Bioinformatics analysis reveals the landscape of immune cell infiltration and novel immune-related biomarkers in moyamoya disease - Cao, Lei; Ai, Yunzheng; Dong, Yang; Li, Dongpeng; Wang, Hao; Sun, Kaiwen; Wang, Chenchao; Zhang, Manxia; Yan, Dongming; Li, Hongwei; Liang, Guobiao; Yang, Bo (Frontiers in Genetics, 2023)
Objective This study aimed to identify immune infiltration characteristics and new immunological diagnostic biomarkers in cerebrovascular tissue of MMD using bioinformatics analysis. Methods GSE189993 and GSE141022 were downloaded from the GEO database. Differentially expressed genes and PPI analysis were performed. After analyzing WGCNA, the most significant module associated with MMD was obtained. Next, functional pathways according to GSEA, GO and KEGG were enriched for above core genes obtained from PPI and WGCNA. Additionally, immune infiltration using CIBERSORT deconvolution algorithm, immune-related biomarkers and the relationship between these genes were further explored. Finally, diagnostic accuracy was verified with ROC curves in validation dataset GSE157628. Results A total of 348 DEGs were screened, including 89 downregulated and 259 up-regulated genes. Thistlel module was detected as the most significant module associated with MMD. Functional analysis of the core genes was chiefly involved the immune response, immune system process, protein tyrosine kinase activity, secretory granule and so on. Among 13 immune-related overlapping genes, four genes (BTK, FGR, PTPN11, SYK) were identified as potential diagnostic biomarkers, PTPN11 showed the highest specificity and sensitivity. Meanwhile, higher proportion of eosinophils, not T cells or B cells, was demonstrated in the specific immune infiltration landscape of MMD. Conclusions Immune activities and immune cells involved in the progression of MMD actively. BTK, FGR, PTPN11 and SYK were identified as potential immune diagnostic biomarkers. These immune-related genes and cells may provide novel insights for immunotherapy in the future.