Prospective observational study to validate a next-generation sequencing blood RNA signature to predict early kidney transplant rejection.

The objective of this study was to validate the performance of Tutivia, a peripheral blood gene expression signature, in predicting early acute rejection (AR) post-kidney transplant. Recipients of living or deceased donor kidney transplants were enrolled in a nonrandomized, prospective, global, and observational study (NCT04727788). The main outcome was validation of the area under the curve (AUC) of Tutivia vs serum creatinine at biopsy alone, or Tutivia + serum creatinine at biopsy. Of the 151 kidney transplant recipients, the mean cohort age was 53 years old, and 64% were male. There were 71% (107/151) surveillance/protocol biopsies and 29% (44/151) for-cause biopsies, with a 31% (47/151) overall rejection rate. Tutivia (AUC 0.69 [95% CI: 0.59-0.77]) and AUC of Tutivia + creatinine at biopsy (0.68 [95% CI: 0.59-0.77]) were greater than the AUC of creatinine at biopsy alone (0.51.4 [95% CI: 0.43-0.60]). Applying a model cut-off of 50 (scale 0-100) generated a high- and low-risk category for AR with a negative predictive value of 0.79 (95% CI: 0.71-0.86), a positive predictive value of 0.60 (95% CI: 0.45-0.74), and an odds ratio of 5.74 (95% CI: 2.63-12.54). Tutivia represents a validated noninvasive approach for clinicians to accurately predict early AR, beyond the current standard of care.

The spatially resolved transcriptome signatures of glomeruli in chronic kidney disease.

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.