Leveraging longitudinal data to boost statistical power for gene–environment interaction analysis (opens in new tab)

Gene–environment interaction (G×E) analyses play a crucial role in advancing genetic discovery, addressing missing heritability, and facilitating precision medicine. However, existing G×E methods are mostly designed for cross-sectional data, limiting the utility of longitudinal data. Here we propose SAGELD, a scalable and accurate genome-wide G×E method for longitudinal traits that controls for sample relatedness in large-scale datasets. SAGELD uses matrix projection to construct test statist...