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Mendelian randomization analysis identified genes pleiotropically associated with the risk and prognosis of COVID-19 - 19/01/21

Doi : 10.1016/j.jinf.2020.11.031 
Di Liu a, 1, Jingyun Yang b, c, 1, Bowen Feng d, Wenjin Lu e, Chuntao Zhao f, Lizhuo Li g,
a Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China 
b Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA 
c Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA 
d Odette School of Business, University of Windsor, Windsor, ON, Canada 
e Department of Mathematics, University College London, London, United Kingdom 
f Brain Tumor Center, Cancer and Blood Diseases Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA 
g Emergency Department, Xuanwu Hospital, Capital Medical University, Beijing, China 

Corresponding author.

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Highlights

We aimed to identify genes that were pleiotropically/potentially causally associated with COVID-19.
We adopted a summary data-based Mendelian randomization method integrating summarized GWAS data for COVID-19 and cis- eQTL (expression quantitative trait loci) data.
We identified 2 probes, ILMN_1,765,146 and ILMN_1,791,057 tagging IFNAR2, that showed pleiotropic association with hospitalized COVID-19.
Multiple genes as tagged by the top 5 probes were involved in inflammation or antiviral immunity.
Several other tagged genes, such as PON2 and HPS5, were involved in blood coagulation.

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Summary

Objectives

COVID-19 has caused a large global pandemic. Patients with COVID-19 exhibited considerable variation in disease behavior. Pervious genome-wide association studies have identified potential genetic variants involved in the risk and prognosis of COVID-19, but the underlying biological interpretation remains largely unclear.

Methods

We applied the summary data-based Mendelian randomization (SMR) method to identify genes that were pleiotropically associated with the risk and various outcomes of COVID-19, including severe respiratory confirmed COVID-19 and hospitalized COVID-19.

Results

In blood, we identified 2 probes, ILMN_1765146 and ILMN_1791057 tagging IFNAR2, that showed pleiotropic association with hospitalized COVID-19 (β [SE]=0.42 [0.09], P = 4.75 × 10−06 and β [SE]=-0.48 [0.11], P = 6.76 × 10−06, respectively). Although no other probes were significant after correction for multiple testing in both blood and lung, multiple genes as tagged by the top 5 probes were involved in inflammation or antiviral immunity, and several other tagged genes, such as PON2 and HPS5, were involved in blood coagulation.

Conclusions

We identified IFNAR2 and other potential genes that could be involved in the susceptibility or prognosis of COVID-19. These findings provide important leads to a better understanding of the mechanisms of cytokine storm and venous thromboembolism in COVID-19 and potential therapeutic targets for the effective treatment of COVID-19.

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Keywords : Coronavirus disease 2019, IFNAR2, Gene expression quantitative trait loci, Summary Mendelian randomization


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Vol 82 - N° 1

P. 126-132 - janvier 2021 Retour au numéro
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