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(American Journal of Pathology. 2009;174:2073-2085.)
© 2009 American Society for Investigative Pathology
DOI: 10.2353/ajpath.2009.080888

Renal Gene and Protein Expression Signatures for Prediction of Kidney Disease Progression

Wenjun Ju^*, Felix Eichinger, Markus Bitzer, Jun Oh, Shannon McWeeney^¶, Celine C. Berthier, Kerby Shedden^||, Clemens D. Cohen^**, Anna Henger, Stefanie Krick^*, Jeffrey B. Kopp, Christian J. Stoeckert, Jr., Steven Dikman, Bernd Schröppel^*, David B. Thomas^¶¶, Detlef Schlondorff^*, Matthias Kretzler and Erwin P. Böttinger^*

From the Department of Medicine,^* Division of Nephrology, and the Department of Pathology, Mount Sinai School of Medicine, New York, New York; the Departments of Internal Medicine-Nephrology, and Statistics,|| University of Michigan, Ann Arbor, Michigan; the Department of Medicine, Division of Nephrology, Albert Einstein College of Medicine, Bronx, New York; the Department of Pediatric Nephrology, University of Heidelberg, Heidelberg, Germany; the Department of Public Health and Preventive Medicine’s Division of Biostatistics,^¶ Oregon Health and Science University, Portland, Oregon; the Nephrology Clinic and Institute of Physiology,^** University of Zurich, Zurich, Switzerland; the Kidney Disease Branch, National Institute of Diabetes, Digestive, and Kidney Disease, National Institutes of Health, Bethesda, Maryland; the Department of Genetics, Center for Bioinformatics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania; and the New York Laboratory^¶¶ , Nephrocor, Uniondale, New York

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-β1 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 (R² = 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.

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