Molekylära mekanismer bakom distributionen av kroppsfett

Tidsperiod:

1 januari – 31 december 2020

Projektledare:

Mathias Rask-Andersen

Finansiär:

Hjärt-Lungfonden

Bidragstyp:

Projektbidrag

Budget:

474 000 SEK

Background:

Distribution of adipose tissue to discrete depots within the abdominal cavity has been suggested as BMI-independent risk factors for cardiometabolic disease. The biological mechanisms that underlie distribution of body fat to these depots, as well their causal effects on disease are poorly understood. Identifying the genetic factors that influence body fat distribution can inform studies into its molecular underpinnings and lead to novel interventions for disease prevention and risk reduction. However, abdominal adipose tissue distribution is difficult to quantify due to technical requirements and high costs.

Aims:

In this project, I will circumvent this problem by constructing prediction models for visceral adipose tissue (VAT), abdominal subcutaneous tissue (SAT) as well as their internal relationship: the VAT/SAT ratio, from common anthropometric traits and bioelectrical impedance measurements in the UK Biobank (UKB). The prediction models will then be utilized to estimate these traits in the full UKB (N=500,000), and perform genome-wide association studies (GWAS) for these traits with unprecedented statistical power.

Project plan:

Prediction models for VAT, SAT and the VAT/SAT ratio is developed in a subset of 6,000 UKB participants with MRI body composition data. Body fat distribution data is then be extrapolated to the entire UKB cohort of half a million participants. GWAS is performed for body fat distribution estimates and findings from GWAS are then analyzed with bioinformatic tools to determine the molecular pathways and tissues that are involved in body fat distribution. Candidate genes and genetic variants are prioritized from the genetic findings and these will be tested in relevant model systems in order to characterize the functional implications of associated genes and genetic variants.

Significance:

Disseminating the biological mechanisms that underlie body fat distribution can lead to new opportunities for pharmacological intervention. Since distribution of body fat affects disease risk, information on the genetic variants that influence body fat distribution can also be utilized for risk assessment in a clinical setting. Epidemiological studies are, by nature, correlational. I will therefore use Mendelian randomization to examine how body fat distribution causally affects the disease risk by using genetic variants with known effects as instrumental variables