Genetically-informed lifestyle changes reduce the risk of metabolic disease
Genome-wide association studies (GWASs) have identified hundreds of signals associated with obesity, type 2 diabetes and cardiovascular disease. This information can be used to generate polygenic scores, which quantify the inherited risk of disease. However, genetic information is not yet routinely used in clinical decision-making, with sufferers unaware of their genetic risk or mitigation options. “People at low genetic risk with unhealthy lifestyles could be at increased risk of these diseases, equally people at high risk but with a healthy lifestyle could be low risk,” observes Jordi Merino, Marie Skłodowska-Curie fellow from the EU-supported INTERPLAY project. “This opens up public health policy questions in the era of big data and precision medicine.” INTERPLAY investigated how lifestyle could modify genetic predisposition to diabetes and related metabolic complications and looked specifically at the role of elevated blood glucose (hyperglycaemia) in cardiovascular disease. INTERPLAY also studied the biological processes underlying food intake. Some findings have already been published and have received international recognition, including the Rachmiel Levine-Arthur Riggs Young Investigator Scientific Achievement Award in 2017.
Genes, metabolic diseases and the role of lifestyle
To identify factors associated with the development of cardiovascular disease, INTERPLAY used Mendelian randomisation analysis to establish the causal role of hyperglycaemia in the risk of the disease. In a separate study to identify markers of diabetes, INTERPLAY used data from the Framingham Heart Study, finding a set of 19 metabolites that could identify individuals at risk, even when deemed low risk clinically. “Importantly, our analysis showed that metabolic alterations that contribute to the earliest stages of diabetes, are also important for the development of cardiovascular disease,” explains Merino. To study interactions between genetic susceptibility and diet/lifestyle – including fat consumption, nutrients and physical activity – INTERPLAY used data from European and American observational studies and clinical interventions. “We wanted to identify subgroups of individuals, based on their genetic profile, who might benefit most from interventions that reduce the risk of metabolic disease,” adds Merino. Using the CHARGE Consortium’s longitudinal data from over 100 000 participants, INTERPLAY showed how both genetic risk and dietary factors were associated with new-onset diabetes. The study is now published in the British Medical Journal. Using data from the American Diabetes Prevention Program, INTERPLAY demonstrated that healthy diets, alongside increased physical activity, reduce cardiometabolic risk regardless of genetic risk, with people at higher risk benefiting most. INTERPLAY also participated in a GWAS study, with a data set of 300 000 individuals, which identified 26 genomic regions associated with increased preference for foods high in carbohydrates, fat or protein. Bioinformatic analyses showed that these genes are mainly in the brain and involved with food reward processes or impaired satiety. “This, the largest analysis into the genetic influence on dietary intake, allowed us to create polygenic scores for the likelihood of obesity and related complications. Better understanding the food reward system could enable more effective treatments,” says Merino. A paper on the findings will be published by ‘Nature Human Behaviour’.
Translating knowledge into practice
Modern healthcare systems are now setting up preventive genomics clinics to empower patients. In the meantime, according to Merino, “Sharing our results with policymakers, biotech companies and food manufacturers is helping to revolutionise medicine, drug development and foods design, while opening new markets.” Merino is currently working on the launch of personalised nutrition clinical trials, to uncover molecular factors involved in adverse metabolic responses to specific foods.
Keywords
INTERPLAY, genes, genome, diet, lifestyle, medicine, carbohydrates, fat, protein, diabetes, cardiovascular disease, obesity
