In constant rise in developing and developed countries, obesity, defined as an abnormal or excessive accumulation of fat that presents a risk to health, represents a worldwide and public health concern. Obesity is a multifactorial disease resulting from the interaction of genetic and environmental factors. To date, only 7 polymorphisms have been associated with the risk of morbid obesity in populations of adult European ancestry. Body mass index (BMI) is the parameter most frequently used to diagnose obesity in the population.
This study aims to explore the genome of > 400,000 adults of normal weight and > 70,000 adults with morbid obesity (BMI ! 40 kg/m2) by meta-analysing multiple large cohorts of European ethnicity, to discover new genetic variants predisposing to obesity, to explain BMI variations in the different obese categories, and apply these results to the general population. For up to 3 years, we will highlight the polygenic architecture of morbid obesity, perform genome-wide association studies (GWAS) meta-analyses, score regression analyses and post-GWAS augmentations with state of-the-art bioinformatics approaches to decipher biological functions and pathways linked to morbid obesity.
Current obesity treatment programs however have largely failed to halt the obesity epidemic, despite huge financial investments that can represent up to 10% of national health expenses. Exploring the causes and consequences of obesity might improve prediction, prevention and care in the long run. This project holds the potential for discovering new genes predisposing to obesity, decipher the complex gene network underlying its physiopathology, understand the molecular links to its comorbidities (cardiometabolic diseases, cancers, type 2 diabetes), and identify novel molecular targets for innovative medications.
