This project addresses the critical need for reliable sarcopenia biomarkers to enable early diagnosis and intervention. Our primary research question is: can we identify novel, functionally relevant biomarkers by integrating genomic and transcriptomic data?
Our scientific rationale is that a multi-omics approach can overcome the limitations of single-platform studies. GWAS studies identify genetic associations but lack functional context, while RNA-sequencing studies reveal expression changes but not the underlying genetic causation. By combining these two data streams, we can pinpoint genes that are both genetically linked and functionally dysregulated in sarcopenia, leading to the discovery of more robust and biologically meaningful biomarker candidates.
Our methodology will involve three main phases. First, we will use UK Biobank data to perform a GWAS to identify genetic variants associated with sarcopenia phenotypes (e.g., grip strength, lean mass). Second, we will analyze external public RNA-sequencing data from sarcopenia patient cohorts to find differentially expressed genes. Third, we will integrate these findings through eQTL analysis to identify the most promising biomarker candidates.