Identification of Asian-specific genetic association with fat and lean muscle mass distribution
Main Applicant – Dr Liu Boxiang, Assistant Professor, Pharmacy & Biomedical Informatics
National University of Singapore

Previous body composition GWAS studies have been limited to the European population and relied on waist-hip ratio measurements without incorporating functional imaging or whole genome sequencing.

However, this study aims to identify genetic risk loci specific to Asian populations associated with fat and lean muscle mass distribution and their role in cardiometabolic diseases. We will use deep-learning based image segmentation and pattern recognition to analyze DEXA scans and obtain precise measurements of fat and lean muscle mass.

By focusing on the SG100K dataset and integrating it with the UK Biobank (UKBB), we address the unique genetic makeup of Asian populations, which are underrepresented in current genetic research.

Through a multi-ethnic meta-analysis and Mendelian randomization, we will discover common and rare genetic variants affecting body composition with causal relationships with cardiometabolic diseases. Colocalization analysis will further link risk genes with disease traits, followed by functional validation to confirm mechanistic links.

The findings are expected to enhance early detection, prevention and targeted treatment strategies for cardiometabolic conditions, ultimately contributing to more inclusive and precise public health interventions.

This research underscores the importance of diversity in genetic studies and aims to fill critical gaps in our understanding of genetic influences on metabolic health in Asian populations.