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Preparing your E-Poster
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E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
Better kidney graft health is a major objective for both patients and clinicians. However, improvements in long term graft function have stagnated. Long term predictors of graft function and graft loss include classical risk factors such as HLA match. Genomic and transcriptomic factors that are derived from both the donor and recipient have been shown to be predictors of rejection and graft function.
The aim of this study was to identify putative transcriptomic factors associated with kidney allograft loss from renal allograft biopsy samples in a mixed ethnicity cohort based in Australia.
The Australian Genomics of Chronic Allograft Dysfunction study is a prospective study at Westmead Hospital, with clinical data, biobanked blood, and renal allograft biopsies, collected at 0/1/3/12 months post-transplant. RNA extracted from renal biopsies underwent Illumina bulk RNA sequencing. Patients were followed since study inception in 2012 for death censored graft loss (DCGL). Self-reported ethnicity was recorded alongside inferred genetic ancestry using SNVstory. Differential gene expression analysis was conducted in R using the limma package; gene ontology was performed using EnrichR packages and QIAGEN Ingenuity Pathway Analysis. Significant genes were selected with false discovery rate of 0.05 and a gene expression fold-change of 1.5 (LFC 0.58).
184 patients were included, of which 11 experienced DCGL. 62 (33.6%) were female. 47 (25.5%) self-identified as non-European ethnicity, which was concordant with measured genetic ancestry. Biopsies were selected at latest sample time – 124 at 12 months, 59 at 3 months, and 1 at 1 month post-transplant. Renal failure aetiology included glomerulonephritis (n=60), diabetes (n=63), polycystic kidney disease (n=22), and hypertension (n=14).
Differential gene expression after testing relative to a threshold analysis identified 282 genes significantly associated with patients with DCGL as compared to a functioning graft during follow-up (151 upregulated genes and 131 downregulated genes).
Gene Ontology enrichment analysis (Figures 2 and 3) and Ingenuity Pathway Analysis (Figure 4) revealed upregulation of inflammatory response pathways (e.g. IL6, C3) and downregulation of cellular transport processes (e.g. SLC16A3). Canonical pathways confirmed with IPA also demonstrated innate immunity pathways activation including neutrophil degranulation, phagosome formation, and complement system activation as crucial components of DCGL.
Figure 1: Volcano plot of differentially expressed genes, red = significantly upregulated, green = significantly downregulated.
Figure 2: Upregulated gene Biological Processes for DCGL (enrichR analysis)
Figure 3: Downregulated gene Biological Processes for DCGL (enrichR analysis)
Figure 4: Ingenuity Pathway Analysis
Renal allograft DCGL was significantly associated with activation of a number of inflammatory pathways and innate immune system activation. We confirmed a number of genes associated with rejection (e.g. FPR1, AQP2) from Banff Human Organ Transplant panel and have identified novel transcriptomic targets relevant to long term graft loss in a multiethnic Australian cohort. Our results will inform future mechanistic studies into drivers of graft loss and guide personalised genomic risk prediction models and future therapeutic pathways.
