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[Expression Levels and Regulation of Selenoprotein Genes in Patients With Coronavirus Disease 2019].
Li, Jing; Zhang, Rong-Qiang; Zhang, Ling-Zhi; Qi, Yan; Hao, Jie; He, Ao-Yue; Zhao, Xu; Li, Xiu-Qin.
Afiliação
  • Li J; Department of Epidemiology and Health Statistics,School of Public Health,Shaanxi University of Chinese Medicine,Xianyang,Shaanxi 712046,China.
  • Zhang RQ; Department of Epidemiology and Health Statistics,School of Public Health,Shaanxi University of Chinese Medicine,Xianyang,Shaanxi 712046,China.
  • Zhang LZ; Department of Laboratory Medicine,The Second Hospital of Hanbin District,Ankang,Shaanxi 725021,China.
  • Qi Y; Department of Epidemiology and Health Statistics,School of Public Health,Shaanxi University of Chinese Medicine,Xianyang,Shaanxi 712046,China.
  • Hao J; Department of Epidemiology and Health Statistics,School of Public Health,Shaanxi University of Chinese Medicine,Xianyang,Shaanxi 712046,China.
  • He AY; Department of Epidemiology and Health Statistics,School of Public Health,Shaanxi University of Chinese Medicine,Xianyang,Shaanxi 712046,China.
  • Zhao X; Department of Epidemiology and Health Statistics,School of Public Health,Shaanxi University of Chinese Medicine,Xianyang,Shaanxi 712046,China.
  • Li XQ; Department of Public Administration,School of Humanities and Management,Shaanxi University of Chinese Medicine,Xianyang,Shaanxi 712046,China.
Zhongguo Yi Xue Ke Xue Yuan Xue Bao ; 46(3): 316-323, 2024 Jun.
Article em Zh | MEDLINE | ID: mdl-38953254
ABSTRACT
Objective To investigate the expression levels of selenoprotein genes in the patients with coronavirus disease 2019 (COVID-19) and the possible regulatory mechanisms.Methods The dataset GSE177477 was obtained from the Gene Expression Omnibus,consisting of a symptomatic group (n=11),an asymptomatic group (n=18),and a healthy control group (n=18).The dataset was preprocessed to screen the differentially expressed genes (DEG) related to COVID-19,and gene ontology functional annotation and Kyoto encyclopedia of genes and genomes enrichment analysis were performed for the DEGs.The protein-protein interaction network of DEGs was established,and multivariate Logistic regression was employed to analyze the effects of selenoprotein genes on the presence/absence of symptoms in the patients with COVID-19.Results Compared with the healthy control,the symptomatic COVID-19 patients presented up-regulated expression of GPX1,GPX4,GPX6,DIO2,TXNRD1,SELENOF,SELENOK,SELENOS,SELENOT,and SELENOW and down-regulated expression of TXNRD2 and SELENON (all P<0.05).The asymptomatic patients showcased up-regulated expression of GPX2,SELENOI,SELENOO,SELENOS,SELENOT,and SELENOW and down-regulated expression of SELP (all P<0.05).The results of multivariate Logistic regression analysis showed that the abnormally high expression of GPX1 (OR=0.067,95%CI=0.005-0.904,P=0.042) and SELENON (OR=56.663,95%CI=3.114-856.999,P=0.006) was the risk factor for symptomatic COVID-19,and the abnormally high expression of SELP was a risk factor for asymptomatic COVID-19 (OR=15.000,95%CI=2.537-88.701,P=0.003).Conclusions Selenoprotein genes with differential expression are involved in the regulation of COVID-19 development.The findings provide a new reference for the prevention and treatment of COVID-19.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Selenoproteínas / COVID-19 Limite: Humans Idioma: Zh Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Selenoproteínas / COVID-19 Limite: Humans Idioma: Zh Ano de publicação: 2024 Tipo de documento: Article