Dataset Information

Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.

ABSTRACT: Chronic kidney disease (CKD) affects 8 to 16% people worldwide, with an increasing incidence and prevalence of end-stage kidney disease (ESKD). The effective management of CKD is confounded by the inability to identify patients at high risk of progression while in early stages of CKD. To address this challenge, a renal biopsy transcriptome-driven approach was applied to develop noninvasive prognostic biomarkers for CKD progression. Expression of intrarenal transcripts was correlated with the baseline estimated glomerular filtration rate (eGFR) in 261 patients. Proteins encoded by eGFR-associated transcripts were tested in urine for association with renal tissue injury and baseline eGFR. The ability to predict CKD progression, defined as the composite of ESKD or 40% reduction of baseline eGFR, was then determined in three independent CKD cohorts. A panel of intrarenal transcripts, including epidermal growth factor (EGF), a tubule-specific protein critical for cell differentiation and regeneration, predicted eGFR. The amount of EGF protein in urine (uEGF) showed significant correlation (P < 0.001) with intrarenal EGF mRNA, interstitial fibrosis/tubular atrophy, eGFR, and rate of eGFR loss. Prediction of the composite renal end point by age, gender, eGFR, and albuminuria was significantly (P < 0.001) improved by addition of uEGF, with an increase of the C-statistic from 0.75 to 0.87. Outcome predictions were replicated in two independent CKD cohorts. Our approach identified uEGF as an independent risk predictor of CKD progression. Addition of uEGF to standard clinical parameters improved the prediction of disease events in diverse CKD populations with a wide spectrum of causes and stages.

SUBMITTER: Ju W

PROVIDER: S-EPMC4861144 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.

Ju Wenjun W Nair Viji V Smith Shahaan S Zhu Li L Shedden Kerby K Song Peter X K PXK Mariani Laura H LH Eichinger Felix H FH Berthier Celine C CC Randolph Ann A Lai Jennifer Yi-Chun JY Zhou Yan Y Hawkins Jennifer J JJ Bitzer Markus M Sampson Matthew G MG Thier Martina M Solier Corinne C Duran-Pacheco Gonzalo C GC Duchateau-Nguyen Guillemette G Essioux Laurent L Schott Brigitte B Formentini Ivan I Magnone Maria C MC Bobadilla Maria M Cohen Clemens D CD Bagnasco Serena M SM Barisoni Laura L Lv Jicheng J Zhang Hong H Wang Hai-Yan HY Brosius Frank C FC Gadegbeku Crystal A CA Kretzler Matthias M

Science translational medicine 20151201 316

Chronic kidney disease (CKD) affects 8 to 16% people worldwide, with an increasing incidence and prevalence of end-stage kidney disease (ESKD). The effective management of CKD is confounded by the inability to identify patients at high risk of progression while in early stages of CKD. To address this challenge, a renal biopsy transcriptome-driven approach was applied to develop noninvasive prognostic biomarkers for CKD progression. Expression of intrarenal transcripts was correlated with the bas ...[more]

PMID: 26631632

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Project description:BACKGROUND:Acute kidney injury (AKI) is most commonly caused by sepsis in critically ill patients, and it is associated with high morbidity and mortality. The pathophysiology of sepsis-induced AKI is generally accepted to include direct inflammatory injury, endothelial cell dysfunction, and apoptosis. Milk fat globule-epidermal growth factor-factor VIII (MFG-E8) is a secretory glycoprotein with a known role in the enhancement of apoptotic cell clearance and regulation of inflammation. We hypothesize that administration of recombinant mouse MFG-E8 (rmMFG-E8) can protect mice from kidney injuries caused by sepsis. METHODS:Sepsis was induced in 8-wk-old male C57BL/6 mice by cecal ligation and puncture (CLP). rmMFG-E8 or phosphate-buffered saline (vehicle) was injected intravenously at a dosage of 20 ?g/kg body weight at time of CLP (n = 5-8 mice per group). After 20 h, serum and renal tissue were harvested for various analyses. The renal injury markers blood urea nitrogen (BUN) and creatinine were determined by enzymatic and chemical reactions, respectively. The gene expression analysis was carried out by real-time quantitative polymerase chain reaction. RESULTS:At 20 h after CLP, serum levels of BUN and creatinine were both significantly increased in the vehicle group compared with the sham group, whereas the mice treated with rmMFG-E8 had a significant reduction in BUN and creatinine levels by 28% and 24.1%, respectively (BUN: 197.7 ± 23.6 versus 142.3 ± 20.7 mg/dL; creatinine: 0.83 ± 0.12 versus 0.63 ± 0.06 mg/dL; P < 0.05). Expressions of novel biomarkers of renal tissue injury neutrophil gelatinase-associated lipocalin and kidney injury molecule-1 were also significantly downregulated by 58.2% and 95%, respectively, after treatment with rmMFG-E8. Proinflammatory cytokine interleukin-6 and tumor necrosis factor-? messenger RNA (mRNA) were significantly reduced by 50.8% and 50.3%, respectively, in rmMFG-E8-treated mice compared with vehicle-treated mice. The mRNA levels of the chemokines keratinocyte chemoattractant and macrophage inhibitory protein-2 were reduced by 85.1% and 78%, respectively, in mice treated with rmMFG-E8 compared with the vehicle mice. In addition, the expression of intercellular cell adhesion molecule-1 and platelet endothelial cell adhesion molecule-1 (PECAM-1/CD31) mRNA was downregulated by 35.6% and 77.8%, respectively, in rmMFG-E8-treated mice compared with the vehicle animals (P < 0.05). CONCLUSIONS:Treatment with rmMFG-E8 reduces renal tissue injury induced by sepsis through inhibiting the production of proinflammatory cytokines and chemokine, as well as through the activation of endothelial cells. Thus, MFG-E8 may have a therapeutic potential for treating AKI induced by sepsis.

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Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.

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Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.

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