Integration of human organoids single‐cell transcriptomic profiles and human genetics repurposes critical cell type‐specific drug targets for severe COVID‐19
Yunlong Ma, Yijun Zhou, Dingping Jiang, Wei Dai, Jingjing Li, Chunyu Deng, Cheng Chen, Gongwei Zheng, Yaru Zhang, Fei Qiu, Haojun Sun, Shilai Xing, Haijun Han, Jia Qu, Nan Wu, Yinghao Yao, Jianzhong Su
Cell Proliferation, doi:10.1111/cpr.13558
Human organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single-cell RNA sequencing (scRNA-seq) technology and genome-wide association study (GWAS) have accelerated the biological and therapeutic interpretation of traitrelevant cell types or states. Here, we constructed a computational framework to integrate atlas-level organoid scRNA-seq data, GWAS summary statistics, expression quantitative trait loci, and gene-drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID-19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID-19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID-19-damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID-19, and this cell subset showed a notable increase in cell-to-cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID-19 in a cell-type-specific manner. Overall, our results showcase that host genetic
AUTHOR CONTRIBUTIONS Yunlong
CONFLICT OF INTEREST STATEMENT The authors declare no competing interests.
SUPPORTING INFORMATION Additional supporting information can be found online in the Supporting Information section at the end of this article.
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'abstract': '<jats:title>Abstract</jats:title><jats:p>Human organoids recapitulate the cell type diversity '
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