COVID-19 and retinal layer thickness: A bidirectional Mendelian randomization study

Abstract

BackgroundObservational 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, the causal relationships remain unknown. Therefore, we assessed the direction and strength of the causal relationship between COVID-19 and GCIPL and RNFL thicknesses using a bidirectional two-sample Mendelian randomization (MR) design. MethodsData were obtained from a large-scale COVID-19 Host Genetics Initiative (Nsample = 6,512,887), GCIPL dataset (Ncase = 31,434), and RNFL dataset (Ncase = 31,434). 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. Sensitivity analyses were implemented with RadialMR, MRPRESSO, MR-Egger regression, Cochran's Q statistic, leave-one-out analysis, and the funnel plot. ResultsForward 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) after Bonferroni correction. Reverse MR analysis did not indicate a significant causal association between GCIPL and RNFL thicknesses and COVID-19 phenotypes. No significant horizontal pleiotropy was found in the sensitivity analysis. ConclusionsThe 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.