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487 Digital Spatial Profiling of Allograft Loss in Kidney Biopsies with Chronic Allograft Dysfunction

Published online by Cambridge University Press:  03 April 2024

Casey R. Dorr
Affiliation:
Hennepin Healthcare Research Institute, Minneapolis, MN University of Minnesota, Minneapolis, MN
Weihua Guan W
Affiliation:
University of Minnesota, Minneapolis, MN
Guillaume Onyeaghala G
Affiliation:
Hennepin Healthcare Research Institute, Minneapolis, MN University of Minnesota, Minneapolis, MN
William S Oetting
Affiliation:
Hennepin Healthcare, Minneapolis, MN
Roslyn B Mannon
Affiliation:
University of Nebraska Medical Center, Omaha, NE
Gaurav Agarwal
Affiliation:
Univeristy of Alabama, Birmingham, AL
Jonathan Maltzman
Affiliation:
Stanford University, Palo Alto, CA
Arthur Matas
Affiliation:
University of Minnesota, Minneapolis, MN
Pamala A Jacobson
Affiliation:
University of Minnesota, Minneapolis, MN
Ajay K Israni
Affiliation:
Hennepin Healthcare Research Institute, Minneapolis, MN University of Minnesota, Minneapolis, MN
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Abstract

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OBJECTIVES/GOALS: Assess molecular and cellular mechanisms of allograft loss in kidney biopsies using digital spatial profiling and clinical outcomes data. METHODS/STUDY POPULATION: Patients with chronic allograft dysfunction (CGD), enrolled in the Deterioration of Kidney Allograft Function (DeKAF) study, with or without eventual allograft loss, were included. CGD was defined as a >25% increase in creatinine over 3 months relative to a baseline. Kidney biopsy tissue was assessed by Nanostring GeoMX digital spatial profiling (DSP) after staining with anti-pan-cytokeratin, anti-CD45, anti-CD68, Syto-13, to identify specific cell populations, and Nanostring’s Whole Transcriptome Atlas (WTA), to quantify the distribution of transcripts across the biopsy. Up to 14 regions of interest (ROIs) were selected, with or without glomerulus. CIBERSORT was used to perform cell deconvolution. Clinical and outcomes data were from the DeKAF study and United States Renal Data System. RESULTS/ANTICIPATED RESULTS: Macrophage (M1) cell population abundance was significantly different in ROIs with glomerulus between graft loss and no graft loss. Principle component analysis of differentially expressed genes resulted in transcriptomes in ROIs that cluster together by clinical outcome of graft loss or no graft loss. There were 203 DEGs in ROIs with glomerulus that were different by graft loss or no graft loss. By pathway analysis, these 203 DEGS were enriched in the T-cell activation, integrin signaling and inflammation pathways. DISCUSSION/SIGNIFICANCE: DSP of kidney allograft biopsies allows for the identification and quantification of specific cell types, such as macrophages and molecular transcripts as potential drug targets. This data can be used to understand mechanisms of kidney allograft loss and may lead to improved immune suppression in kidney transplant recipients.

Type
Precision Medicine/Health
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2024. The Association for Clinical and Translational Science