Frontiers in Immunology (Aug 2023)

The impact of immunoglobulin G N-glycosylation level on COVID-19 outcome: evidence from a Mendelian randomization study

  • Feiwu Long,
  • Chenghan Xiao,
  • Huijie Cui,
  • Wei Wang,
  • Zongze Jiang,
  • Mingshuang Tang,
  • Wenqiang Zhang,
  • Yunjie Liu,
  • Rong Xiang,
  • Li Zhang,
  • Xunying Zhao,
  • Chao Yang,
  • Peijing Yan,
  • Xueyao Wu,
  • Yutong Wang,
  • Yanqiu Zhou,
  • Ran Lu,
  • Ran Lu,
  • Ran Lu,
  • Yulin Chen,
  • Jiayuan Li,
  • Xia Jiang,
  • Chuanwen Fan,
  • Chuanwen Fan,
  • Chuanwen Fan,
  • Chuanwen Fan,
  • Chuanwen Fan,
  • Ben Zhang,
  • Ben Zhang

DOI
https://doi.org/10.3389/fimmu.2023.1217444
Journal volume & issue
Vol. 14

Abstract

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BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID‐19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial.MethodsWe conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran’s Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results.ResultsWe found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92–0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy.ConclusionsOur study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels.

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