Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-18827
Ju, W; Eichinger, F; Bitzer, M; Oh, J; McWeeney, S; Berthier, C C; Shedden, K; Cohen, C D (2009). Renal gene and protein expression signatures for prediction of kidney disease progression. American Journal of Pathology, 174(6):2073-2085.
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Although chronic kidney disease (CKD) is common, only a fraction of CKD patients progress to end-stage renal disease. Molecular predictors to stratify CKD populations according to their risk of progression remain undiscovered. Here we applied transcriptional profiling of kidneys from transforming growth factor-beta1 transgenic (Tg) mice, characterized by heterogeneity of kidney disease progression, to identify 43 genes that discriminate kidneys by severity of glomerular apoptosis before the onset of tubulointerstitial fibrosis in 2-week-old animals. Among the genes examined, 19 showed significant correlation between mRNA expression in uninephrectomized left kidneys at 2 weeks of age and renal disease severity in right kidneys of Tg mice at 4 weeks of age. Gene expression profiles of human orthologs of the 43 genes in kidney biopsies were highly significantly related (R(2) = 0.53; P < 0.001) to the estimated glomerular filtration rates in patients with CKD stages I to V, and discriminated groups of CKD stages I/II and III/IV/V with positive and negative predictive values of 0.8 and 0.83, respectively. Protein expression patterns for selected genes were successfully validated by immunohistochemistry in kidneys of Tg mice and kidney biopsies of patients with IgA nephropathy and CKD stages I to V, respectively. In conclusion, we developed novel mRNA and protein expression signatures that predict progressive renal fibrosis in mice and may be useful molecular predictors of CKD progression in humans.
|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||04 Faculty of Medicine > University Hospital Zurich > Clinic for Nephrology|
04 Faculty of Medicine > Institute of Physiology
07 Faculty of Science > Institute of Physiology
|DDC:||570 Life sciences; biology|
610 Medicine & health
|Deposited On:||03 Jun 2009 16:17|
|Last Modified:||27 Nov 2013 17:31|
|Citations:||Web of Science®. Times Cited: 30|
Scopus®. Citation Count: 30
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