discovers 'distinct metabolic signature' for obesity
The fundamental new findings could one day be used to identify individuals more likely to be at risk of developing obesity-related health problems in addition to offering nutrition researchers a new set of biomarkers to assess the impact of diet on health, said Nestlé.
Published in PLoS One, the research team studied a group of women with visceral obesity - where excess fat is concentrated around the internal organs - and discovered they had a distinct ‘metabolic signature’ of lipids and amino acids in common, as well as specific changes in gut microbial activities.
The findings are part of a research partnership between food and nutrition giant Nestlé and General Electric which aims to find efficient and inexpensive methods of screening and monitoring body composition.
“Finding minimally-invasive, fast and reliable biomarkers to screen people for visceral obesity could help to monitor the effectiveness of different therapies,” explained François-Pierre Martin, the Nestlé scientist who led the study.
“In the future it could be an efficient and accessible way of helping to address the burden of obesity-related problems such as insulin resistance, Type 2 diabetes and cardiovascular disease," he said.
The Nestlé team noted that people who have visceral obesity are recognised as being at higher risk of developing certain related illnesses, and that the identification of the unique biomarkers could help scientists to better understand the relationship between visceral fat stores and metabolic health, as well as how lifestyle factors, such as exercise and diet, influence body composition and fat distribution.
Study details
The research team monitored 40 obese but otherwise healthy women over a two-week period at the out-patient obesity clinic of the University Hospital of Lausanne, Switzerland. They measured the women’s body composition and distribution of fat tissue with modern imaging techniques including dual energy X-ray absorptiometry (DXA) and computed tomography (CT) - using technology provided by General Electric.
The team also took blood and urine samples at regular intervals to monitor individuals’ metabolism - via metabonomic and lipidomic analysis.
"Metabolites important in predicting visceral fat adiposity as assessed by Random forest analysis highlighted 7 most robust markers, including tyrosine, glutamine, PC-O 44:6, PC-O 44:4, PC-O 42:4, PC-O 40:4, and PC-O 40:3 lipid species," wrote the team.
"The visceral fat associated amino acid and lipid signature is proposed to be further validated for future patient stratification and cardiometabolic health diagnostics."7
