Open AccessRenal Fibrosis mRNA Classifier: Validation in Experimental Lithium-Induced Interstitial Fibrosis in the Rat Kidney
Author(s) -
Hanspeter Marti,
Aaron Jeffs,
Andreas Scherer,
John P. Leader,
Catherine Leader,
Jennifer J. Bedford,
Robert Walker
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0168240
Subject(s) - renal cortex , fibrosis , medulla , biology , gene expression , endocrinology , medicine , kidney , pathology , gene , biochemistry
Accurate diagnosis of fibrosis is of paramount clinical importance. A human fibrosis classifier based on metzincins and related genes (MARGS) was described previously. In this investigation, expression changes of MARGS genes were explored and evaluated to examine whether the MARGS-based algorithm has any diagnostic value in a rat model of lithium nephropathy. Male Wistar rats (n = 12) were divided into 2 groups (n = 6). One group was given a diet containing lithium (40 mmol/kg food for 7 days, followed by 60mmol/kg food for the rest of the experimental period), while a control group (n = 6) was fed a normal diet. After six months, animals were sacrificed and the renal cortex and medulla of both kidneys removed for analysis. Gene expression changes were analysed using 24 GeneChip ® Affymetrix Rat Exon 1.0 ST arrays. Statistically relevant genes (p-value<0.05, fold change>1.5, t-test) were further examined. Matrix metalloproteinase-2 (MMP2), CD44, and nephroblastoma overexpressed gene (NOV) were overexpressed in the medulla and cortex of lithium-fed rats compared to the control group. TGFβ2 was overrepresented in the cortex of lithium-fed animals 1.5-fold, and 1.3-fold in the medulla of the same animals. In Gene Set Enrichment Analysis (GSEA), both the medulla and cortex of lithium-fed animals showed an enrichment of the MARGS, TGFβ network, and extracellular matrix (ECM) gene sets, while the cortex expression signature was enriched in additional fibrosis-related-genes and the medulla was also enriched in immune response pathways. Importantly, the MARGS-based fibrosis classifier was able to classify all samples correctly. Immunohistochemistry and qPCR confirmed the up-regulation of NOV, CD44, and TGFβ2. The MARGS classifier represents a cross-organ and cross-species classifier of fibrotic conditions and may help to design a test to diagnose and to monitor fibrosis. The results also provide evidence for a common pathway in the pathogenesis of fibrosis.