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

A Lianne Messchendorp; Esther Meijer; Wendy E Boertien; Gerwin E Engels; Niek F Casteleijn; Edwin M Spithoven; Monique Losekoot; Johannes G M Burgerhof; Dorien J M Peters; Ron T Gansevoort; DIPAK Consortium

doi:10.1016/j.ekir.2017.10.004

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

Kidney Int Rep. 2017 Oct 14;3(2):291-301. doi: 10.1016/j.ekir.2017.10.004. eCollection 2018 Mar.

Affiliations

¹ Department of Nephrology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
² HaemoScan bv, Groningen, the Netherlands.
³ Department of Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands.
⁴ Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
⁵ Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands.

Abstract

Introduction: 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.

Keywords: ADPKD; MCP-1; beta-2 microglobulin; kidney function decline; kidney volume; urinary biomarkers.