Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation.

BACKGROUND: Kidney transplantation is the most effective treatment for end-stage renal disease. Allograft rejections severely affect survivals of allograft kidneys and recipients. METHODS: Using bioinformatics approaches, the present study was designed to investigate immune status in renal transplant recipients. Fifteen datasets from Gene Expression Omnibus (GEO) were collected and analysed. Analysis of gene enrichment and protein-protein interactions were also used. RESULTS: There were 40 differentially expressed genes (DEGs) identified in chronic rejection group when compared with stable recipients, which were enriched in allograft rejection module. There were 135 DEGs identified in acute rejection patients, compared with stable recipients, in which most genes were enriched in allograft rejection and immune deficiency. There were 288 DEGs identified in stable recipients when compared to healthy subjects. Most genes were related to chemokine signalling pathway. In integrated comparisons, expressions of MHC molecules and immunoglobulins were increased in both acute and chronic rejection; expressions of LILRB and MAP 4 K1 were increased in acute rejection patients, but not in stable recipients. There were no overlapping DEGs in blood samples of transplant recipients. CONCLUSION: By performing bioinformatics analysis on the immune status of kidney transplant patients, the present study reports several DEGs in the renal biopsy of transplant recipients, which are requested to be validated in clinical practice.

PIR-B expressing CD8+ T cells exhibit features of Tc1 and Tc17 in SKG mice.

OBJECTIVE: In autoimmune arthritis, TCR signalling is attenuated by peripheral tolerance mechanisms. We have described previously a population of inhibitory receptor LIR-1 expressing autoreactive CD8+ T cells in rheumatoid arthritis. Here, we investigated the role of CD8+ T cells in murine autoimmune arthritis by analysing their expression of the mouse orthologue of LIR-1, PIR-B. METHODS: Frequencies of PIR-B+CD8+ T cells were determined in the SKG arthritis model. The phenotype of those cells was determined ex vivo by FACS and functionality was investigated by means of cytokine production and cytolytic potential upon activation in vitro. RESULTS: SKG mice, under non-SPF (specific pathogen-free) conditions with clinical symptoms of arthritis, were found to harbour significantly increased frequencies of PIR-B+CD8+ T cells. Those cells showed a pro-inflammatory phenotype with preferential production of IL-17 and IFN-γ. The frequency of those cells correlated inversely with the arthritis score, indicating that they might represent autoreactive, but functionally inhibited, CD8+ T cells. CONCLUSION: PIR-B+CD8+ T cells from SKG mice show a cytotoxic and pro-inflammatory phenotype. Inhibition of CD8+ T cell autoreactivity by PIR-B/LIR-1 receptor signalling might be a counter-regulatory mechanism to curb autoreactivity and arthritis.