Novel biomarkers in antibody mediated rejection of kidney transplants
File(s)
Author(s)
Beadle, Jack
Type
Thesis
Abstract
Antibody-mediated rejection (AMR) is the leading cause of long-term kidney allograft dysfunction and loss. Current diagnosis relies on the Banff Classification, which requires characteristic histopathological features and evidence of antibody–endothelial interaction to diagnose AMR. However, biopsies that have incomplete features of AMR are associated with worse graft outcomes than biopsies with normal histology, highlighting limitations of conventional diagnostics.
This study evaluated whether molecular diagnostics using NanoString gene expression profiling with the Banff–Human Organ Transplant (B-HOT) panel could enable earlier and more precise detection of AMR. Our objectives were to identify AMR-associated gene expression signatures; apply these signatures to biopsies with incomplete AMR features; assess molecular profiles in biopsies obtained at the time of donor-specific antibody (DSA) detection; and examine gene expression patterns in biopsies with microvascular inflammation (MVI) in the presence or absence of DSA and in the context of missing inhibitory self-signals (“missing-self”).
We performed an integrated molecular, histological, and serological analysis of kidney transplant biopsies. A 9-gene molecular score was identified that predicted AMR and was associated with increased risk of allograft loss in biopsies with incomplete AMR features. In a separate cohort with MVI, 50% of biopsies lacked detectable DSA, yet their histological and molecular profiles were indistinguishable from DSA-positive cases. Although DSA-negative biopsies more frequently demonstrated missing-self, gene expression patterns were similar, suggesting convergence on a common inflammatory pathway. At the time of DSA detection, only biopsies with histological rejection showed molecular signatures of rejection; however, “normal” biopsies from DSA-positive recipients exhibited distinct molecular profiles compared with DSA-negative controls, consistent with possible accommodation.
In conclusion, integrating molecular diagnostics with histological assessment enhances AMR detection, and may inform early intervention. Future research will focus on multicentre prospective validation and clinical implementation.
This study evaluated whether molecular diagnostics using NanoString gene expression profiling with the Banff–Human Organ Transplant (B-HOT) panel could enable earlier and more precise detection of AMR. Our objectives were to identify AMR-associated gene expression signatures; apply these signatures to biopsies with incomplete AMR features; assess molecular profiles in biopsies obtained at the time of donor-specific antibody (DSA) detection; and examine gene expression patterns in biopsies with microvascular inflammation (MVI) in the presence or absence of DSA and in the context of missing inhibitory self-signals (“missing-self”).
We performed an integrated molecular, histological, and serological analysis of kidney transplant biopsies. A 9-gene molecular score was identified that predicted AMR and was associated with increased risk of allograft loss in biopsies with incomplete AMR features. In a separate cohort with MVI, 50% of biopsies lacked detectable DSA, yet their histological and molecular profiles were indistinguishable from DSA-positive cases. Although DSA-negative biopsies more frequently demonstrated missing-self, gene expression patterns were similar, suggesting convergence on a common inflammatory pathway. At the time of DSA detection, only biopsies with histological rejection showed molecular signatures of rejection; however, “normal” biopsies from DSA-positive recipients exhibited distinct molecular profiles compared with DSA-negative controls, consistent with possible accommodation.
In conclusion, integrating molecular diagnostics with histological assessment enhances AMR detection, and may inform early intervention. Future research will focus on multicentre prospective validation and clinical implementation.
Version
Open Access
Date Issued
2025-03-18
Date Awarded
01/02/2026
Advisor
Roufosse, Candice
Publisher Department
Department of Immunology and Inflammation
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)