B3407 - Identifying genetic variants predisposing to overeating behaviour - 10/01/2020

B number: 
B3407
Principal applicant name: 
Fotios Drenos | Brunel University London and University College London
Co-applicants: 
Dr Terry Dovey
Title of project: 
Identifying genetic variants predisposing to overeating behaviour
Proposal summary: 

Obesity has been associated with a number of life threatening common diseases and is cited as the driving force behind poor health from early ages in both developing and developed countries. Obesity is the product of a complex interplay between our biology and our environment, with our behaviour playing a major role on how these interact. Previous studies have shown that targeted behavioural changes are effective obesity interventions for both short-term weight loss and long-term weight management. Although behaviour is a complex characteristic shaped by our culture, society and upbringing, similar to other complex human characteristics, it also has a genetic component that predisposes us to respond to environment cues in a specific manner. These genetic predisposition markers usually confer poor prediction of a specific individual’s complex phenotype or behaviour, but in larger population samples, they can provide information for existing patterns that can help us plan effective population level interventions and assess the causal patterns associated with them.

Impact of research: 
To identify the genetic predisposition of overeating and the markers predicting the behaviour. To use this information to better understand overconsumption and the potential behavioural interventions that can be used to avoid overeating and associated health problems.
Date proposal received: 
Monday, 11 November, 2019
Date proposal approved: 
Tuesday, 12 November, 2019
Keywords: 
Genetic epidemiology (including association studies and mendelian randomisation), Behaviour - e.g. antisocial behaviour, risk behaviour, etc., Diabetes, Eating disorders - anorexia, bulimia, Obesity, Computer simulations/modelling/algorithms, GWAS, Metabolomics, BMI, Cardiovascular, Genetic epidemiology, Genome wide association study, Mendelian randomisation, Metabolic - metabolism, Psychology - personality