The integration of omics technologies, such as genomics, proteomics, and metabolomics, has enabled researchers to uncover complex biological mechanisms underlying disease. In a recent study, Loh et al. used a multi-omics approach to investigate the liver-derived protein INHBC and its role in cardiometabolic health. Through bidirectional Mendelian Randomization and phenome-wide analysis, they identified INHBC as both a driver and consequence of metabolic dysfunction, including obesity, dyslipidemia, and inflammation.
The study revealed that INHBC contributes to coronary artery disease risk by altering lipid levels and is associated with renal and liver traits. Functional assays demonstrated that INHBC, via activin C, signals through the ALK7 receptor to suppress fat breakdown in adipose tissue. These findings position INHBC as a potential biomarker and therapeutic target. Overall, this work illustrates how omics tools can move beyond correlation to reveal causality and provide mechanistic insights with translational relevance in complex disease pathways.