AJKD Atlas of Renal Pathology: acute antibody-mediated rejection

Diagnosis and classification of kidney transplant rejection using machine learning-assisted surface-enhanced Raman spectroscopy using a single drop of serum

The quest to reduce kidney transplant rejection has emphasized the urgent requirement for the development of non-invasive, precise diagnostic technologies. These technologies aim to detect antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR), which are asymptomatic and pose a risk of potential kidney damage. The protocols for managing rejection caused by ABMR and TCMR differ, and diagnosis has traditionally relied on invasive biopsy procedures. Therefore, a convergence system using a nano-sensing chip, Raman spectroscopy, and AI technology was introduced to facilitate diagnosis using serum samples obtained from patients with no major abnormality, ABMR, and TCMR after kidney transplantation. Tissue biopsy and Banff score analysis were performed across the groups for validation, and 5 μL of serum obtained at the same time was added onto the Au-ZnO nanorod-based Surface-Enhanced Raman Scattering sensing chip to obtain Raman spectroscopy signals. The accuracy of machine learning algorithms for principal component-linear discriminant analysis and principal component-partial least squares discriminant analysis was 93.53% and 98.82%, respectively. The collagen (an indicative of kidney injury), creatinine, and amino acid-derived signals (markers of kidney function) contributed to this accuracy; however, the high accuracy was primarily due to the ability of the system to analyze a broad spectrum of various biomarkers.

Impact of Early Rejection Treatment on Infection Development in Kidney Transplant Recipients: A Propensity Analysis

Introduction

The impact of renal allograft rejection treatment on infection development has not been formally defined in the literature.

Methods

We conducted a retrospective cohort study of 185 rejection (case) and 185 nonrejection (control) kidney transplant patients treated at our institution from 2014 to 2020 to understand the impact of rejection on infection development. Propensity scoring was used to match cohorts. We collected data for infections within 6 months of rejection for the cases and 18 months posttransplant for controls.

Results

In 370 patients, we identified 466 infections, 297 in the controls, and 169 in the cases. Urinary tract infections (38.9%) and cytomegalovirus viremia (13.7%) were most common. Cumulative incidence of infection between the case and controls was 2.17 (CI 1.54-3.05); p < 0.001. There was no difference in overall survival (HR 0.90, CI 0.49-1.66) or graft survival (HR 1.27, CI 0.74-2.20) between the groups. There was a significant difference in overall survival (HR 2.28, CI 1.14-4.55; p = 0.019) and graft survival (HR 1.98, CI 1.10-3.56; p = 0.023) when patients with infection were compared to those without.

Conclusions

As previously understood, rejection treatment is a risk factor for subsequent infection development. Our data have defined this relationship more clearly. This study is unique, however, in that we found that infections, but not rejection, negatively impacted both overall patient survival and allograft survival, likely due to our institution's robust post-rejection protocols. Clinicians should monitor patients closely for infections in the post-rejection period and have a low threshold to treat these infections while also restarting appropriate prophylaxis.

Identification of PDCD1 as a potential biomarker in acute rejection after kidney transplantation via comprehensive bioinformatic analysis

Background

Acute rejection is a determinant of prognosis following kidney transplantation. It is essential to search for novel noninvasive biomarkers for early diagnosis and prompt treatment.

Methods

Gene microarray data was downloaded from the Gene Expression Omnibus (GEO) expression profile database and the intersected differentially expressed genes (DEGs) was calculated. We conducted the DEGs with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Distribution of immune cell infiltration was calculated by CIBERSORT. A hub gene marker was identified by intersecting the rejection-related genes from WGCNA and a selected KEGG pathway-T cell receptor signaling pathway (hsa04660), and building a protein-protein interaction network using the STRING database and Cytoscape software. We performed flow-cytometry analysis to validate the hub gene.

Results

A total of 1450 integrated DEGs were obtained from five datasets (GSE1563, GSE174020, GSE98320, GSE36059, GSE25902). The GO, KEGG and immune infiltration analysis results showed that AR was mainly associated with T cell activation and various T-cell related pathways. Other immune cells, such as B cells, Macrophage and Dendritic cells were also associated with the progress. After utilizing the WGCNA and PPI network, PDCD1 was identified as the hub gene. The flow-cytometry analysis demonstrated that both in CD4⁺ and CD8⁺ T cells, PD1⁺CD57^-, an exhausted T cell phenotype, were downregulated in the acute rejection whole blood samples.

Conclusions

Our study illustrated that PDCD1 may be a candidate diagnostic biomarker for acute kidney transplant rejection via integrative bioinformatic analysis.

Thrombalexin: Use of a Cytotopic Anticoagulant to Reduce Thrombotic Microangiopathy in a Highly Sensitized Model of Kidney Transplantation

Early activation of coagulation is an important factor in the initiation of innate immunity, as characterized by thrombotic microangiopathy (TMA). In transplantation, systemic anticoagulation is difficult due to bleeding. A novel "cytotopic" agent, thrombalexin (TLN), combines a cell-membrane-bound (myristoyl tail) anti-thrombin (hirudin-like peptide [HLL]), which can be perfused directly to the donor organ or cells. Thromboelastography was used to measure time to clot formation (r-time) in both rhesus and human blood, comparing TLN versus HLL (without cytotopic tail) versus negative control. Both TLN- and HLL-treated rhesus or human whole blood result in significantly prolonged r-time compared to kaolin controls. Only TLN-treated human endothelial cells and neonatal porcine islets prolonged time to clot formation. Detection of membrane-bound TLN was confirmed by immunohistochemistry and fluorescence activated cell sorter. In vivo, perfusion of a nonhuman primate kidney TLN-supplemented preservation solution in a sensitized model of transplantation demonstrated no evidence of TLN systemically. Histologically, TLN was shown to be present up to 4 days after transplantation. There was no platelet deposition, and TMA severity, as well as microvascular injury scores (glomerulitis + peritubular capillaritis), were less in the TLN-treated animals. Despite promising evidence of localized efficacy, no survival benefit was demonstrated.