A single-cell map of hypertension
Qiongzi QiuiD, Yong LiuiD, Hong XueiD, Rajan PandeyiD, Jing LiuiD, Lishu HeiD, Pengyuan Liu, Bhavika TheraniiD, Vinod D. KumariD, Jing HuangiD, Shima Sadri, Maya GuentheriD, Kristie UsaiD, Michael N. GrzybowskiiD, Mark A. Vanden AvondiD, Andrew s. Greene, Allen W. CowleyiD, Sridhar RaoiD, Aron M. GeurtsiD, Mingyu LiangiD
Abstract
Hypertension is a leading risk factor for disease burden and death worldwide. Several organ systems are involved in the development of hypertension, which contributes to stroke, heart disease, and kidney disease. Despite the broad health relevance, our understanding of the molecular landscape in hypertension is limited and lags other major diseases. Here we report an extensive analysis of the molecular landscape in hypertension and its end-organ damage and uncover novel mechanisms linking human genetic variants to the development of these diseases. We obtained single-nucleus RNA-seq (612,984 nuclei), single-nucleus ATAC-seq (179,637 nuclei), or spatial transcriptome data from five organs (hypothalamus, kidney, heart, 3rd order mesenteric artery, middle cerebral artery) in three mouse and rat models under twelve experimental conditions. More than one third of all hypertension research in animal models involves these three models. We identified both model-specific and convergent responses in cell types, genes, and pathways. By integrating our data with human genomic data, we partitioned the blood pressure and end-organ damage traits into cell type-specific transcriptional contributions and cell types common across multiple traits. Using genomic editing in animal models and human induced pluripotent stem cells, we extended key findings and identified new mechanisms linking human genetic variants to the development of hypertension and related renal injury. We anticipate that our rich data sets and findings will broadly drive forward the research of hypertension and hypertensive end-organ damage. Our approach of integrating multi-model and multi-tissue single-cell analysis with human genetic data and in vivo and in vitro genome editing can be applied to investigate other complex traits.
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