Dai Yulin, Wang Junke, Jeong Hyun-Hwan, Chen Wenhao, Jia Peilin, Zhao Zhongming
Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA.
bioRxiv. 2021 Feb 19:2021.02.17.431554. doi: 10.1101/2021.02.17.431554.
The coronavirus disease 2019 (COVID-19) is an infectious disease that mainly affects the host respiratory system with ∼80% asymptomatic or mild cases and ∼5% severe cases. Recent genome-wide association studies (GWAS) have identified several genetic loci associated with the severe COVID-19 symptoms. Delineating the genetic variants and genes is important for better understanding its biological mechanisms.
We implemented integrative approaches, including transcriptome-wide association studies (TWAS), colocalization analysis and functional element prediction analysis, to interpret the genetic risks using two independent GWAS datasets in lung and immune cells. To understand the context-specific molecular alteration, we further performed deep learning-based single cell transcriptomic analyses on a bronchoalveolar lavage fluid (BALF) dataset from moderate and severe COVID-19 patients.
We discovered and replicated the genetically regulated expression of and genes. These two genes have a protective effect on the lung and a risk effect on whole blood, respectively. The colocalization analysis of GWAS and -expression quantitative trait loci highlighted the regulatory effect on expression in lung and immune cells. In the lung resident memory CD8 T (T ) cells, we found a 3.32-fold decrease of cell proportion and lower expression of in the severe than moderate patients using the BALF transcriptomic dataset. Pro-inflammatory transcriptional programs were highlighted in T cells trajectory from moderate to severe patients.
from the . locus is associated with severe COVID-19. tends to have a lower expression in lung T cells of severe patients, which aligns with the protective effect of from TWAS analysis. We illustrate one potential mechanism of host genetic factor impacting the severity of COVID-19 through regulating the expression of and T cell proportion and stability. Our results shed light on potential therapeutic targets for severe COVID-19.
2019年冠状病毒病(COVID-19)是一种主要影响宿主呼吸系统的传染病,约80%为无症状或轻症病例,约5%为重症病例。最近的全基因组关联研究(GWAS)已经确定了几个与COVID-19重症症状相关的基因位点。描绘这些遗传变异和基因对于更好地理解其生物学机制很重要。
我们采用了综合方法,包括全转录组关联研究(TWAS)、共定位分析和功能元件预测分析,以利用肺和免疫细胞中的两个独立GWAS数据集来解释遗传风险。为了了解特定背景下的分子改变,我们进一步对中度和重度COVID-19患者的支气管肺泡灌洗液(BALF)数据集进行了基于深度学习的单细胞转录组分析。
我们发现并重复了 和 基因的基因调控表达。这两个基因分别对肺有保护作用,对全血有风险作用。GWAS与 -表达数量性状位点的共定位分析突出了对肺和免疫细胞中 表达的调控作用。在肺驻留记忆CD8 T(T )细胞中,使用BALF转录组数据集,我们发现重症患者的细胞比例比中度患者降低了3.32倍,并且 的表达更低。从中度到重症患者的T 细胞轨迹中突出了促炎转录程序。
来自 。 位点与重症COVID-19相关。在重症患者的肺T 细胞中 倾向于有较低表达,这与TWAS分析中 的保护作用一致。我们阐述了宿主遗传因素通过调节 和T 细胞比例及稳定性影响COVID-19严重程度的一种潜在机制。我们的结果为重症COVID-19的潜在治疗靶点提供了线索。