单细胞转录组全基因组孟德尔随机化和共定位揭示了新冠病毒的免疫介导调控机制和药物靶点。

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

作者信息

Ying Hui, Wu Xueyan, Jia Xiaojing, Yang Qianqian, Liu Haoyu, Zhao Huiling, Chen Zhihe, Xu Min, Wang Tiange, Li Mian, Zhao Zhiyun, Zheng Ruizhi, Wang Shuangyuan, Lin Hong, Xu Yu, Lu Jieli, Wang Weiqing, Ning Guang, Zheng Jie, Bi Yufang

机构信息

Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.

出版信息

EBioMedicine. 2025 Mar;113:105596. doi: 10.1016/j.ebiom.2025.105596. Epub 2025 Feb 10.

DOI:10.1016/j.ebiom.2025.105596

PMID:39933264

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11867302/

Abstract

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 with drug trial information, we developed a tier system and prioritized 37 drug targets for COVID-19.

INTERPRETATION

Our study showcased the central role of immune-mediated regulatory mechanisms for COVID-19 and prioritized drug targets that might inform interventions for viral infectious diseases.

FUNDING

This work was supported by grants from the National Key Research and Development Program of China (2022YFC2505203).

摘要

背景

新型冠状病毒肺炎（COVID-19）继续对我们的健康产生长期影响。已推出的有效免疫介导抗病毒药物有限。

方法

我们使用26,597个单细胞表达定量性状位点（sc-eQTL）进行孟德尔随机化（MR）和共定位分析，以代表14种外周血免疫细胞中16,597个基因的表达效应，并根据COVID-19遗传宿主计划全基因组关联研究（GWAS）荟萃分析第7轮的4个COVID-19结局对其进行测试。我们还进行了额外的验证，包括共定位、连锁不平衡检查和宿主-病原体相互作用组预测。我们将MR研究结果与来自几个药物基因相关数据库的临床试验证据相结合，以识别具有重新利用潜力的药物。最后，我们开发了一个分级系统，并确定了基于免疫细胞的COVID-19优先药物靶点。

研究结果

我们在14种免疫细胞中确定了132个可能的因果基因（343个MR关联）与COVID-19相关，其中58个基因以前未被报道。145对（73%）基因-COVID-19对仅在一种免疫细胞类型中显示出对COVID-19的影响，这意味着广泛的免疫细胞特异性效应。对于通路分析，我们发现可能的因果基因在自然杀伤（NK）细胞募集细胞中富集，但在NK细胞中减少。使用深度学习模型，我们发现107个（81%）可能的因果基因（41个新基因）被预测与严重急性呼吸综合征冠状病毒2（SARS-CoV-2）蛋白相互作用。将上述证据与药物试验信息相结合，我们开发了一个分级系统，并确定了37个COVID-19优先药物靶点。