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DOI 10.1016/j.micinf.2023.105170

Медицинская библиотека · Microbes and infection · 2023

A systematical association analysis of 25 common virus infection and genetic susceptibility of COVID-19 infection.

Zhang Na, Chen Yujing, Li Chun'e, Qin Xiaoyue, He Dan, Wei Wenming, Zhao Yijing, Cai Qingqing, Shi Sirong, Chu Xiaoge, Wen Yan, Jia Yumeng, Zhang Feng

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

OBJECTIVES

Previous studies identified a number of diseases were associated with 2019 coronavirus disease (COVID-19). However, the associations between these diseases related viral infections and COVID-19 remains unknown now.

METHODS

In this study, we utilized single nucleotide polymorphisms (SNPs) related to COVID-19 from genome-wide association study (GWAS) and individual-level genotype data from the UK biobank to calculate polygenic risk scores (PRS) of 487,409 subjects for eight COVID-19 clinical phenotypes. Then, multiple logistic regression models were established to assess the correlation between serological measurements (positive/negative) of 25 viruses and the PRS of eight COVID-19 clinical phenotypes. And we performed stratified analyses by age and gender.

RESULTS

In whole population, we identified 12 viruses associated with the PRS of COVID-19 clinical phenotypes, such as VZV seropositivity for Varicella Zoster Virus (Unscreened/Exposed_Negative: β = 0.1361, P = 0.0142; Hospitalized/Unscreened: β = 0.1167, P = 0.0385) and MCV seropositivity for Merkel Cell Polyomavirus (Unscreened/Exposed_Negative: β = -0.0614, P = 0.0478). After age stratification, we identified seven viruses associated with the PRS of eight COVID-19 clinical phenotypes in the age < 65 years group. After gender stratification, we identified five viruses associated with the PRS of eight COVID-19 clinical phenotypes in the women group.

CONCLUSION

Our study findings suggest that the genetic susceptibility to different COVID-19 clinical phenotypes is associated with the infection status of various common viruses.

Для цитирования: Zhang Na, Chen Yujing, Li Chun'e, Qin Xiaoyue, He Dan, Wei Wenming, Zhao Yijing, Cai Qingqing, Shi Sirong, Chu Xiaoge, Wen Yan, Jia Yumeng, Zhang Feng. A systematical association analysis of 25 common virus infection and genetic susceptibility of COVID-19 infection.. Microbes and infection. 2023. DOI: 10.1016/j.micinf.2023.105170.

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