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The emergence of large-scale, population-based biobanks has fundamentally transformed genetic epidemiology, providing well-powered datasets to rigorously investigate the genetic architecture of complex human traits and diseases. In this presentation, I will examine the integration of multi-omics and multi-modal data, including genomics, transcriptomics, and proteomics, with a primary focus on its application to understanding the genetic basis of complex traits. First, I will discuss gene discovery through large-scale genetic association studies within and across populations in diverse global biobanks. These comprehensive studies identified both common and rare protein-coding variations associated with complex traits, including psychiatric and neurodegenerative disorders. Second, to bridge the critical translational gap between genetic associations and biological functional impact, I will discuss the development and application of advanced statistical methodologies, including Mendelian randomization, fine-mapping, and molecular quantitative trait locus (QTL) integration. Finally, I will discuss how linking these multi-omics data with longitudinal electronic health records can significantly enhance our understanding of disease etiology and accelerate human genetics-driven drug target discovery and precision medicine.