Identification of mechanistic CKD biomarkers in a rat SNx kidney fibrosis model by transcriptomics and proteomics detectable in biofluids

The rat sub-total nephrectomy (SNx) is a functional model of general chronic kidney disease (CKD) where the main pathological driver is glomerular hypertension representative of several subtypes of CKD. Comprehensive transcriptomics and proteomics analyses on the SNx rats were performed to identify biomarkers in plasma or urine that correlate with kidney disease and functional kidney loss. Kidneys were subjected to collagen I and III staining for fibrosis scoring, SWATH-MS proteomics and bulk RNA-sequencing transcriptomics, with SWATH-MS also performed on plasma and urine. Differential expression analysis demonstrated significant dysregulation of genes and proteins involved in fibrosis, metabolism, and immune response in the SNx rats compared to controls. Gene ontology analysis of the intersecting genes and proteins from both studies demonstrated common biology between animal cohorts that reached the predefined kidney disease thresholds (serum creatinine > two-fold or proteinuria > three-fold increase over sham-operated). Thirteen significantly differential molecules were detected with consistent directional changes in both omics datasets. These molecules were detected independently in kidney (both RNA and protein) and urine (protein only), but not in plasma. Bioinformatics analysis enabled the identification of mechanistic CKD biomarkers including lumican and collagen alpha-1(III) chain, whose co-expression has previously been both implicated in fibrosis and detected in urine in CKD patients.

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Journal
Scientific Reports
Published
2025-04-02
DOI
https://doi.org/10.1038/s41598-025-93894-6
Citations
1
Primary Topic
Chronic Kidney Disease and Diabetes
Type
article
Field-Weighted Citation Impact
1.43
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article

Identification of mechanistic CKD biomarkers in a rat SNx kidney fibrosis model by transcriptomics and proteomics detectable in biofluids

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1 citations
Scientific Reports
Chronic Kidney Disease and Diabetes
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article

Identification of mechanistic CKD biomarkers in a rat SNx kidney fibrosis model by transcriptomics and proteomics detectable in biofluids

Elisabetta A. M. Verderio, Elisa Tonoli, Breda M. Twomey, Margarida Sancho, Andrew Skelton, David J. Boocock, John Atkinson, Timothy S. Johnson, Karin Barnouin, Clare Coveney, Linghong Huang, James Shephard
article en
1 citations

Abstract

The rat sub-total nephrectomy (SNx) is a functional model of general chronic kidney disease (CKD) where the main pathological driver is glomerular hypertension representative of several subtypes of CKD. Comprehensive transcriptomics and proteomics analyses on the SNx rats were performed to identify biomarkers in plasma or urine that correlate with kidney disease and functional kidney loss. Kidneys were subjected to collagen I and III staining for fibrosis scoring, SWATH-MS proteomics and bulk RNA-sequencing transcriptomics, with SWATH-MS also performed on plasma and urine. Differential expression analysis demonstrated significant dysregulation of genes and proteins involved in fibrosis, metabolism, and immune response in the SNx rats compared to controls. Gene ontology analysis of the intersecting genes and proteins from both studies demonstrated common biology between animal cohorts that reached the predefined kidney disease thresholds (serum creatinine > two-fold or proteinuria > three-fold increase over sham-operated). Thirteen significantly differential molecules were detected with consistent directional changes in both omics datasets. These molecules were detected independently in kidney (both RNA and protein) and urine (protein only), but not in plasma. Bioinformatics analysis enabled the identification of mechanistic CKD biomarkers including lumican and collagen alpha-1(III) chain, whose co-expression has previously been both implicated in fibrosis and detected in urine in CKD patients.

Scientific ReportsVol. 15(1)
TGS (United Kingdom) (GB), Mission Therapeutics (United Kingdom) (GB), Gilead Sciences (United Kingdom) (GB), MSD K.K. (Japan) (JP), UCB Pharma (United Kingdom) (GB), Nottingham Trent University (GB), University of Sheffield (GB), University of Bologna (IT)
Good health and well-being
Openalex Percentile: Top 21%
Chronic Kidney Disease and Diabetes
1.43
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