Current understanding of ocular fluid analysis in uveitis

Abstract

Uveitis sometimes causes severe inflammation and significant loss of visual function. However, the cause is unknown in approximately 50% of cases, and the pathogenesis of the disease is also unknown in many cases. Intraocular fluid is rich in biological substances such as DNA/RNA, cytokines, antibodies, proteins, and metabolites and analysis of intraocular fluid is important for identifying biomarkers and understanding the pathogenesis of uveitis. For example, comprehensive polymerase chain reaction test of intraocular fluid has enabled rapid diagnosis of infectious uveitis. In addition, a combination of histopathological examination of intraocular fluid, cytokine measurement, flow cytometry, and genetic assessments has increased the efficiency of diagnosis of intraocular malignant lymphoma. In recent years, omics analysis such as metabolomics, proteomics, and transcriptomics has been actively conducted in the medical field, and there are scattered reports of intraocular fluid analysis in uveitis. Moreover, research and practical application of artificial intelligence (AI) is also progressing rapidly in the medical field. In the field of ophthalmology, many studies introducing AI have been reported, and a small number of machine learning studies using intraocular fluid have also been reported. In this review, we searched PubMed for previous reports on intraocular fluid analysis in uveitis and aim to introduce the analysis of intraocular fluid in uveitis, including the results of our comprehensive genetic analysis of cytomegalovirus in the eye.

Keywords

• artificial intelligence
• intraocular fluid analysis
• omics analysis
• polymerase chain reaction test
• uveitis