Single-cell transcriptome-wide Mendelian randomization and colocalization reveals immune-mediated regulatory mechanisms and drug targets for COVID-19

作者：Hui Ying, Xueyan Wu, Xiaojing Jia, Qianqian Yang, Haoyu Liu, Huiling Zhao, Zhihe Chen, Min Xu, Tiange Wang, Mian Li, Zhiyun Zhao, Ruizhi Zheng, Shuangyuan Wang, Honghui Lin, Yu Xu, Jieli Lu, Weiqing Wang, Guang Ning, Jie Zheng, Yufang Bi · 发表于：EBioMedicine · 年份：2025 · DOI：10.1016/j.ebiom.2025.105596 · 被引用次数：19 · 研究领域：Single-cell and spatial transcriptomics、COVID-19 Clinical Research Studies、Genetic Associations and Epidemiology

BACKGROUND: COVID-19 continues to show long-term impacts on our health. Limited effective immune-mediated antiviral drugs have been launched. METHODS: We conducted a Mendelian randomization (MR) and colocalization analysis using 26,597 single-cell expression quantitative trait loci (sc-eQTL) to proxy effects of expressions of 16,597 genes in 14 peripheral blood immune cells and tested them against four COVID-19 outcomes from COVID-19 Genetic Housing Initiative GWAS meta-analysis Round 7. We also carried out additional validations including colocalization, linkage disequilibrium check and host-pathogen interactome predictions. We integrated MR findings with clinical trial evidence from several drug gene related databases to identify drugs with repurposing potential. Finally, we developed a tier system and identified immune-cell-based prioritized drug targets for COVID-19. FINDINGS: We identified 132 putative causal genes in 14 immune cells (343 MR associations) for COVID-19, with 58 genes that were not reported previously. 145 (73%) gene-COVID-19 pairs showed effects on COVID-19 in only one immune cell type, which implied widespread immune-cell specific effects. For pathway analyses, we found the putative causal genes were enriched in natural killer (NK) recruiting cells but de-enriched in NK cells. Using a deep learning model, we found 107 (81%) of the putative causal genes (41 novel genes) were predicted to interact with SARS-COV-2 proteins. Integrating the above evidence wi...