Your browser doesn't support javascript.
An integrated strategy to identify COVID-19 causal genes and characteristics represented by LRRC37A2.
Zhu, Zijun; Chen, Xinyu; Wang, Chao; Zhang, Sainan; Yu, Rui; Xie, Yubin; Yuan, Shuofeng; Cheng, Liang; Shi, Lei; Zhang, Xue.
  • Zhu Z; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
  • Chen X; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
  • Wang C; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
  • Zhang S; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
  • Yu R; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
  • Xie Y; Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
  • Yuan S; State Key Laboratory of Emerging Infectious Diseases, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
  • Cheng L; Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
  • Shi L; State Key Laboratory of Emerging Infectious Diseases, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
  • Zhang X; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
J Med Virol ; 95(2): e28585, 2023 02.
Article in English | MEDLINE | ID: covidwho-2289067
ABSTRACT
Genome-wide association study (GWAS) could identify host genetic factors associated with coronavirus disease 2019 (COVID-19). The genes or functional DNA elements through which genetic factors affect COVID-19 remain uncharted. The expression quantitative trait locus (eQTL) provides a path to assess the correlation between genetic variations and gene expression. Here, we firstly annotated GWAS data to describe genetic effects, obtaining genome-wide mapped genes. Subsequently, the genetic mechanisms and characteristics of COVID-19 were investigated by an integrated strategy that included three GWAS-eQTL analysis approaches. It was found that 20 genes were significantly associated with immunity and neurological disorders, including prior and novel genes such as OAS3 and LRRC37A2. The findings were then replicated in single-cell datasets to explore the cell-specific expression of causal genes. Furthermore, associations between COVID-19 and neurological disorders were assessed as a causal relationship. Finally, the effects of causal protein-coding genes of COVID-19 were discussed using cell experiments. The results revealed some novel COVID-19-related genes to emphasize disease characteristics, offering a broader insight into the genetic architecture underlying the pathophysiology of COVID-19.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Genome-Wide Association Study / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: J Med Virol Year: 2023 Document Type: Article Affiliation country: Jmv.28585

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Genome-Wide Association Study / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: J Med Virol Year: 2023 Document Type: Article Affiliation country: Jmv.28585