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This review discusses the implications of frameworks leveraging genetic admixture and multiomics data for advancing gene discovery in cardiovascular and kidney disease research. By broadening gene discovery efforts to additional populations that have a disproportionately high risk of disease and leveraging genetic diversity in admixed populations, studies can identify population-enriched risk variants that traditionally have been missed in genome-wide association studies. The use of multiomics approaches, including the transcriptome, proteome, and metabolome, advances a mechanistic understanding of disease beyond associations. As single-cell omics technologies continue to improve, their integration into gene discovery may help uncover cell-type-specific regulatory pathways and more precise biological contexts. The full potential of these approaches depends on sustained investment in diverse, well-characterized omics data sets, methodological innovation in multiancestry statistical approaches, and interdisciplinary collaboration bridging genomics, epidemiology, and clinical medicine. These efforts will need to be translated into clinically actionable insights, including ancestry-informed risk stratification and targeted therapeutics, to improve outcomes for cardiovascular and kidney diseases.