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1.
J Immunol Res ; 2022: 5326083, 2022.
Article in English | MEDLINE | ID: mdl-35733922

ABSTRACT

Kidney transplantation is the ideal treatment for end-stage renal disease (ESRD). Chronic antibody-mediated rejection (CAMR) is the main cause of graft failure. Tfh and B cells are key immune cells that play important roles in CAMR. In this study, the populations of different Tfh cell phenotypes and B cell subsets in CAMR were investigated in a total of 36 patients. Based on Banff-2019, 15 patients were diagnosed with CAMR (CAMR group), 11 recipients were diagnosed with recurrent or de novo IgA nephropathy (IgAN group), and 10 patients displayed stable renal function (stable group). The Tfh and B cell subsets were analyzed by flow cytometry. The percentage and absolute number of PD-1+ICOS+Tfh cells were significantly higher in CAMR (p < 0.05), as was the ratio of CD226+Tfh cells to TIGIT+Tfh cells (p < 0.05). Compared with stable recipients, CAMR patients had lower naïve B cells and higher unswitched memory B cells, which were also significantly related to renal function (p < 0.05). Using the logistic regression model, we concluded that the estimated glomerular filtration rate (eGFR), absolute number of PD-1+ICOS+Tfh cells, and ratio of CD226+Tfh cells to TIGIT+Tfh cells were independent risk factors for CAMR. The combination of eGFR, PD-1+ICOS+Tfh cells, and the ratio of CD226+Tfh cells to TIGIT+Tfh cells showed better diagnostic efficacy for CAMR than each single parameter. The collective findings show that monitoring different Tfh phenotypes and B cell subsets is beneficial to kidney transplant recipients and implicate the combination of eGFR, number of PD-1+ICOS+Tfh cells, and ratio of CD226+Tfh cells to TIGIT+Tfh cells as a biomarker for diagnosing CAMR. The findings may also inform new strategies to identify and treat CAMR.


Subject(s)
Glomerulonephritis, IGA , Graft Rejection , Graft vs Host Disease , Kidney Transplantation , Antibodies , Antigens, Differentiation, T-Lymphocyte/metabolism , Biomarkers/metabolism , Graft vs Host Disease/etiology , Humans , Inducible T-Cell Co-Stimulator Protein/metabolism , Kidney Transplantation/adverse effects , Programmed Cell Death 1 Receptor/metabolism , Receptors, Immunologic , T Follicular Helper Cells
2.
J Clin Lab Anal ; 36(2): e24200, 2022 Feb.
Article in English | MEDLINE | ID: mdl-34957609

ABSTRACT

BACKGROUND: The roles of PD-1+ CXCR5+ follicular helper CD8+ T cell were reported in different disease conditions, but their roles in transplantation are unclear. In this study, the association between PD-1+ CXCR5+ follicular helper CD8+ T cell and renal allograft dysfunction in kidney transplant recipients (KTRs) was investigated. METHODS: 82 KTRs were enrolled in this study. 45 KTRs were included in the chronic allograft dysfunction (CAD) group, and 37 KTRs were included in the stable recipients group. Among the CAD group, 12 cases of antibody-mediated rejection (ABMR) and 4 cases of T cell-mediated rejection (TCMR) were diagnosed by biopsy. The percentage of CXCR5+ CD8+ T cells and the co-expression of signal transducers and activators of transcription 4 (STAT4), STAT5, and PD-1 in peripheral blood were determined by flow cytometry. RESULTS: The expression of CXCR5 on CD3+ CD8+ T cells and the percentage of STAT5+ CXCR5+ cells in the CD3+ CD8+ T-cell population were significantly lower in the CAD group (p < 0.05), while the expression of PD-1+ CXCR5+ CD8+ T cells was significantly higher (p < 0.05). Through logistic regression analysis, we concluded that the percentage of PD-1+ CXCR5+ CD8+ T cells was an independent risk factor for renal dysfunction. Grouping by pathological type, PD-1+ CXCR5+ CD8+ T cells showed relatively good diagnostic efficacy for ABMR by ROC analysis. CONCLUSIONS: Our results suggested that PD-1+ CXCR5+ CD8+ T cells were a promising biomarker for distinguishing renal allograft dysfunction and different allograft pathological types. Also, our findings may provide new ways of identifying and treating allograft rejection.


Subject(s)
Kidney Transplantation , Kidney/physiopathology , Programmed Cell Death 1 Receptor/metabolism , T Follicular Helper Cells/physiology , Adult , Allografts , Biomarkers , CD8-Positive T-Lymphocytes/physiology , Female , Graft Rejection/diagnosis , Humans , Logistic Models , Male , Middle Aged , Programmed Cell Death 1 Receptor/physiology , ROC Curve , Receptors, CXCR5/metabolism , T Follicular Helper Cells/metabolism
3.
Clin Biochem ; 102: 19-25, 2022 Apr.
Article in English | MEDLINE | ID: mdl-34968481

ABSTRACT

BACKGROUND: In our previous study, serum soluble T-cell immunoglobulin and mucin structure-3 (sTim-3) and galactosin-9 (sGal-9) were found to be associated with renal function after kidney transplantation. However, it is unclear whether these two indicators can predict adverse outcomes after transplantation. METHODS: Ninety-one recipients of kidney transplantation were enrolled and divided into a stable group and an adverse outcome group (consisting of biopsy-proven rejection, graft loss, death and clinically diagnosed rejection). The expression levels of sTim-3 and sGal-9 before (pre-Tim-3 and pre-Gal-9) and one month after transplantation (post-Tim-3 and post-Gal-9) were measured by ELISA. RESULTS: The level of pre-Tim-3 was significantly higher in the stable group than in the adverse outcome group [median (range), 2275 (840-4236) pg/mL vs. 1589 (353-3094) pg/mL, P = 0.002]. The level of post-Gal-9 was significantly lower in the stable group than in the adverse outcome group [median (range), 4869 (1418-13080) pg/mL vs. 6852: (4128-10760) pg/mL, P = 0.003]. The areas under the curve (AUCs) for pre-Tim-3 and post-Gal-9 were 0.737 (P = 0.002) and 0.751 (P = 0.003), respectively, better than AUC of post-eGFR (0.633) (P = 0.071), according to the receiver operating characteristic (ROC) curve. Through Cox regression analysis, including pre-Tim-3, post-Gal-9, post-eGFR, sex, age, BMI of recipients and donors, pre-Tim-3 and post-Gal-9 were independent risk factors for adverse outcomes after kidney transplantation (P = 0.016, P = 0.033, respectively). CONCLUSION: Serum sTim-3 and sGal-9 can predict adverse outcomes within two years after kidney transplantation.


Subject(s)
Hepatitis A Virus Cellular Receptor 2 , Kidney Transplantation , Area Under Curve , Cohort Studies , Graft Rejection/diagnosis , Humans , Kidney Transplantation/adverse effects , ROC Curve
4.
Medicine (Baltimore) ; 100(11): e24762, 2021 Mar 19.
Article in English | MEDLINE | ID: mdl-33725942

ABSTRACT

ABSTRACT: Chemokines are majorly involved in inflammatory and immune responses. The interferon-γ-inducible chemokines C-X-C motif chemokines 9 and 10 (CXCL9 and CXCL10) are considerably associated with Th1 cells and monocytes, and their expression levels rapidly increase during the early episodes of renal allograft rejection and various infectious diseases. CXCL13 is one of the most potent B-cell and T follicular helper-cell chemoattractants. The expression of CXCL13 in the presence of infection indicates an important chemotactic activity in multiple infectious diseases. C-C motif chemokine ligand 2 (CCL2) can attract monocytes and macrophages during inflammatory responses. However, there are no studies on the role of these chemokines in posttransplant infection in kidney transplant recipients.In this study, CXCL9, CXCL10, CXCL13, and CCL2 were analyzed using the Bio-Plex suspension array system before transplant and 30 days after transplant.The serum levels of CXCL9 and CXCL13 30 days after kidney transplant were associated with infection within 1 year after transplant (P = .021 and P = .002, respectively). The serum levels of CXCL9 and CXCL13 before surgery and those of CCL2 and CXCL10 before and after surgery were not associated with infection within 1 year after transplant (P > .05). The combination of postoperative day (POD) 30 CXCL9 and postoperative day 30 CXCL13 provided the best results with an area under the curve of 0.721 (95% confidence interval, 0.591-0.852), with a sensitivity of 71.4% and specificity of 68.5% at the optimal cutoff value of 52.72 pg/mL.As important chemokines, CXCL9 and CXCL13 could be used to predict the occurrence of infection after kidney transplant.


Subject(s)
Chemokine CXCL13/blood , Chemokine CXCL9/blood , Infections/etiology , Kidney Diseases/blood , Kidney Transplantation/adverse effects , Postoperative Complications/etiology , Adult , Biomarkers/blood , Chemokine CCL2/blood , Chemokine CXCL10/blood , Female , Humans , Kidney Diseases/surgery , Male , Middle Aged , Postoperative Period , Predictive Value of Tests , Preoperative Period , Retrospective Studies
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