Use of the Urine-to-Plasma Urea Ratio to Predict ADPKD Progression

BACKGROUND AND OBJECTIVES: Predicting disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD) poses a challenge, especially in early-stage disease when kidney function is not yet affected. Ongoing growth of cysts causes maximal urine-concentrating capacity to decrease from early on. We therefore hypothesized that the urine-to-plasma urea ratio, as a reflection of the urine-concentrating capacity, can be used as a marker to predict ADPKD progression. DESIGN: The urine-to-plasma urea ratio was calculated by dividing concentrations of early morning fasting spot urine urea by plasma urea. First, this ratio was validated as surrogate marker in 30 patients with ADPKD who underwent a prolonged water deprivation test. Thereafter, association with kidney outcome was evaluated in 583 patients with ADPKD with a broad range of kidney function. Multivariable mixed-model regression was used to assess association with eGFR slope, and logarithmic regression to identify patients with rapidly progressive disease, using a cutoff of -3.0 ml/min per 1.73 m2 per year. The urine-to-plasma urea ratio was compared with established predictors, namely, sex, age, baseline eGFR, Mayo Clinic height-adjusted total kidney volume class, and PKD gene mutation. RESULTS: The maximal urine-concentrating capacity and urine-to-plasma urea ratio correlated strongly (R=0.90; P<0.001). Next, the urine-to-plasma urea ratio was significantly associated with rate of eGFR decline during a median follow-up of 4.0 (interquartile range, 2.6-5.0) years, both crude and after correction for established predictors (β=0.58; P=0.02). The odds ratio of rapidly progressive disease was 1.35 (95% confidence interval, 1.19 to 1.52; P<0.001) for every 10 units decrease in urine-to-plasma urea ratio, with adjustment for predictors. A combined risk score of the urine-to-plasma urea ratio, Mayo Clinic height-adjusted total kidney volume class, and PKD mutation predicted rapidly progressive disease better than each of the predictors separately. CONCLUSIONS: The urine-to-plasma urea ratio, which is calculated from routine laboratory measurements, predicts disease progression in ADPKD in addition to other risk markers. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_01_27_CJN10470620_final.mp3

Urinary Biomarkers to Identify Autosomal Dominant Polycystic Kidney Disease Patients With a High Likelihood of Disease Progression

The variable disease course of autosomal dominant polycystic kidney disease (ADPKD) makes it important to develop biomarkers that can predict disease progression, from a patient perspective and to select patients for renoprotective treatment. We therefore investigated whether easy-to-measure urinary biomarkers are associated with disease progression and have additional value over that of conventional risk markers. Methods: At baseline, inflammatory, glomerular, and tubular damage markers were measured in 24-hour urine collections (albumin, IgG, kidney injury molecule−1 (KIM-1), N-acetyl-β-d-glucosaminidase (NAG), β2 microglobulin (β2MG), heart-type fatty acid binding protein (HFABP), macrophage migration inhibitory factor (MIF), neutrophil gelatinase-associated lipocalin (NGAL), and monocyte chemotactic protein−1 (MCP-1). Disease progression was expressed as annual change in estimated glomerular filtration rate (eGFR, Chronic Kidney Disease EPIdemiology equation), measured glomerular filtation rate (mGFR, using 125I-iothalamate), or height-adjusted total kidney volume (htTKV). Multivariable linear regression was used to assess associations of these markers independent of conventional risk markers. Results: A total of 104 ADPKD patients were included (40 ± 11 years, 39% female, eGFR 77 ± 30, mGFR 79 ± 30 ml/min per 1.73 m2 and htTKV 852 [510−1244] ml/m). In particular, β2MG and MCP-1 were associated with annual change in eGFR, and remained associated after adjustment for conventional risk markers (standardized β = −0.35, P = 0.001, and standardized β = −0.29, P = 0.009, respectively). Adding β2MG and MCP-1 to a model containing conventional risk markers that explained annual change in eGFR significantly increased the performance of the model (final R2 = 0.152 vs. 0.292, P = 0.001). Essentially similar results were obtained when only patients with an eGFR ≥ 60 ml/min per 1.73 m2 were selected, or when change in mGFR was studied. Associations with change in htTKV were less strong. Conclusion: Urinary β2MG and MCP-1 excretion were both associated with GFR decline in ADPKD, and had added value beyond that of conventional risk markers. These markers therefore have the potential to serve as predictive tools for clinical practice