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The spatially resolved transcriptome signatures of glomeruli in chronic kidney disease
Geremy Clair, … , Sargis Sedrakyan, Laura Perin
Geremy Clair, … , Sargis Sedrakyan, Laura Perin
Published March 22, 2024
Citation Information: JCI Insight. 2024;9(6):e165515. https://doi.org/10.1172/jci.insight.165515.
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Research Article Nephrology

The spatially resolved transcriptome signatures of glomeruli in chronic kidney disease

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Abstract

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.

Authors

Geremy Clair, Hasmik Soloyan, Paolo Cravedi, Andrea Angeletti, Fadi Salem, Laith Al-Rabadi, Roger E. De Filippo, Stefano Da Sacco, Kevin V. Lemley, Sargis Sedrakyan, Laura Perin

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Figure 6

Gene expression signature in AS glomeruli from young patients.

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Gene expression signature in AS glomeruli from young patients.
(A) Venn ...
(A) Venn diagrams of TMM-normalized expression of genes detected above LOQ in biopsies from young patients with AS (sample no. 1, n = 8 ROIs; sample no. 2, n = 7 ROIs), showing the distribution of the number of genes commonly expressed in all glomeruli (AS no. 1, 676 genes; AS no. 2, 588 genes). The black lines point to a list of the most highly enriched pathways (GO, KEGG, REACTOME) for the commonly expressed genes among all glomeruli in AS no. 1 and 2. (B) Unsupervised principal component analysis (PCA) based on label-free quantification of the transcripts expressed in young AS (no. 1 and 2, gray-green circles) and young nondiseased glomerular ROIs (no. 8, blue circles), based on PC1 and PC2 constructed to capture the most variation in the samples. Percentage of total variance is indicated after each principal component. Significantly enriched GO terms and KEGG and REACTOME pathways (EASE-modified Fisher’s exact P < 0.05) for the top 10% of transcripts contributing the most to each principal component are shown next to the plot. (C) Dendrogram showing hierarchical clustering and transcriptional link between glomeruli from AS no. 1 and 2 and nondiseased glomeruli no. 8. Y, young. (D) Heatmap depicting the transcripts significantly modulated between glomeruli from AS (no.1 and 2) and nondiseased glomeruli no. 8 (Student’s t test and binomial GLM test, adjusted P < 0.05). Transcripts less than LOQ in value are shown in white. (E) A select list of GO terms and KEGG and REACTOME pathways significantly enriched (EASE-modified Fisher exact, P < 0.05) for the upregulated and downregulated genes in AS (no. 1 and 2) versus nondiseased (no. 8) shown in D.

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