Insights into the Correlation and Immune Crosstalk Between COVID-19 and Sjögren's Syndrome Keratoconjunctivitis Sicca via Weighted Gene Coexpression Network Analysis and Machine Learning

通过加权基因共表达网络分析和机器学习深入了解 COVID-19 与干燥综合征性角结膜炎之间的相关性和免疫串扰

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Abstract

Background: Although autoimmune complications of COVID-19 have aroused concerns, there is no consensus on its ocular complications. Sjögren's syndrome is an autoimmune disease accompanied by the ocular abnormality keratoconjunctivitis sicca (SS-KCS), which may be influenced by COVID-19. Thereby, we explored the possible interaction between COVID-19 and SS-KCS, and we aimed to elucidate the potential correlated mechanism. Methods: Differentially expressed genes (DEGs) in COVID-19 and SS-KCS transcriptome data obtained from the gene expression omnibus database were identified, and COVID-19-related genes were screened using weighted gene coexpression network analysis. Common genes were verified using four machine-learning diagnostic predictors. The clinical relationship between the two common hub genes of COVID-19 was analyzed. Finally, the immune cell types infiltrating the microenvironment in the COVID-19 dataset were analyzed using CIBERSORT, and the interrelation between key genes and differentially infiltrating immune cells was verified via Pearson correlation. Results: Ten potential primary hub mRNAs were screened by intersecting the COVID-19 DEGs, SS-KCS DEGs, and WGCNA genes. After a multifaceted evaluation using four mainstream machine-learning diagnostic predictors, the most accurate and sensitive random forest model identified CR1 and TAP2 as the common hub genes of COVID-19 and SS-KCS. Together with the clinical information on COVID-19, the expression of CR1 and TAP2 was significantly correlated with the status and severity of COVID-19. CR1 and TAP2 were significantly positively correlated with M0 and M2 macrophages, neutrophils, and CD4+ memory resting T cells and negatively correlated with activated NK cells, monocytes, and CD8+ T cells. Conclusions: We validated the hub genes associated with both COVID-19 and SS-KCS, and we investigated the immune mechanisms underlying their interaction, which may help in the early prediction, identification, diagnosis, and management of SARS-CoV-2 infection-related SS-KCS syndrome or many other immune-related complications in the long COVID period.

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