Dataset Information

Glomerular proteomic profiling of kidney biopsies with hypertensive nephropathy reveals a signature of disease progression

ABSTRACT: Background and Objective: Hypertensive nephropathy (HN) requires a kidney biopsy as gold-standard for its diagnosis but histological findings are not entirely specific and lack specific prognostic markers. We aimed at defining prognostic candidate markers based on glomerular protein signatures. Method: We included adult patients (n=17) with an eGFR >30 ml/min/1.73m2 and proteinuria <3g/d from the Norwegian Kidney Biopsy Registry: stable patients (n=9) and subjects with HN progression (n=8) leading to end-stage renal disease (ESRD) within 20 years of follow-up. Glomerular cross-sections were microdissected from archival kidney biopsy sections and processed for protein extraction. Proteomic analyses were performed using Q-exactive HF mass spectrometer and relative glomerular protein abundance were compared between progressive vs non-progressive patients. Results: Amongst 1870 quality filtered proteins, we identified 58 proteins with an absolute fold change (FC)>1.5, p<0.05, including 17 proteins with absolute FC >2, indicative of HN progression (highest FC: Cadherin 16 and UDP-glucuronosyl-transferase 2B7). Hierarchical cluster and principal component analysis (PCA) with the 17 proteins showed clear separation of samples into HN progressors and non-progressors. Supervised classifier analysis (K nearest neighbour) identified a set of five proteins which classified 16/17 samples correctly. Applying Geneset Enrichment Analysis (GSEA), in general metabolic pathways were enriched in progressors, and structural cell pathways enriched in non-progressors. Pathway analysis identified Epithelial Adherens Junction Signaling as the most affected canonical pathway. The signature of HN progression is different from the respective signature of IgA progression. Conclusion: Glomerular proteomic profiling can be used to discriminate progressors from non-progressors in HN.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Kidney, Renal Glomerulus

SUBMITTER: Kenneth Finne

LAB HEAD: Hans Peter Marti

PROVIDER: PXD026709 | Pride | 2023-05-23

REPOSITORIES: Pride

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Glomerular proteomic profiling of kidney biopsies with hypertensive nephropathy reveals a signature of disease progression.

Mikkelsen Håvard H Vikse Bjørn E BE Eikrem Oystein O Scherer Andreas A Finne Kenneth K Osman Tarig T Marti Hans-Peter HP

Hypertension research : official journal of the Japanese Society of Hypertension 20221014 1

Hypertensive nephropathy (HN) requires a kidney biopsy as diagnostic gold-standard but histological findings are unspecific and specific prognostic markers are missing. We aimed at identifying candidate prognostic markers based on glomerular protein signatures. We studied adult patients (n = 17) with eGFR >30 ml/min/1.73m<sup>2</sup> and proteinuria <3 g/d from the Norwegian Kidney Biopsy Registry, including subjects non progressing (NP, n = 9), or progressing (P, n = 8) to end-stage renal disea ...[more]

PMID: 36229534

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Project description:Background: In a previous study of patients with assumed benign IgA nephropathy (IgAN), we have shown that 18.6% develop a progressive clinical course, which was not predicted by any known clinical nor histopathological parameters (Knoop 2017). We aim to differentiate between future progressors and non-progressors with assumed benign IgAN by using glomerular transcriptomics from diagnostic kidney biopsies and to investigate whether this can identify drugs to be used in those patients. Methods: We included adult progressors (n=15) and patients with clinical remission (non-progressors, n=21) from our previously reported IgAN cohort. Glomerular cross-sections were obtained through laser-capture microdissection from 10µm archival kidney biopsy sections for mRNA sequencing, using the SMARTer Stranded Total RNA-Seq kit – Pico Input Mammalian (Clontech Laboratories, California, USA). Key results were validated in external cohorts and on the protein level with immunohistochemistry in the discovery cohort and an internal validation cohort. We also compared our transcriptomic findings with an external genome-wide association study (GWAS) dataset (Kiryluk 2021). Results: For the statistical analyses, we studied 8 progressors and 9 non-progressors. Based on the 1,240 differentially expressed glomerular genes from the initial kidney biopsies, we were able to identify future IgAN progressors and non-progressors using a two-component classifier. The classifier predicted disease progression with 88% accuracy, 75% sensitivity and 100% specificity (AUC=0.875), more accurate than the recommended International IgAN Prediction Tool in this specific patient cohort. Among our differentially expressed genes, 10 were also found in the GWAS dataset (Kiryluk 2021). We identified 45 drug targets in the DrugBank database, including angiotensinogen, a target of sparsentan, currently investigated as therapy in IgAN (NCT03762850 and NCT04663204). The findings on upregulation of angiotensinogen, which was independent of blood pressure, were validated in an internal IgAN validation cohort. Interestingly, complement activation did not play a major role in our data. Our work suggests that LXR, FXR and macrophage activation pathways could be critically involved in the inhibition of the progression of low-risk ccRCC. Furthermore, a 10-component classifier could support an early identification of apparently low-risk ccRCC patients.

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