Combined Analysis of Metabolomics and Proteomics in Immune-Related Dry Eye Disease

Dry eye disease (DED) is a chronic ocular surface disorder with immune factors significantly contributing to its pathogenesis. Traditional research methods, often focused on single-dimensional approaches, have limited the understanding of the complex mechanisms involved in DED. The advent of multi-omics technologies, however, offers a comprehensive framework to explore molecular mechanisms across multiple levels, presenting new possibilities for diagnosing and treating DED. This study specifically aimed to compare the proteomics and metabolomics profiles of individuals with Sjögren’s Syndrome (SS), a condition often associated with DED, to healthy controls, and to identify potential biomarkers and pathways that play a role in its development. Serum proteins and metabolites were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS), followed by multivariate and univariate statistical analysis to pinpoint differentially expressed proteins (DEPs) and metabolites (DEMs). Functional annotations and pathway enrichment analyses were conducted using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases to identify key molecular pathways. Bioinformatics tools were then applied to integrate the proteomics and metabolomics data, highlighting crucial differential proteins, metabolites, and biomarkers. The study identified 112 DEPs in individuals with SS, including 94 upregulated and 18 downregulated proteins. The most significantly enriched pathways in KEGG analysis included amino acid biosynthesis, glycolysis/gluconeogenesis, the Rap1 signaling pathway, carbon metabolism, focal adhesion, platelet activation, the pentose phosphate pathway, and actin cytoskeleton regulation. Key proteins identified as potentially related to SS development included GAPDH, CFL1, ENO1, VCL, MYH9, FLNA, TPI1, ITGA2B, TLN1, and TXN. In the metabolomics analysis, 372 DEMs were identified, with 268 upregulated and 104 downregulated metabolites, primarily enriched in glycine, serine, threonine metabolism, as well as taurine and hypotaurine metabolism. The integration of proteomics and metabolomics data underscored the significance of the Rap1 signaling pathway, suggesting its potential involvement in the development of DED. Overall, this study revealed several key differential proteins, metabolites, and potential biomarkers, providing valuable insights into the molecular mechanisms underlying DED and offering new avenues for further research into its pathogenesis.干眼症（Dry Eye Disease, DED）是一种慢性眼表疾病，免疫因素在其发病机制中发挥关键作用。传统研究方法多聚焦于单维度路径，限制了研究者对干眼症复杂发病机制的认知。然而，多组学（multi-omics）技术的出现为探索多层面分子机制提供了全面框架，为干眼症的诊断与治疗带来了新可能。本研究旨在对比常与干眼症伴发的干燥综合征（Sjögren’s Syndrome, SS）患者与健康对照者的蛋白质组学与代谢组学特征，并筛选与其发病相关的潜在生物标志物及通路。本研究采用液相色谱-串联质谱（liquid chromatography-tandem mass spectrometry, LC-MS/MS）分析血清蛋白与代谢物，随后通过多变量与单变量统计分析筛选差异表达蛋白（differentially expressed proteins, DEPs）与差异代谢物（differentially expressed metabolites, DEMs）。本研究借助基因本体（Gene Ontology, GO）与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）数据库开展功能注释与通路富集分析，以筛选关键分子通路。随后本研究借助生物信息学工具整合蛋白质组与代谢组数据，明确关键差异蛋白、代谢物及生物标志物。本研究在干燥综合征患者中筛选得到112个差异表达蛋白，其中94个表达上调、18个表达下调。KEGG富集分析显示，最显著富集的通路包括氨基酸生物合成、糖酵解/糖异生、Rap1信号通路、碳代谢、黏着斑、血小板活化、磷酸戊糖途径及肌动蛋白细胞骨架调控。本研究筛选得到与干燥综合征发病潜在相关的关键蛋白包括GAPDH、CFL1、ENO1、VCL、MYH9、FLNA、TPI1、ITGA2B、TLN1及TXN。代谢组学分析中共筛选得到372个差异代谢物，其中268个表达上调、104个表达下调，主要富集于甘氨酸、丝氨酸、苏氨酸代谢以及牛磺酸与次牛磺酸代谢通路。蛋白质组与代谢组数据整合分析进一步凸显了Rap1信号通路的重要性，提示该通路可能参与干眼症的发病过程。综上，本研究筛选得到多个关键差异蛋白、代谢物及潜在生物标志物，为解析干眼症的分子发病机制提供了重要见解，也为其发病机制的后续研究开辟了新方向。