Changes in T and B cell subsets in end stage renal disease patients before and after kidney transplantation

Peripheral Blood Lymphocyte Subgroups in Patients Undergoing Hemodialysis with Medium Cutoff Membranes and High-Flux Membranes: THE SHE Continuation Study

INTRODUCTION

Chronic kidney disease (CKD) poses a significant global health burden, with increasing prevalence and high morbidity and mortality rates, particularly in end-stage kidney disease (ESKD). While traditional risk factors contribute, the exact mechanisms remain elusive, with inflammation playing a pivotal role. Medium cutoff (MCO) membranes offer promise in improving dialysis outcomes by efficiently clearing uremic toxins without substantial albumin loss. We aimed to elucidate the impact of MCO and high-flux (HF) membranes on peripheral blood lymphocyte subpopulations in hemodialysis patients.

METHODS

Twenty-four ESKD patients underwent 36 sessions each with MCO and HF membranes. Immunophenotyping by flow cytometry was performed to analyze lymphocyte subsets.

RESULTS

NK cell percentages significantly increased with MCO, returning to baseline with HF. Th1 cells decreased post-HF, while Th2 and Tfh cells increased with MCO and persisted. Treg cells remained stable with MCO but decreased with HF.

CONCLUSION

MCO dialysis induced an anti-inflammatory shift, evidenced by increased Th2 and Tfh cells and stable Treg cells. NK cells also responded favorably to MCO. These findings underscore MCO membranes' potential to modulate immune responses and improve patient outcomes in ESKD.

Kidney Transplantation and Cellular Immunity Dynamics: Immune Cell Alterations and Association with Clinical and Laboratory Parameters

Background/Objectives: The purpose of this study was to evaluate numerical changes in immune cells after successful kidney transplantation and associate their recovery with clinical and laboratory factors. Methods: In 112 kidney transplant recipients, we performed flow cytometry to evaluate counts of CD4+, CD8+, and regulatory T cells (Tregs), as well as natural killer (NK) cells, before kidney transplantation (T0) and three (T3), six (T6), and twelve (T12) months later. The results were associated with the recipient's age, cold ischemia time (CIT), the type of donor, dialysis method and vintage, and graft function in one year. Results: Total and CD8+ T cell counts increased gradually one year post transplantation in comparison with pre-transplantation levels, whereas the number of CD4+ T cells and Tregs increased, and the number of NK cells decreased in the first three months and remained stable thereafter. The recipient's age was negatively correlated with total, CD4+, and Treg counts at T12, whereas CIT affected only total and CD4+ T cell count. Moreover, recipients receiving kidneys from living donors presented better recovery of all T cell subsets at T12 in comparison with recipients receiving kidneys from cadaveric donors. Patients on peritoneal dialysis had increased numbers of total and CD8+ T cells, as well as NK cells. Finally, estimated glomerular filtration rate was positively correlated with Treg level and potentially CD4+ T cells one-year post transplantation. Conclusions: Successful kidney transplantation results in the recovery of most T cell subsets. Lower recipient age and better graft function contribute to increased T cell counts, whereas donor type and dialysis modality are the most important modifiable factors for optimal immune recovery.

Pre-Transplant Frequencies of FoxP3+CD25+ in CD3+CD8+ T Cells as Potential Predictors for CMV in CMV-Intermediate Risk Kidney Transplant Recipients

Cytomegalovirus (CMV) infection detrimentally influences graft survival in kidney transplant recipients, with the risk primarily determined by recipient and donor serostatus. However, recipient CD8+ T cells play a crucial role in CMV control. The optimal preventive strategy (prophylaxis vs. pre-emptive treatment), particularly for seropositive (intermediate risk) recipients, remains uncertain. We investigated CD8+ T cell subpopulation dynamics and CMV occurrence (DNAemia ≥ 100 IU/mL) in 65 kidney transplant recipients, collecting peripheral blood mononuclear cells before (T1) and 1 year after transplantation (T2). Comparing the two timepoints, we found an increase in granulocyte, monocyte and CD3+CD8+ T cells numbers, while FoxP3+CD25+, LAG-3+ and PD-1+ frequencies were reduced at T2. CMV DNAemia occurred in 33 recipients (55.8%) during the first year. Intermediate risk patients were disproportionally affected by posttransplant CMV (N = 29/45, 64.4%). Intermediate risk recipients developing CMV after transplantation exhibited lower leukocyte, monocyte, and granulocyte counts and higher FoxP3+CD25+ frequencies in CD3+CD8+ T cells pre-transplantation compared to patients staying CMV negative. Pre-transplant FoxP3+CD25+ in CD3+CD8+ T cells had the best discriminatory potential for CMV infection prediction within the first year after transplantation (AUC: 0.746). The FoxP3+CD25+ CD3+CD8+ T cell subset may aid in selecting intermediate risk kidney transplant recipients for CMV prophylaxis.

Evaluation of Regulatory B Cell Subpopulations CD24++CD38++, CD24++CD27+, Plasmablasts and Their Correlation with T Regs CD3+CD4+CD25+FOXP3+ in Dialysis Patients and Early Post-Transplant Rejection-Free Kidney Recipients

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.

Unravelling B cell heterogeneity: insights into flow cytometry-gated B cells from single-cell multi-omics data

Introduction

B cells play a pivotal role in adaptive immunity which has been extensively characterised primarily via flow cytometry-based gating strategies. This study addresses the discrepancies between flow cytometry-defined B cell subsets and their high-confidence molecular signatures using single-cell multi-omics approaches.

Methods

By analysing multi-omics single-cell data from healthy individuals and patients across diseases, we characterised the level and nature of cellular contamination within standard flow cytometric-based gating, resolved some of the ambiguities in the literature surrounding unconventional B cell subsets, and demonstrated the variable effects of flow cytometric-based gating cellular heterogeneity across diseases.

Results

We showed that flow cytometric-defined B cell populations are heterogenous, and the composition varies significantly between disease states thus affecting the implications of functional studies performed on these populations. Importantly, this paper draws caution on findings about B cell selection and function of flow cytometric-sorted populations, and their roles in disease. As a solution, we developed a simple tool to identify additional markers that can be used to increase the purity of flow-cytometric gated immune cell populations based on multi-omics data (AlliGateR). Here, we demonstrate that additional non-linear CD20, CD21 and CD24 gating can increase the purity of both naïve and memory populations.

Discussion

These findings underscore the need to reconsider B cell subset definitions within the literature and propose leveraging single-cell multi-omics data for refined characterisation. We show that single-cell multi-omics technologies represent a powerful tool to bridge the gap between surface marker-based annotations and the intricate molecular characteristics of B cell subsets.

Impact of Immunosenescence in Older Kidney Transplant Recipients: Associated Clinical Outcomes and Possible Risk Stratification for Immunosuppression Reduction

The number of older individuals receiving a kidney transplant as replacement therapy has significantly increased in the past decades and this increase is expected to continue. Older patients have a lower rate of acute rejection but an increased incidence of death with a functioning graft. Several factors, including an increased incidence of infections, post-transplant malignancy and cardiovascular comorbidity and mortality, contribute to this increased risk. Notwithstanding, kidney transplantation is still the best form of kidney replacement therapy in all patients with chronic kidney disease, including in older individuals. The best form of immunosuppression and the optimal dose of these medications in older recipients remains a topic of discussion. Pharmacological studies have usually excluded older patients and when included, patients were highly selected and their numbers insignificant to draw a reasonable conclusion. The reduced incidence of acute rejection in older recipients has largely been attributed to immunosenescence. Immunosenescence refers to the aging of the innate and adaptive immunity, accumulating in phenotypic and functional changes. These changes influences the response of the immune system to new challenges. In older individuals, immunosenescence is associated with increased susceptibility to infectious pathogens, a decreased response after vaccinations, increased risk of malignancies and cardiovascular morbidity and mortality. Chronic kidney disease is associated with premature immunosenescent changes, and these are independent of aging. The immunosenescent state is associated with low-grade sterile inflammation termed inflammaging. This chronic low-grade inflammation triggers a compensatory immunosuppressive state to avoid further tissue damage, leaving older individuals with chronic kidney disease in an immune-impaired state before kidney transplantation. Immunosuppression after transplantation may further enhance progression of this immunosenescent state. This review covers the role of immunosenescence in older kidney transplant recipients and it details present knowledge of the changes in chronic kidney disease and after transplantation. The impact of immunosuppression on the progression and complications of an immunosenescent state are discussed, and the future direction of a possible clinical implementation of immunosenescence to individualize/reduce immunosuppression in older recipients is laid out.

Host-Microbe Multi-omic Profiling Identifies a Unique Program of COVID-19 Inflammatory Dysregulation in Solid Organ Transplant Recipients

Coronavirus disease 2019 (COVID-19) poses significant risks for solid organ transplant (SOT) recipients, who have atypical but poorly characterized immune responses to SARS-CoV-2 infection. We sought to understand and the host immunologic and microbial features of COVID-19 in SOT recipients by leveraging a prospective multicenter cohort of 1164 hospitalized patients. Using multi-omic immuoprofiling, we studied 86 SOT recipients in this cohort, who were age- and sex-matched 2:1 with 172 non-SOT controls. PBMC and nasal transcriptional profiling unexpectedly demonstrated upregulation of innate immune pathways related to interferon (IFN) and Toll-like receptor signaling, and complement activation, in SOT recipients. Longitudinal analyses across the first 30-days post-hospitalization demonstrated persistent upregulation of these innate immunity pathways in SOT recipients. The levels of several proinflammatory serum chemokines, such as CX3CL1 and KITLG, were also higher in SOT recipients at the time of hospitalization, although IFN-gamma levels were lower. We observed differential dynamics of CXCL11, which remained persistently elevated in SOT recipients over the course of hospitalization. Nasal microbiome alpha diversity was higher in SOT recipients versus controls, but no differences in taxonomic abundance beyond SARS-CoV-2 were observed. SOT recipients had higher nasal SARS-CoV-2 viral loads and impaired viral clearance compared to controls. Antibody analysis demonstrated lower anti-SARS-CoV-2 spike IgG levels in SOT recipients upon hospitalization, but no distinctions over time compared to controls. Mass cytometry demonstrated marked differences in blood immune cell populations, with SOT recipients exhibiting decreased plasmablasts and transitional B cells, and increased senescent T cells. Severe disease in SOT recipients was characterized by a less robust induction of inflammatory chemokines, such as IL-6 and CCL7, and a more subtle proinflammatory transcriptional response in the blood and airway. Together, our study reveals distinct immune features and altered viral dynamics in SOT recipients compared to non-SOT controls. We unexpectedly find that SOT recipients exhibit an augmented, predominantly innate immune response in both the blood and upper respiratory tract that remains relatively stable across disease severity, in contrast to non-SOT controls. These findings may relate to the paradoxical observation that SOT recipients have similar COVID-19 mortality rates versus the general population, despite being more susceptible to SARS-CoV-2 infection, remaining infectious longer, and having higher rates of hospitalization. In summary, we find that COVID-19 in SOT recipients is characterized by a biologically distinct immune state, suggesting the potential for unique prognostic biomarkers and therapeutic approaches in this vulnerable population.

Exploring Perturbations in Peripheral B Cell Memory Subpopulations Early after Kidney Transplantation Using Unsupervised Machine Learning

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.

Immune landscape in rejection of renal transplantation revealed by high-throughput single-cell RNA sequencing

Background: The role of the cellular level in kidney transplant rejection is unclear, and single-cell RNA sequencing (scRNA-seq) can reveal the single-cell landscape behind rejection of human kidney allografts at the single-cell level. Methods: High-quality transcriptomes were generated from scRNA-seq data from five human kidney transplantation biopsy cores. Cluster analysis was performed on the scRNA-seq data by known cell marker genes in order to identify different cell types. In addition, pathways, pseudotime developmental trajectories and transcriptional regulatory networks involved in different cell subpopulations were explored. Next, we systematically analyzed the scoring of gene sets regarding single-cell expression profiles based on biological processes associated with oxidative stress. Results: We obtained 81,139 single cells by scRNA-seq from kidney transplant tissue biopsies of three antibody-mediated rejection (ABMR) patients and two acute kidney injury (AKI) patients with non-rejection causes and identified 11 cell types, including immune cells, renal cells and several stromal cells. Immune cells such as macrophages showed inflammatory activation and antigen presentation and complement signaling, especially in rejection where some subpopulations of cells specifically expressed in rejection showed specific pro-inflammatory responses. In addition, patients with rejection are characterized by an increased number of fibroblasts, and further analysis of subpopulations of fibroblasts revealed their involvement in inflammatory and fibrosis-related pathways leading to increased renal rejection and fibrosis. Notably, the gene set score for response to oxidative stress was higher in patients with rejection. Conclusion: Insight into histological differences in kidney transplant patients with or without rejection was gained by assessing differences in cellular levels at single-cell resolution. In conclusion, we applied scRNA-seq to rejection after renal transplantation to deconstruct its heterogeneity and identify new targets for personalized therapeutic approaches.

Kidney allograft rejection is associated with an imbalance of B cells, regulatory T cells and differentiated CD28-CD8+ T cells: analysis of a cohort of 1095 graft biopsies

Introduction

The human immune system contains cells with either effector/memory or regulatory functions. Besides the well-established CD4+CD25hiCD127lo regulatory T cells (Tregs), we and others have shown that B cells can also have regulatory functions since their frequency and number are increased in kidney graft tolerance and B cell depletion as induction therapy may lead to acute rejection. On the other hand, we have shown that CD28-CD8+ T cells represent a subpopulation with potent effector/memory functions. In the current study, we tested the hypothesis that kidney allograft rejection may be linked to an imbalance of effector/memory and regulatory immune cells.

Methods

Based on a large cohort of more than 1000 kidney graft biopsies with concomitant peripheral blood lymphocyte phenotyping, we investigated the association between kidney graft rejection and the percentage and absolute number of circulating B cells, Tregs, as well as the ratio of B cells to CD28-CD8+ T cells and the ratio of CD28-CD8+ T cells to Tregs. Kidney graft biopsies were interpreted according to the Banff classification and divided into 5 biopsies groups: 1) normal/subnormal, 2) interstitial fibrosis and tubular atrophy grade 2/3 (IFTA), 3) antibody-mediated rejection (ABMR), 4) T cell mediated-rejection (TCMR), and 5) borderline rejection. We compared group 1 with the other groups as well as with a combined group 3, 4, and 5 (rejection of all types) using multivariable linear mixed models.

Results and discussion

We found that compared to normal/subnormal biopsies, rejection of all types was marginally associated with a decrease in the percentage of circulating B cells (p=0.06) and significantly associated with an increase in the ratio of CD28-CD8+ T cells to Tregs (p=0.01). Moreover, ABMR, TCMR (p=0.007), and rejection of all types (p=0.0003) were significantly associated with a decrease in the ratio of B cells to CD28-CD8+ T cells compared to normal/subnormal biopsies. Taken together, our results show that kidney allograft rejection is associated with an imbalance between immune cells with effector/memory functions and those with regulatory properties.

Single-Cell Transcriptome Analysis of Chronic Antibody-Mediated Rejection After Renal Transplantation

Renal transplantation is currently the most effective treatment for end-stage renal disease. However, chronic antibody-mediated rejection (cABMR) remains a serious obstacle for the long-term survival of patients with renal transplantation and a problem to be solved. At present, the role and mechanism underlying immune factors such as T- and B- cell subsets in cABMR after renal transplantation remain unclear. In this study, single-cell RNA sequencing (scRNA-seq) of peripheral blood monocytes (PBMCs) from cABMR and control subjects was performed to define the transcriptomic landscape at single-cell resolution. A comprehensive scRNA-seq analysis was performed. The results indicated that most cell types in the cABMR patients exhibited an intense interferon response and release of proinflammatory cytokines. In addition, we found that the expression of MT-ND6, CXCL8, NFKBIA, NFKBIZ, and other genes were up-regulated in T- and B-cells and these genes were associated with pro-inflammatory response and immune regulation. Western blot and qRT-PCR experiments also confirmed the up-regulated expression of these genes in cABMR. GO and KEGG enrichment analyses indicated that the overexpressed genes in T- and B-cells were mainly enriched in inflammatory pathways, including the TNF, IL-17, and Toll-like receptor signaling pathways. Additionally, MAPK and NF-κB signaling pathways were also involved in the occurrence and development of cABMR. This is consistent with the experimental results of Western blot. Trajectory analysis assembled the T-cell subsets into three differentiation paths with distinctive phenotypic and functional prog rams. CD8 effector T cells and γδ T cells showed three different differentiation trajectories, while CD8_MAI T cells and naive T cells primarily had two differentiation trajectories. Cell-cell interaction analysis revealed strong T/B cells and neutrophils activation in cABMR. Thus, the study offers new insight into pathogenesis and may have implications for the identification of novel therapeutic targets for cABMR.