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A Chinese host genetic study discovered IFNs and causality of laboratory traits on COVID-19 severity.

ABSTRACT: The COVID-19 pandemic has caused over 220 million infections and 4.5 million deaths worldwide. Current risk factor cannot fully explain the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients' laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory traits and used Mendelian randomization (MR) analysis to further investigate the causality of traits on disease severity. Two causal traits, WBC counts and cholesterol levels, were identified based on MR study, and their functional genes are located at genes MHC complex and ApoE, respectively. Our gene-based analysis and GSEA revealed four interferon pathways, including type I interferon receptor binding and SARS coronavirus and innate immunity. We hope that our work will contribute to studying the genetic mechanisms of disease and serve as a useful reference for COVID-19 diagnosis and treatment.

SUBMITTER: Zhu H

PROVIDER: S-EPMC8481128 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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A Chinese host genetic study discovered IFNs and causality of laboratory traits on COVID-19 severity.

Zhu Huanhuan H Zheng Fang F Li Linxuan L Jin Yan Y Luo Yuxue Y Li Zhen Z Zeng Jingyu J Tang Ling L Li Zilong Z Xia Ningyu N Liu Panhong P Han Dan D Shan Ying Y Zhu Xiaoying X Liu Siyang S Xie Rong R Chen Yilin Y Liu Wen W Liu Longqi L Xu Xun X Wang Jian J Yang Huanming H Shen Xia X Jin Xin X Cheng Fanjun F

iScience 20210930 10

The COVID-19 pandemic has caused over 220 million infections and 4.5 million deaths worldwide. Current risk factor cannot fully explain the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients' laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory traits and used Mendelian randomization (MR) analysis to further inves ...[more]

PMID: 34608450

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Project description: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 CXCR6 and CCR9 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 cis -expression quantitative trait loci highlighted the regulatory effect on CXCR6 expression in lung and immune cells. In the lung resident memory CD8 + T (T RM ) cells, we found a 3.32-fold decrease of cell proportion and lower expression of CXCR6 in the severe than moderate patients using the BALF transcriptomic dataset. Pro-inflammatory transcriptional programs were highlighted in T RM cells trajectory from moderate to severe patients. CXCR6 from the 3p21 . 31 locus is associated with severe COVID-19. CXCR6 tends to have a lower expression in lung T RM cells of severe patients, which aligns with the protective effect of CXCR6 from TWAS analysis. We illustrate one potential mechanism of host genetic factor impacting the severity of COVID-19 through regulating the expression of CXCR6 and T RM cell proportion and stability. Our results shed light on potential therapeutic targets for severe COVID-19.

Dataset Information

A Chinese host genetic study discovered IFNs and causality of laboratory traits on COVID-19 severity.

Publications

A Chinese host genetic study discovered IFNs and causality of laboratory traits on COVID-19 severity.

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