About
First defined by Rosenberg et al. in 1989, sarcopenia refers to age-related loss of skeletal muscle mass and function, posing heavy burdens on healthcare worldwide. Nevertheless, its genetic underpinnings and risk factors are yet to be unravel. We aim to 1) identify novel risk factors, candidate genes and biological links involved in sarcopenia; 2) investigate causal associations of putative risk exposures with sarcopenia. As a complex human trait, polygenic basis has been postulated for sarcopenia. Genome-wide association studies are powerful in the identification of candidate genes. The availability of genome data and electronical health records in a largest population (~500,000 in UK Biobank and ~300,000 in FinnGen) paves a way for this analysis. With the help of computer programming, big data, and biology et al., bioinformatics is a powerful tool to help researchers understand and unveil patterns in biological data. Therefore, in the first part, we will employ several bioinformatic tools to identify risk genes for sarcopenia. In the second part, we will testify the causality between numerous potential risk factors and sarcopenia. The study will hopefully provide hints at precise treatment targets and effective prevention strategies for sarcopenia, hence, be of great significance to the public health. The project takes three years.