1 Research questions:
1) How can obesity fine phenotype be classified based on DXA-assessed body composition data and metabolic markers?
2) Which genetic variants are associated with metabolic obesity, body composition phenotypes and sarcopenic obesity in the British population?
2 Objectives
1) Characterize obesity fine phenotype (especially sarcopenic obesity) linked to DXA-assessed body composition and metabolic data.
2) Identify body composition-related genetic loci through genome-wide association studies (GWAS) and perform fine-mapping.
3) Explore difference between body composition phenotype-related, sarcopenic obesity-related and metabolic obesity-related genetic loci.
3 Scientific rationale:
Previous definitions of obesity often used BMI as a representative estimate, but were limited by the measuring methods to make precise obesity phenotype classifications based on body fat distribution. Thus, Body composition GWAS research has focused on the genetics of body mass index, waist and hip circumference or simple compartments of body composition (BIA-assessed), such as bone mass, lean mass or fat mass. Also, existing studies are hindered by small sample sizes. UK Biobank’s large-scale genetic and DXA data offers a unique opportunity to address these gaps. By analyzing GWAS data and linked DXA data (different parts’ FFM, TM, FM, LM, standardisation mass, etc.), this study aims to uncover novel genetic drivers, clarify obesity fine phenotype (especially sarcopenic obesity) linked to DXA-assessed body composition and sarcopenic obesity, advance precision medicine in obesity.