#3979 DIGITAL SPATIAL PROFILING CAN BE USED TO STUDY GLOMERULAR ENDOTHELIAL CELLS IN IGA NEPHROPATHY
Authors: Selvaskandan Haresh , Boys Charlotte , Pawluczyk Izabella , Barratt Jonathan 
Published: June 2023

Abstract

Background and Aims
IgA nephropathy (IgAN) is the most common primary glomerular disease worldwide; approximately 30% of cases progress to kidney failure 10-20 years from diagnosis. Five histopathological kidney lesions independently predict a poor prognosis in IgAN (MEST-C score) [1]. Published case series highlight the ‘endocapillary hypercellularity’ (E1) lesion as potentially reversible with systemic immunosuppression, improving clinical outcomes [2]. Delineating differences in the transcriptomes of glomerular endothelial cells (GEnCs) associated with and without E1 (E0) may highlight avenues for safer therapeutic strategies, given the overt risks associated with systemic immunosuppression in IgAN. GEnC transcriptomes have never been profiled in diseased kidneys before. Here we used digital spatial profiling (DSP) to achieve this.

Method
DSP was performed on a Nanostring GeoMx platform. Single 5μm sections were collected from four formalin fixed paraffin embedded (FFPE) kidney biopsies with E1 and five with E0. Following deparaffinization and antigen retrieval, the tissue was incubated with a whole transcriptome atlas probe set. GEnCs were stained for CD31 (red) and macrophages (which associate with E1[3]) with CD68 (yellow) with conjugated antibodies. Glomeruli were selected as regions of interests (ROIs), and a custom JavaScript function was used to mask over GEnCs and macrophages (segmentation), which were selected as areas of illumination (AOIs) (Fig 1). Photocleaved nucleotide barcodes were sequenced using an Illumina sequencer. Single cell enrichment was assessed using the SpatialDecon algorithm, differential gene expression was explored using a linear mixed effects model, and pathway analysis was performed using Reactome.

Results
The custom written JavaScript function allowed good segmentation on GEnCs and macrophages (Fig 1). Single cell deconvolution performed using the human kidney cell atlas as a reference showed significant enrichment of GEnCs relative to neighbouring cell types (Fig 2). Exploration of differential gene expressions using a linear mixed effects model found an up-regulation of TRIM23, IL27RA, TMEM139, P14K2B and PSMD9, after P value adjustment, among GEnCs associated with macrophages in glomerular capillary loops compared to those in the absence of macrophages (Fig 3). Pathway analysis based on differential gene expression performed using Reactome revealed that the complement cascade and regulators of the complement cascade were enhanced in GEnCs associated with macrophages (Fig 4).

Conclusion
This pilot study found DSP on the GeoMx to be effective at enriching GEnC transcript signals from neighbouring cell types in FFPE tissue. This preliminary data also shows that GEnCs associated with macrophages may display a more inflammatory phenotype, which may be related to up-regulation in complement activity and may account for the progressive phenotype associated with E1 in IgAN. With several trials investigating complement system targeting therapeutics in IgAN, validation of these findings might highlight a cohort of patients with IgAN most likely to benefit from treatment.