Project Title

Addressing variability in body composition and fat distribution to better assess the risk of diabetes and cardiovascular disease 

Background

BMI is widely used to measure body adiposity. Still, it fails to capture individual differences in body composition and fat distribution, which are crucial for assessing the risk of T2D and CVD. Furthermore, BMI’s role in assessing T2D and CVD risk varies between sexes due to inherent differences in body composition and fat distribution. Understanding these differences is essential for improving risk assessment of T2D and CVD. 

Aim

Our aim is to identify sex-specific population subgroups with distinct body composition and fat distribution patterns at the same level of BMI and to assess associations of these subgroups with T2D and CVD risk. Furthermore, we aim to develop subgroup-specific polygenic scores and use them to calibrate BMI values for more precise T2D and CVD risk assessment. 

Methods

We will subgroup participants based on sex-specific body composition and fat distribution patterns. We will examine associations with T2D and CVD using data from the UK Biobank and Danish Diet, Cancer and Health cohorts. We will create subgroup-specific polygenic scores to calibrate BMI for better risk prediction of T2D and CVD and characterize underlying biological pathways by examining associations with plasma proteomic and metabolomic profiles. 

Preliminary results

Among 670 known BMI risk variants, our preliminary analyses identified eight distinct genetic subtypes with unique body composition and fat distribution patterns. We observed significant differences in cardiometabolic risk profiles between these subtypes, giving important clues to T2D and CVD risk assessment.