Intragraft Molecular Pathways Associated with Tolerance Induction in Renal Transplantation

Multi-omics Approach in Kidney Transplant: Lessons Learned from COVID-19 Pandemic

Purpose of Review

Multi-omics approach has advanced our knowledge on transplantation-associated clinical outcomes, such as acute rejection and infection, and emerging omics data are becoming available in kidney transplant and COVID-19. Herein, we discuss updated findings of multi-omics data on kidney transplant outcomes, as well as COVID-19 and kidney transplant.

Recent Findings

Transcriptomics, proteomics, and metabolomics revealed various inflammation pathways associated with kidney transplantation-related outcomes and COVID-19. Although multi-omics data on kidney transplant and COVID-19 is limited, activation of innate immune pathways and suppression of adaptive immune pathways were observed in the active phase of COVID-19 in kidney transplant recipients.

Summary

Multi-omics analysis has led us to a deeper exploration and a more comprehensive understanding of key biological pathways in complex clinical settings, such as kidney transplantation and COVID-19. Future multi-omics analysis leveraging multi-center biobank collaborative will further advance our knowledge on the precise immunological responses to allograft and emerging pathogens.

Chimerism-based Tolerance Induction in Clinical Transplantation: Its Foundations and Mechanisms

Hematopoietic chimerism remains the most promising strategy to bring transplantation tolerance into clinical routine. The concept of chimerism-based tolerance aims to extend the recipient's mechanisms of self-tolerance (ie, clonal deletion, anergy, and regulation) to include the tolerization of donor antigens that are introduced through the cotransplantation of donor hematopoietic cells. For this to be successful, donor hematopoietic cells need to engraft in the recipient at least temporarily. Three pioneering clinical trials inducing chimerism-based tolerance in kidney transplantation have been published to date. Within this review, we discuss the mechanisms of tolerance that are associated with the specific therapeutic protocols of each trial. Recent data highlight the importance of regulation as a mechanism that maintains tolerance. Insufficient regulatory mechanisms are also a likely explanation for situations of tolerance failure despite persisting donor chimerism. After decades of preclinical development of chimerism protocols, mechanistic data from clinical trials have recently become increasingly important. Better understanding of the required mechanisms for tolerance to be induced in humans will be a key to design more reliable and less invasive chimerism protocols in the future.

Transcriptomic analysis reveals partial epithelial-mesenchymal transition and inflammation as common pathogenic mechanisms in hypertensive nephrosclerosis and Type 2 diabetic nephropathy

Hypertensive nephrosclerosis (HN) and Type 2 diabetic nephropathy (T2DN) are the leading causes of chronic kidney disease (CKD). To explore shared pathogenetic mechanisms, we analyzed transcriptomes of kidney biopsies from patients with HN or T2DN. Total RNA was extracted from 10 μm whole kidney sections from patients with HN, T2DN, and normal controls (Ctrl) (n = 6 for each group) and processed for RNA sequencing. Differentially expressed (log2 fold change >1, adjusted p < 0.05) genes (DEG) and molecular pathways were analyzed, and selected results were validated by immunohistochemistry (IHC). ELISA on serum samples was performed on a related cohort consisting of patients with biopsy-proven HN (n = 13) and DN (n = 9), and a normal control group (n = 14). Cluster analysis on RNA sequencing data separated diseased and normal tissues. RNA sequencing revealed that 88% (341 out of 384) of DEG in HN were also altered in T2DN, while gene set enrichment analysis (GSEA) showed that over 90% of affected molecular pathways, including those related to inflammation, immune response, and cell-cycle regulation, were similarly impacted in both HN and T2DN samples. The increased expression of genes tied to interleukin signaling and lymphocyte activation was more pronounced in HN, while genes associated with extracellular matrix organization were more evident in T2DN. Both HN and T2DN tissues exhibited significant upregulation of genes connected with inflammatory responses, T-cell activity, and partial epithelial to mesenchymal transition (p-EMT). Immunohistochemistry (IHC) further confirmed T-cell (CD4+ and CD8+ ) infiltration in the diseased tissues. Additionally, IHC revealed heightened AXL protein expression, a key regulator of inflammation and p-EMT, in both HN and T2DN, while serum analysis indicated elevated soluble AXL levels in patients with both conditions. These findings underline the shared molecular mechanisms between HN and T2DN, hinting at the potential for common therapeutic strategies targeting both diseases.

Chimerism-Based Tolerance to Kidney Allografts in Humans: Novel Insights and Future Perspectives

Chronic rejection and immunosuppression-related toxicity severely affect long-term outcomes of kidney transplantation. The induction of transplantation tolerance – the lack of destructive immune responses to a transplanted organ in the absence of immunosuppression – could potentially overcome these limitations. Immune tolerance to kidney allografts from living donors has been successfully achieved in humans through clinical protocols based on chimerism induction with hematopoietic cell transplantation after non-myeloablative conditioning. Notably, two of these protocols have led to immune tolerance in a significant fraction of HLA-mismatched donor-recipient combinations, which represent the large majority of cases in clinical practice. Studies in mice and large animals have been critical in dissecting tolerance mechanisms and in selecting the most promising approaches for human translation. However, there are several key differences in tolerance induction between these models and humans, including the rate of success and stability of donor chimerism, as well as the relative contribution of different mechanisms in inducing donor-specific unresponsiveness. Kidney allograft tolerance achieved through durable full-donor chimerism may be due to central deletion of graft-reactive donor T cells, even though mechanistic data from patient series are lacking. On the other hand, immune tolerance attained with transient mixed chimerism-based protocols initially relies on Treg-mediated suppression, followed by peripheral deletion of donor-reactive recipient T-cell clones under antigenic pressure from the graft. These conclusions were supported by data deriving from novel high-throughput T-cell receptor sequencing approaches that allowed tracking of alloreactive repertoires over time. In this review, we summarize the most important mechanistic studies on tolerance induction with combined kidney-bone marrow transplantation in humans, discussing open issues that still need to be addressed and focusing on techniques developed in recent years to efficiently monitor the alloresponse in tolerance trials. These cutting-edge methods will be instrumental for the development of immune tolerance protocols with improved efficacy and to identify patients amenable to safe immunosuppression withdrawal.

Advances of miRNAs in kidney graft injury

Kidney transplantation is the preferred treatment for patients with end-stage renal disease. However, various types of kidney graft injury after transplantation are still key factors that affect the survival of the kidney graft. Therefore, exploring the underlying mechanisms involved is very important. Current diagnostic measures for kidney graft injury (including needle biopsy, blood creatinine, eGFR, etc.) have many limiting factors such as invasiveness, insufficient sensitivity and specificity, so they cannot provide timely and effective information to clinicians. As for kidney grafts that have occurred injury, the traditional treatment has a little efficacy and many side effects. Therefore, there is an urgent need for developing new biomarkers and targeted treatment for kidney graft injury. Recently, studies have found that miRNAs are involved in the regulation of the progression of kidney graft injury. At the same time, it has high stability in blood, urine, and other body fluids, so it is suggested to have the potential as a biomarker and therapeutic target for kidney graft injury. Here, we reviewed the miRNAs involved in the pathophysiology of kidney graft injury such as ischemia/reperfusion injury, acute rejection, drug-induced nephrotoxicity, chronic allograft dysfunction, BK virus infection, and the latest advances of miRNAs as biomarkers and therapeutic targets of kidney graft injury, then summarized the specific data of miRNAs expression level in kidney graft injury, which aims to provide a reference for subsequent basic research and clinical transformation.

Tolerance induction with donor hematopoietic stem cell infusion in kidney transplantation: a single-center experience in China with a 10-year follow-up

Background

Immunosuppressive therapy after life-saving kidney transplantation increases the risk of infection, cardiovascular diseases, metabolic diseases, and cancer. To date, four centers (three in the USA and one in South Korea) have reported clinical tolerance trials in kidney transplantation. We performed the first Chinese clinical trial in which kidney transplantation was combined with donor hematopoietic stem cell (DHSC) infusion to induce tolerance. This study summarizes the 10-year follow-up results.

Methods

From 2009 to 2017, 11 donor/recipient pairs underwent living-related kidney transplantation combined with DHSC infusion. Two of the pairs were human leukocyte antigen (HLA)-matched, and nine were HLA-mismatched. DHSCs were mobilized using granulocyte colony-stimulating factor (G-CSF) and harvested 1 day before transplantation. The recipients received consecutive total lymphoid irradiation (TLI) for 3 days before kidney transplantation. The induction drug was anti-thymocyte globulin (ATG). DHSCs were infused on days 2, 4, and 6 post surgery. All patients were followed-up until Dec 2019. Routine laboratory examinations, chimerism, biopsies, and mixed lymphocyte reactions were performed.

Results

One HLA-matched recipient had 30-50% chimerism, while the other patients had less than 1% chimerism. Recipients had donor-specific hyporesponsiveness (DSH) while sustaining normal reactivity to non-donors in mixed lymphocyte reactions. All recipients were followed up for 717-3,918 days. One recipient lost allograft function, and 10 recipients had stable renal function. None of the 11 recipients developed myelosuppression or graft-versus-host disease (GVHD) post transplantation. Our protocol did not increase the risk of infection. Allograft biopsy confirmed that one patient had mild rejection with Banff grade IA, while the other ten recipients did not develop rejection. Five patients were able to reduce the dose of their immunosuppressive therapy.

Conclusions

Our immune tolerance induction protocol, which used DHSC infusion and TLI, achieved low dose immunosuppression with long-term stable kidney allograft survival in Chinese patients.

Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review

BACKGROUND

The purpose of this review is to depict current research and impact of artificial intelligence/machine learning (AI/ML) algorithms on dialysis and kidney transplantation. Published studies were presented from two points of view: What medical aspects were covered? What AI/ML algorithms have been used?

METHODS

We searched four electronic databases or studies that used AI/ML in hemodialysis (HD), peritoneal dialysis (PD), and kidney transplantation (KT). Sixty-nine studies were split into three categories: AI/ML and HD, PD, and KT, respectively. We identified 43 trials in the first group, 8 in the second, and 18 in the third. Then, studies were classified according to the type of algorithm.

RESULTS

AI and HD trials covered: (a) dialysis service management, (b) dialysis procedure, (c) anemia management, (d) hormonal/dietary issues, and (e) arteriovenous fistula assessment. PD studies were divided into (a) peritoneal technique issues, (b) infections, and (c) cardiovascular event prediction. AI in transplantation studies were allocated into (a) management systems (ML used as pretransplant organ-matching tools), (b) predicting graft rejection, (c) tacrolimus therapy modulation, and (d) dietary issues.

CONCLUSIONS

Although guidelines are reluctant to recommend AI implementation in daily practice, there is plenty of evidence that AI/ML algorithms can predict better than nephrologists: volumes, Kt/V, and hypotension or cardiovascular events during dialysis. Altogether, these trials report a robust impact of AI/ML on quality of life and survival in G5D/T patients. In the coming years, one would probably witness the emergence of AI/ML devices that facilitate the management of dialysis patients, thus increasing the quality of life and survival.

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.