疾病
基因组学
生物
计算生物学
生物信息学
组学
全基因组关联研究
数据科学
人类遗传学
人口
精密医学
肾脏疾病
转化研究
危险分层
医学
梅德林
功能基因组学
遗传数据
基因
遗传变异
科学发现
遗传关联
基因调控网络
人类疾病
人口分层
多样性(政治)
风险评估
遗传多样性
作者
Andréa R. V. R. Horimoto,Nora Franceschini
出处
期刊:Hypertension
[Lippincott Williams & Wilkins]
日期:2026-07-22
标识
DOI:10.1161/hypertensionaha.126.26092
摘要
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.
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