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.

Fig. 1

Schematic overview of the tissue transcriptome-driven strategy to identify urinary biomarkers for CKD progression.

Fig. 2. Transcript-eGFR association and EGF expression in the kidney in patients with CKD

(A) Correlation between observed and predicted eGFR (continuous line) on the basis of intrarenal transcripts integrated by ridge regression analysis (top 1 to 30 transcripts shown), providing eGFR prediction in the validation cohort (n = 55). Gray area represents 95% confidence interval (CI). Black arrow indicates the highest correlation provided by a six-marker set, which is depicted in (B). (B) Maximal correlation (r = 0.77, P < 0.0001) was demonstrated between observed eGFR and that predicted by gene expression values of six transcripts (n = 55). Dotted line represents 95% CI. (C) Intrarenal EGF mRNA showed a significant correlation with patients’ eGFR in discovery (n = 164) and validation cohorts (n = 55 and 42). TLDA, Taq-Man Low Density Array. (D) EGF mRNA expression in major human organs/tissues (a selection out of a panel of 84 human organs/tissues and cell lines), derived from BioGPS (http://biogps.org), indicating a highly kidney-specific expression pattern. For full data set, see fig. S2. (E) EGF mRNA expression pattern in adult kidney (glomeruli, inner and outer cortex, inner and outer medulla, papillary tips, and renal pelvis); data were extracted from Higgins et al. (10). (F) In situ hybridization demonstrates tubule-specific EGF mRNA in both cortex (I and III) and medulla (II and IV), with reduced expression in CKD (III and IV) compared to healthy controls (I and II). Black arrows indicate positive staining in pink. Scale bars, 50 μM.

Fig. 3. Correlation of uEGF/Cr with intrarenal EGF mRNA and eGFR

(A and B) uEGF/Cr is correlated with intrarenal EGF mRNA in patients with matching urine enzyme-linked immunosorbent assay (ELISA) data and tissue mRNA expression data in C-PROBE (A) (n = 34) and NEPTUNE (B) (n = 85) cohorts. uEGF/Cr is correlated significantly (P < 0.0001) with eGFR at the time of biopsy in patients from C-PROBE [(C) n = 349], NEPTUNE [(D) n = 141], and PKU-IgAN [(E) n = 452].

Fig. 4. Association of uEGF/Cr with tubulointerstitial damage

(A and B) Tubulointerstitial damage is reflected by the percentage of cortex affected by IF/TA. Scoring of IF/TA was based on evaluation of silver, periodic acid–Schiff (PAS), and trichrome-stained kidney sections (n = 102) by six readers who were blinded to the uEGF/Cr value. For each section, the average scores of the six readers for IF and TA were calculated as indicators of tubulointerstitial damage. uEGF/Cr is significantly correlated with IF (A) and TA (B) scores (Spearman correlation, P < 0.001).

Fig. 5. Association of EGF with eGFR slope

(A) Intrarenal EGF RNA expression correlated significantly (P < 0.001) with eGFR slope in C-PROBE patients (n = 29). (B and C) Correlation of the observed eGFR slope of CKD patients in C-PROBE (n = 344) with slope predicted by uEGF/Cr (B) or ACR (C) using a regression model (adjusted for age and gender). eGFR slope predicted by uEGF/Cr (B) exhibited a higher correlation with the observed value than slope predicted by ACR (C).

Fig. 6. Multivariable-adjusted HRs for predicting the composite end point on the basis of uEGF/Cr

HRs were adjusted by age, gender, eGFR, and ACR. Adjusted HRs and 95% CIs were obtained by separate Cox regression models in each study cohort. A one-unit decrease of uEGF/Cr (in log scale) was associated with an increased risk of CKD progression of 3.73 (1.85 to 7.69)–fold, 3.43 (1.72 to 6.67)–fold, and 1.96 (1.45 to 2.70)–fold in these three cohorts. The unadjusted HRs for EGF were 0.33 (0.21 to 0.51) (C-PROBE), 0.33 (0.21 to 0.52) (NEPTUNE), and 0.57 (0.46 to 0.70) (PKU-IgAN).