AUTHOR=Huang Jing , Zhou Qiong TITLE=Gene Biomarkers Related to Th17 Cells in Macular Edema of Diabetic Retinopathy: Cutting-Edge Comprehensive Bioinformatics Analysis and In Vivo Validation JOURNAL=Frontiers in Immunology VOLUME=Volume 13 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.858972 DOI=10.3389/fimmu.2022.858972 ISSN=1664-3224 ABSTRACT=Background: Previous studies have shown that T-helper 17 (Th17) cells play critical role in the inflammatory response of diabetic retinopathy (DR), but its cell infiltration and gene correlation in the retina of DR, especially in diabetic macular edema (DME), remains unclear. Methods: Download dataset GSE160306 from the Gene Expression Omnibus (GEO) database. ImmuCellAI algorithm was used to estimate the abundance of Th17 cells in 24 kinds of infiltrating immune cells. The differentially expressed Th17 related genes (DETh17RGs) between NPDR and DME were documented by difference analysis and correlation analysis. Through routine enrichment analysis, a protein-protein interaction (PPI) network was constructed to analyze the potential function of DETh17RGs. CytoHubba plug-in algorithm, Lasso regression analysis and support vector machine recursive feature elimination (SVM-RFE) were implemented to comprehensively identify Hub DETh17RGs. The expression archetypes of Hub DETh17RGs were verified in several independent datasets related to DR. The Th17RG score was defined as the genetic characterization of Hub DETh17RGs using the GSVA score method, which was used to distinguish early and advanced diabetic nephropathy (DN) as well as normal and diabetic nephropathy. Finally, real-time quantitative PCR (qPCR) was implemented to verify the transcription levels of Hub DETh17RGs the STZ-induced DR model mice (C57BL/6J). Results: 238 DETh17RGs were identified, of which 212 genes were positively correlated while only 26 genes were negatively correlated. 6 genes (CD44, CDC42, TIMP1, BMP7, RHOC, FLT1) were identified as Hub DETh17RGs. The verification of multiple independent datasets related to DR and DN proved that Hub DETh17RGs can not only distinguish PDR patients from normal people, but also distinguish DN patients from normal people. It can also identify the initial and advanced stages of the two diseases (NPDR vs DME, Early DN vs Advanced DN). Except for CDC42 and TIMP1, the qPCR transcription levels and trends of other Hub DETh17RGs in STZ-induced DR model mice were consistent with the human transcriptome level. Conclusion: This study may improve our understanding of Th17 cell-related molecular mechanisms in the progression of DME. Meanwhile, it also provides an updated basis for the molecular mechanism of Th17 cell crosstalk in the eye and kidney in diabetes.