Data-Driven Kidney Transplant Phenotyping as a Histology-Independent Framework for Biomarker Discovery.

BACKGROUND: In transplant medicine, clinical decision making largely relies on histology of biopsy specimens. However, histology suffers from low specificity, sensitivity, and reproducibility, leading to suboptimal stratification of patients. We developed a histology-independent immune framework of kidney graft homeostasis and rejection. METHODS: We applied tailored RNA deconvolution for leukocyte enumeration and coregulated gene network analysis to published bulk human kidney transplant RNA transcriptomes as input for unsupervised, high-dimensional phenotype clustering. We used framework-based graft survival analysis to identify a biomarker that was subsequently characterized in independent transplant biopsy specimens. RESULTS: We found seven immune phenotypes that confirm known rejection types and uncovered novel signatures. The molecular phenotypes allow for improved graft survival analysis compared with histology, and identify a high-risk group in nonrejecting transplants. Two fibrosis-related phenotypes with distinct immune features emerged with reduced graft survival. We identified lysyl oxidase-like 2 (LOXL2)-expressing peritubular CD68+ macrophages as a framework-derived biomarker of impaired allograft function. These cells precede graft fibrosis, as demonstrated in longitudinal biopsy specimens, and may be clinically useful as a biomarker for early fibrogenesis. CONCLUSIONS: This study provides a comprehensive, data-driven atlas of human kidney transplant phenotypes and demonstrates its utility to identify novel clinical biomarkers.

Quantification of Hv1-induced proton translocation by a lipid-coupled Oregon Green 488-based assay.

Passive proton translocation across membranes through proton channels is generally measured with assays that allow a qualitative detection of the H+-transfer. However, if a quantitative and time-resolved analysis is required, new methods have to be developed. Here, we report on the quantification of pH changes induced by the voltage-dependent proton channel Hv1 using the commercially available pH-sensitive fluorophore Oregon Green 488-DHPE (OG488-DHPE). We successfully expressed and isolated Hv1 from Escherichia coli and reconstituted the protein in large unilamellar vesicles. Reconstitution was verified by surface enhanced infrared absorption (SEIRA) spectroscopy and proton activity was measured by a standard 9-amino-6-chloro-2-methoxyacridine assay. The quantitative OG488-DHPE assay demonstrated that the proton translocation rate of reconstituted Hv1 is much smaller than those reported in cellular systems. The OG488-DHPE assay further enabled us to quantify the KD-value of the Hv1-inhibitor 2-guanidinobenzimidazole, which matches well with that found in cellular experiments. Our results clearly demonstrate the applicability of the developed in vitro assay to measure proton translocation in a quantitative fashion; the assay allows to screen for new inhibitors and to determine their characteristic parameters. Graphical abstract ᅟ.

Plasma protein signatures reflect systemic immunity and allograft function in kidney transplantation.

Kidney transplantation causes large perturbations of the immune system. While many studies focus on the allograft, insights into systemic effects are largely missing. Here, we analyzed the systemic immune response in 3 cohorts of kidney transplanted patients. Using serum proteomics, laboratory values, mass cytometry, histological and clinical parameters, inter-patient heterogeneity was leveraged for multi-omic co-variation analysis. We identified circulating immune modules (CIM) that describe extra-renal signatures of co-regulated plasma proteins. CIM are present in nontransplanted controls, in transplant conditions and during rejection. They are enriched in pathways linked to kidney function, extracellular matrix, signaling, and cellular activation. A complex leukocyte response in the blood during allograft quiescence and rejection is associated with CIM activity and CIM-specific cytokines. CIM activity correlates with kidney function including a 2-month prediction. Together, the data suggest a systemic and multi-layered response of transplant immunity that might be insightful for understanding allograft dysfunction and developing translational biomarkers.