B3859 - Analysis of 3D body scans genetics of body morphology correlation with measure of adiposity and cardiometabolic consequences - 08/09/2021

B number: 
Principal applicant name: 
Christoffer NellÄker | NDWRH, University of Oxford (United Kingdom)
Michael Suttie, Abigail Fraser, Professor, Cecilia Lindgren, Professor
Title of project: 
Analysis of 3D body scans: genetics of body morphology, correlation with measure of adiposity and cardiometabolic consequences.
Proposal summary: 

Obesity is a major risk factor for diseases ranging from diabetes, heart conditions and even cancers. However, it is also well established that it is not only the amount of fat in the body that confers risk for various diseases but where the fat is distributed. There are a number of ways adiposity and body composition can be measured, but it is an ongoing area of research as to what measures are best for understanding the risk of disease and the genetic underpinnings of why this happens.
Body mass index (BMI) is a measure of body size but is a crude indicator of body composition, taking into account only a height-weight ratio. The gold standards to measure specific adipose tissue distribution and body composition involve either MRI, which is costly, or CT imaging, which requires unnecessary exposure to ionising radiation. 3D imaging is a non-invasive, cost-effective method of capturing surface geometry. Whole-body 3D scans can provide a detailed, geometrically accurate representation of body morphology and physical composition. We propose to analyse 3D body scan data collected as part of the ALSPAC study to examine how body shapes can be used to investigate genetics and the risk of cardiometabolic diseases.

Impact of research: 
We hope to elucidate if 3D body scan data could become a valuable anthropometric tool for health outcome predictions in the future. These instruments are being explored for non-medical purposes such as the fashion and online retailer industries, and could constitute a minimally invasive clinical tool in the future.
Date proposal received: 
Tuesday, 24 August, 2021
Date proposal approved: 
Wednesday, 1 September, 2021
Genetic epidemiology (including association studies and mendelian randomisation), Obesity, Computer simulations/modelling/algorithms, Cardiovascular