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

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.

Genomic biomarkers for chronic kidney disease.

Chronic kidney disease (CKD) remains a major challenge in nephrology and for public health care, affecting 14% to 15% of the adult US population and consuming significant health care resources. In the next 20 years, the number of patients with end stage renal disease is projected to increase by 50%. Ideal biomarkers that allow early identification of CKD patients at high risk of progression are urgently needed for early and targeted treatment to improve patient care. Recent success of integrating molecular approaches for personalized management of neoplastic diseases, including diagnosis, staging, prognosis, treatment selection, and monitoring, has strongly encouraged kidney researchers to pursue molecular definitions of patients with kidney disease. Challenges for molecular marker identification in CKD are a high degree of cellular heterogeneity of the kidney and the paucity of human tissue availability for molecular studies. Despite these limitations, potential molecular biomarker candidates have been uncovered at multiple levels along the genome--phenome continuum. Here we will review the identification and validation of potential genomic biomarker candidates of CKD and CKD progression in clinical studies. The challenges in predicting CKD progression, as well as the promises and opportunities resulting from a molecular definition of CKD will be discussed.