Citations

Background: Although donor and recipient characteristics are used to estimate graft failure risk, they remain limited in predicting early acute rejection. We developed and validated a next-generation sequencing (NGS) assay targeting the pre-transplant immunologic profile to predict early acute rejection following kidney transplantation. Methods: This prospective, international study enrolled 321 kidney transplant participants across 13 sites, forming discovery and validation cohorts. Peripheral blood was collected prior to transplant and at 1, 3, 6, 12, and 24 months post-transplant, with protocol biopsies performed at 3 and 12 months, as well as any indication biopsies. Biopsies were assessed by a blinded central pathologist according to the 2019 Banff criteria. The pre-transplant risk assessment (PTRA™) test to evaluate RNA expression of a 29-gene signature algorithm designed to predict early acute rejection risk was clinically validated utilizing 122 deceased donor kidney transplant recipients. Results: PTRA classified 31 of 122 participants (25%) as high-risk and 91 (75%) as low-risk. There were 9 early acute rejection events in the first 60 days post-transplant: 6/31 (19%) in the high-risk group and 3/91 (3%) in the low-risk group. PTRA discrimination for early acute rejection at 60 days post-transplant yielded an AUC of 0.78 (95% confidence interval [CI]: 64.4 to 91.5), p<0.001. A cut-off of ≤45 was defined as low-risk and >45 as high-risk for early acute rejection within 60 days post-transplant. Sensitivity 0.67 (95% CI: 0.36 to 0.97), specificity 0.78 (95% CI: 0.70 to 0.86), positive predictive value 0.19 (95% CI: 0.05 to 0.33), and negative predictive value 0.97 (95% CI: 0.93 to 1.00). The odds ratio comparing patients identified as high- vs low-risk by PTRA was 7.04 (95% CI: 1.64 to 30.2), p=0.009. Conclusions: This study validates the ability of PTRA to stratify kidney transplant recipients as high- or low-risk for early acute rejection using a pre-transplant transcriptomic profile, with implications for graft health and personalized treatment management.

Here, we used digital spatial profiling (DSP) to describe the glomerular transcriptomic signatures that may characterize the complex molecular mechanisms underlying progressive kidney disease in Alport syndrome, focal segmental glomerulosclerosis, and membranous nephropathy. Our results revealed significant transcriptional heterogeneity among diseased glomeruli, and this analysis showed that histologically similar glomeruli manifested different transcriptional profiles. Using glomerular pathology scores to establish an axis of progression, we identified molecular pathways with progressively decreased expression in response to increasing pathology scores, including signal recognition particle–dependent cotranslational protein targeting to membrane and selenocysteine synthesis pathways. We also identified a distinct signature of upregulated and downregulated genes common to all the diseases investigated when compared with nondiseased tissue from nephrectomies. These analyses using DSP at the single-glomerulus level could help to increase insight into the pathophysiology of kidney disease and possibly the identification of biomarkers of disease progression in glomerulopathies.

Transplant pathology plays a critical role in ensuring that transplanted organs function properly and the immune systems of the recipients do not reject them. To improve outcomes for transplant recipients, accurate diagnosis and timely treatment are essential. Recent advances in artificial intelligence (AI)-empowered digital pathology could help monitor allograft rejection and weaning of immunosuppressive drugs. To explore the role of AI in transplant pathology, we conducted a systematic search of electronic databases from January 2010 to April 2023. The PRISMA checklist was used as a guide for screening article titles, abstracts, and full texts, and we selected articles that met our inclusion criteria. Through this search, we identified 68 articles from multiple databases. After careful screening, only 14 articles were included based on title and abstract. Our review focuses on the AI approaches applied to four transplant organs: heart, lungs, liver, and kidneys. Specifically, we found that several deep learning-based AI models have been developed to analyze digital pathology slides of biopsy specimens from transplant organs. The use of AI models could improve clinicians’ decision-making capabilities and reduce diagnostic variability. In conclusion, our review highlights the advancements and limitations of AI in transplant pathology. We believe that these AI technologies have the potential to significantly improve transplant outcomes and pave the way for future advancements in this field.

Hydralazine is a vasodilator used for the management of hypertension, heart failure, and hypertensive emergencies in pregnancy. It has been implicated in the causation of drug-induced lupus erythematosus (DLE) and rarely with ANCA-associated vasculitis (AAV), which may present as a pulmonary-renal syndrome and be rapidly fatal. Herein, we describe a case of hydralazine-associated AAV presenting as acute kidney injury with the use of early bronchoalveolar lavage (BAL) with serial aliquots to aid with diagnosis. Our case highlights how, in the correct clinical setting, BAL can act as a rapid diagnostic test to help guide quicker treatment to allow for better patient outcomes.

Despite recent progress in the identification of mediators of podocyte injury, mechanisms underlying podocyte loss remain poorly understood, and cell-specific therapy is lacking. We previously reported that kidney and brain expressed protein (KIBRA), encoded by WWC1 , promotes podocyte injury in vitro through activation of the Hippo signaling pathway. KIBRA expression is increased in the glomeruli of patients with focal segmental glomerulosclerosis, and KIBRA depletion in vivo is protective against acute podocyte injury. Here, we tested the consequences of transgenic podocyte-specific WWC1 expression in immortalized human podocytes and in mice, and we explored the association between glomerular WWC1 expression and glomerular disease progression. We found that KIBRA overexpression in immortalized human podocytes promoted cytoplasmic localization of Yes-associated protein (YAP), induced actin cytoskeletal reorganization, and altered focal adhesion expression and morphology. WWC1 -transgenic (KIBRA-overexpressing) mice were more susceptible to acute and chronic glomerular injury, with evidence of YAP inhibition in vivo. Of clinical relevance, glomerular WWC1 expression negatively correlated with renal survival among patients with primary glomerular diseases. These findings highlight the importance of KIBRA/YAP signaling to the regulation of podocyte structural integrity and identify KIBRA-mediated injury as a potential target for podocyte-specific therapy in glomerular disease.