Mapping the genetic architecture of human traits to cell types in the kidney identifies mechanisms of disease and potential treatments

The functional interpretation of genome-wide association studies (GWAS) is challenging due to the cell-type-dependent influences of genetic variants. Here, we generated comprehensive maps of expression quantitative trait loci (eQTLs) for 659 microdissected human kidney samples and identified cell-ty...

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Published in:Nature genetics Vol. 53; no. 9; pp. 1322 - 1333
Main Authors: Sheng, Xin, Guan, Yuting, Ma, Ziyuan, Wu, Junnan, Liu, Hongbo, Qiu, Chengxiang, Vitale, Steven, Miao, Zhen, Seasock, Matthew J., Palmer, Matthew, Shin, Myung K., Duffin, Kevin L., Pullen, Steven S., Edwards, Todd L., Hellwege, Jacklyn N., Hung, Adriana M., Li, Mingyao, Voight, Benjamin F., Coffman, Thomas M., Brown, Christopher D., Susztak, Katalin
Format: Journal Article
Language:English
Published: New York Nature Publishing Group US 01-09-2021
Nature Publishing Group
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Summary:The functional interpretation of genome-wide association studies (GWAS) is challenging due to the cell-type-dependent influences of genetic variants. Here, we generated comprehensive maps of expression quantitative trait loci (eQTLs) for 659 microdissected human kidney samples and identified cell-type-eQTLs by mapping interactions between cell type abundances and genotypes. By partitioning heritability using stratified linkage disequilibrium score regression to integrate GWAS with single-cell RNA sequencing and single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing data, we prioritized proximal tubules for kidney function and endothelial cells and distal tubule segments for blood pressure pathogenesis. Bayesian colocalization analysis nominated more than 200 genes for kidney function and hypertension. Our study clarifies the mechanism of commonly used antihypertensive and renal-protective drugs and identifies drug repurposing opportunities for kidney disease. Cell-type-specific eQTL maps in the human kidney generated from the analysis of over 600 microdissected kidney samples, together with single-cell RNA sequencing and single-nucleus ATAC-seq, prioritize cell types influencing kidney function, hypertension and other traits.
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These authors contributed equally
K.S., X.S. and Y.G. conceived, planned and oversaw the study, and wrote the manuscript. Y.G. performed the CRISPR/Cas9 medicated genome editing. X.S. and S.V. developed the web database. Z.Ma and J.W. conducted the human kidney snATAC-seq experiment. X.S. analyzed data with the help of Y.G., H.L., C.Q., Z.Mi., S.V.. Y.G., M.J.S., M.P., M.K.S., K.D., S.S.P., T.L.E., J.N.H., A.M.H., M.L., B.V., T.C., C.D.B., K.S. assisted with data generation and manuscript revision.
Author contributions
ISSN:1061-4036
1546-1718
1546-1718
DOI:10.1038/s41588-021-00909-9