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COVID-19 and Retinal Layer Thickness: A bidirectional Mendelian Randomization Study
  • +10
  • lili Lang,
  • Kun Zhao,
  • Xiqiao Xiang,
  • Wang Wenwen,
  • QingWei Zhang,
  • Bingxin Gu,
  • Yanyan Zhang,
  • xingxing zhang,
  • Zhen Tang,
  • Meixiang Guo,
  • Wei YuanHao,
  • Lin Yuan,
  • Shaoling Yang
lili Lang
Shanghai 6th Peoples Hospital Affiliated to Shanghai Jiao Tong University

Corresponding Author:[email protected]

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Kun Zhao
Shanghai 6th Peoples Hospital Affiliated to Shanghai Jiao Tong University
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Xiqiao Xiang
Shanghai 6th Peoples Hospital Affiliated to Shanghai Jiao Tong University
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Wang Wenwen
Shanghai 6th Peoples Hospital Affiliated to Shanghai Jiao Tong University
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QingWei Zhang
Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital
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Bingxin Gu
Fudan University Shanghai Cancer Center Radiation Oncology Research Center
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Yanyan Zhang
Fudan University Institute of Radiation Medicine
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xingxing zhang
Shanghai 6th Peoples Hospital Affiliated to Shanghai Jiao Tong University
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Zhen Tang
Shanghai 6th Peoples Hospital Affiliated to Shanghai Jiao Tong University
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Meixiang Guo
Shanghai 6th Peoples Hospital Affiliated to Shanghai Jiao Tong University
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Wei YuanHao
Harbin Medical University School of Public Health
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Lin Yuan
Shanghai 6th Peoples Hospital Affiliated to Shanghai Jiao Tong University
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Shaoling Yang
Shanghai 6th Peoples Hospital Affiliated to Shanghai Jiao Tong University
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Abstract

Observational studies have reported that COVID-19 is associated with alterations in retinal layer thickness, including changes in the ganglion cell inner plexiform layer (GCIPL) and retinal nerve fiber layer (RNFL). However, observational studies are susceptible to confounding factors and reverse causality. Therefore, we assessed the direction and strength of the causal relationship between COVID-19 patient phenotypes (susceptibility, hospitalization, and severity) and GCIPL and RNFL thicknesses using a bidirectional two-sample Mendelian randomization (MR) design. The inverse-variance weighted (IVW) method is the primary approach used to estimate causal effects. MR Egger, weighted median, weighted mode, MR Egger (bootstrap), and penalized weighted median methods were applied. In addition, we performed sensitivity analyses using RadialMR, MRPRESSO, MR Egger regression, Cochran’s Q statistic, and Leave-one-out analysis. Forward MR analysis revealed that genetically identified COVID-19 susceptibility significantly increased the risk of GCIPL thickness (OR: 2.428, 95% confidence interval[CI]:1.493-3.947, PIVW=3.579 ×10 -4) and RNFL thickness (OR: 1.735,95%CI:1.198-2.513, PIVW=3.580×10 -3). The results after excluding MRPRESSO and RadialMR to identify outliers and SNPs associated with confounding factors showed RNFL thickness(OR:1.800,95%CI: 1.192-2.717, PIVW=5.147×10 -3).Reverse MR analysis did not indicate a significant causal association between GCIPL and RNFL thicknesses and COVID-19 phenotypes. In conclusion, the host genetic liability to COVID-19 susceptibility was causally associated with increased GCIPL and RNFL thicknesses. Documenting this association increases our understanding of the pathophysiological mechanisms underlying COVID-19 susceptibility in retinopathy.