Background: B cells have a significant role in transplantation. We examined the distribution of memory subpopulations (MBCs) and naïve B cell (NBCs) phenotypes in patients soon after kidney transplantation. Unsupervised machine learning cluster analysis is used to determine the association between the cellular phenotypes and renal function. Methods: MBC subpopulations and NBCs from 47 stable renal transplant recipients were characterized by flow cytometry just before (T0) and 6 months after (T6) transplantation. T0 and T6 measurements were compared, and clusters of patients with similar cellular phenotypic profiles at T6 were identified. Two clusters, clusters 1 and 2, were formed, and the glomerular filtration rate was estimated (eGFR) for these clusters. Results: A significant increase in NBC frequency was observed between T0 and T6, with no statistically significant differences in the MBC subpopulations. Cluster 1 was characterized by a predominance of the NBC phenotype with a lower frequency of MBCs, whereas cluster 2 was characterized by a high frequency of MBCs and a lower frequency of NBCs. With regard to eGFR, cluster 1 showed a higher value compared to cluster 2. Conclusions: Transplanted kidney patients can be stratified into clusters based on the combination of heterogeneity of MBC phenotype, NBCs and eGFR using unsupervised machine learning.

Background: B and T regulatory cells, also known as Bregs and Tregs, are involved in kidney transplantation. The purpose of this study is to monitor changes in the frequency and absolute numbers of Tregs (CD3+CD4+CD25+FoxP3+), transitional Bregs (tBregs) (CD24++CD38++), memory Bregs (mBregs) (CD24++CD27+), and plasmablasts before (T0) and six months (T6) after transplantation. Additionally, we aim to investigate any correlation between Tregs and tBregs, mBregs, or plasmablasts and their relationship with graft function. Methods: Flow cytometry was used to immunophenotype cells from 50 kidney recipients who did not experience rejection. Renal function was assessed using the estimated glomerular filtration rate (eGFR). Results: At T6, there was a significant decrease in the frequency of Tregs, plasmablasts, and tBregs, as well as in the absolute number of tBregs. The frequency of mBregs, however, remained unchanged. Graft function was found to have a positive correlation with the frequency of tBregs and plasmablasts. A significant correlation was observed between the frequency and absolute number of tBregs only when the eGFR was greater than 60 but not at lower values. At an eGFR greater than 60, there was a positive correlation between the absolute numbers of Tregs and mBregs but not between Tregs and tBregs. No correlation was observed for any cell population in dialysis patients. Conclusions: The data show a correlation between the frequency and absolute number of tBregs and the absolute number of Tregs and mBregs with good renal function in the early post-transplant period.

Background: Detailed characterization of B cells in dialysis patients who are candidates for kidney transplant is still lacking, with little information on how dialysis duration and modality impact B cell subsets. Methods: Cluster analysis of flow cytometry determined the frequencies and absolute numbers of B-cell subsets and divided the cohort of 78 candidates into two distinct clusters, one with shorter and one with longer dialysis duration. Results: The immune profiles of the clusters differed depending on whether frequencies or absolute counts were considered. In long-term dialysis patients, the frequency of total memory, double negative and marginal zone B cells increased, while the frequency of naive and regulatory B cells decreased. This pattern was reversed in short-term dialysis patients, with a decrease in memory and an increase in naive and regulatory populations. The B subset number decreased significantly in long-term dialysis patients, while it increased significantly in short-term dialysis patients. The dialysis modality affected the frequency-based subset immune profiles. Conclusions: It is important to determine whether the evaluation is based on frequencies or absolute numbers. The different distribution of B cell subsets in the clusters, in terms of frequencies and absolute numbers, was influenced by dialysis duration. Modality and age only influenced the frequencies.

Objectives/Background: B lymphocytes are involved in both graft function and rejection. The role of double-negative (DN) and marginal zone B (MZB) lymphocytes in transplantation remains unclear. This study aims to investigate their role one year after transplant. Methods: The frequency and absolute numbers of DN and MZB cells were determined by flow cytometry before transplantation and at 3, 6 and 12 months after transplant. They were correlated with graft function and rejection. Results: Both the frequency and absolute number of MZB and DN cells increased 12 months after transplantation. Variations were observed in the populations studied at different time points. The observed decrease in the frequency of MZB lymphocytes in kidney recipients with rejection at 12 months, the end of follow-up, was associated with rejection episodes. On ROC curve analysis, a cut-off value of <20.6% could be a predictor of rejection risk in the first 12 months after transplantation (sensitivity 72.7%, specificity 69.6%). No relationship was found between the frequencies and absolute numbers of cell populations and graft function at any time point. Conclusions: The kinetics of B cells (DN and MZB) were determined over the course of 12 months after kidney transplantation. The frequency of MZ B cells was associated with rejection episodes.

Background: The clinical relevance of circulating B-cell subpopulations during the early period after kidney transplantation remains incompletely understood. Methods: In this prospective single-center study, frequencies and absolute numbers of peripheral B-cell subpopulations were longitudinally assessed by flow cytometry in 71 kidney transplant recipients before transplantation (T0) and at 3 (T3), 6 (T6) and 12 months (T12) post-transplant. Associations with graft function, rejection episodes and clinical variables were explored. Results: During the first post-transplant year, relative frequencies of total and naïve B cells declined, whereas absolute counts showed modest increases. Memory B-cells expanded over time, driven by both class-switched (CSBC) and class-non-switched (CNSBC) subsets. Transitional regulatory B cells (tBregs) and plasmablasts decreased significantly, while memory regulatory B cells (mBregs) remained stable. Pre-transplant B-cell profiles did not differ between recipients experienced rejection and those with stable graft function. At T12, rejection was associated with a shift toward a memory-dominant peripheral profile, characterized by reduced naïve representation. tBregs showed modest positive associations with graft function during follow-up. Hierarchical clustering identified naïve- and memory-dominant phenotypes representing distinct post-transplant immune compositions. Conclusions: Early post-transplant peripheral B-cell landscapes are dynamic and heterogeneous. Peripheral B-cell phenotyping shows limited value as a standalone clinical monitoring tool.