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Benchmarking urinary cell transcriptomes for noninvasive differentiation of BK polyomavirus–associated nephropathy from T cell–mediated rejection
Franco B. Mueller, Carol Li, Darshana M. Dadhania, Surya V. Seshan, Thalia Salinas, Vijay K. Sharma, Jenny Z. Xiang, Hans H. Hirsch, Thangamani Muthukumar, Manikkam Suthanthiran
Franco B. Mueller, Carol Li, Darshana M. Dadhania, Surya V. Seshan, Thalia Salinas, Vijay K. Sharma, Jenny Z. Xiang, Hans H. Hirsch, Thangamani Muthukumar, Manikkam Suthanthiran
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Research Article Immunology Nephrology

Benchmarking urinary cell transcriptomes for noninvasive differentiation of BK polyomavirus–associated nephropathy from T cell–mediated rejection

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Abstract

BK polyomavirus–associated nephropathy (BKVN) adversely impacts kidney allograft survival and often mimics acute T cell–mediated rejection (TCMR), confounding diagnosis and management. To address this conundrum, we performed unbiased RNA sequencing of urinary cells matched to biopsies classified as BKVN with intragraft inflammation (BKVN-P), BKVN without inflammation (BKVN-N), TCMR, or no rejection (NR). BKVN-N displayed dominant host DNA replication, cell cycle, and repair programs, while BKVN-P samples exhibited expansive innate immune activation, antigen presentation, chemokine upregulation, and epithelial injury. Both BKVN subtypes shared signatures of T cell exhaustion and mature and tolerogenic dendritic cell activation but differed in immune orientation — Th1 predominance in BKVN-N versus Treg and CD8 enrichment in BKVN-P. Compared with TCMR samples, BKVN-P lacked robust TCR/CD28 signaling and was enriched for viral and innate modules; BKVN-N lacked alloimmune activation. B cell exhaustion characterized BKVN-N, while BKVN-P displayed robust B cell activation with metabolic downregulation. A ratiometric urinary cell biomarker, CXCL10 mRNA/CD3E mRNA, distinguished both BKVN subtypes from TCMR with diagnostic accuracy, replicated by quantitative reverse transcription PCR for clinical translation, and confirmed in an independent cohort. These findings demonstrate the utility of urinary cell transcriptomics for resolving viral injury from alloimmunity, enabling precision diagnostics and targeted immunomodulation in kidney transplantation.

Authors

Franco B. Mueller, Carol Li, Darshana M. Dadhania, Surya V. Seshan, Thalia Salinas, Vijay K. Sharma, Jenny Z. Xiang, Hans H. Hirsch, Thangamani Muthukumar, Manikkam Suthanthiran

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Figure 17

Transcriptomic signature discriminating TCMR from BKVN.

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Transcriptomic signature discriminating TCMR from BKVN.
(A) Twenty-one u...
(A) Twenty-one urinary cell transcriptomes matched to 21 TCMR biopsies were compared with 11 urinary cell transcriptomes matched to 10 BKVN biopsies (4 BKVN-N and 6 BKVN-P). The volcano plots show DEGs (log2 fold change vs. log10 P). Supplemental Table 39 lists 104 DEGs. (B) glmnet cross-validation plots display mean-squared and misclassification error across λ values, with vertical lines indicating the optimal penalties (minimum error and more parsimonious 1-SE solution). (C) Elastic net coefficient plot for each of the 18 predictor genes shows coefficient direction and magnitude in the model that perfectly separates TCMR from BKVN (AUROC = 1.0). Supplemental Table 40 lists the 18 genes and their elastic net coefficients, random forest validation metrics, and TCMR versus BKVN fold changes and adjusted P values. (D) ROC curve for a bootstrapped random forest classifier trained on the selected genes (N = 1,000 bootstraps; caret with optimal mtry = 2) shows high performance accuracy of 0.973 (95% CI, 0.970–0.975) and AUROC of 0.995.

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