Fei Huang, Ranran Xu, Yiru Wang, Yongman Lv and Qingquan Liu* Pages 149 - 161 ( 13 )
Background: The soluble urokinase plasminogen activator receptor (suPAR), a biomarker of inflammation, has been found to be a potential prognostic factor of renal function progression. Our previous study showed that plasma suPAR levels were significantly associated with disease activity and prognosis in patients with antineutrophil cytoplasmic autoantibody-associated vasculitis (AAV).
Objective: This study aimed to explore whether urokinase plasminogen activator receptor (uPAR) participated in MPO-ANCA-induced glomerular endothelial cell (GEnC) injury, which is one of the most important aspects in the pathogenesis of AAV.
Methods: GEnC activation and injury were analyzed by measuring the mRNA levels of ICAM-1 and VCAM-1. Permeability experiments were performed to detect endothelial monolayer activation in number. The expression of TLR4 was detected. In addition, TLR4 siRNA and TLR4 inhibitors were employed to determine its role. Bioinformatics methods were used for further analysis.
Results: Compared with a single stimulation, uPAR could further increase the expression of ICAM-1 and VCAM-1 mRNA levels, increase endothelial monolayer permeability and impair tight junctions in GEnCs stimulated with MPO-ANCA-positive IgG. The expression of TLR4 was upregulated by uPAR and MPO-ANCApositive IgG stimulation. TLR4 siRNA significantly reduced the expression of ICAM-1 and VCAM-1 mRNA levels induced by uPAR and MPO-ANCA-positive IgG. The TLR4 antagonist significantly downregulated the levels of ICAM-1 mRNA in cells and sICAM-1 in the supernatants of GEnCs treated with uPAR plus MPOANCA- positive IgG. PLAUR is a core gene in bioinformatics analysis.
Conclusion: uPAR protein can enhance the GEnC activation and injury induced by MPO-ANCA-positive IgG through the TLR4 pathway, indicating that suPAR may be involved in the pathogenesis of AAV and that su- PAR might be regarded as a potential therapeutic target.
uPAR, antineutrophil cytoplasmic antibody, vasculitis, GEnC, TLR4, bioinformatics analysis.