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Multicenter Study
. 2013 May;40(5):674-83.
doi: 10.3899/jrheum.120879. Epub 2013 Apr 1.

urinary biomarkers in relapsing antineutrophil cytoplasmic antibody-associated vasculitis

Affiliations
Multicenter Study

urinary biomarkers in relapsing antineutrophil cytoplasmic antibody-associated vasculitis

Jason G Lieberthal et al. J Rheumatol. 2013 May.

Abstract

Objective: Glomerulonephritis (GN) is common in antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), but tools for early detection of renal involvement are imperfect. We investigated 4 urinary proteins as markers of active renal AAV: alpha-1 acid glycoprotein (AGP), kidney injury molecule-1 (KIM-1), monocyte chemoattractant protein-1 (MCP-1), and neutrophil gelatinase-associated lipocalin (NGAL).

Methods: Patients with active renal AAV (n = 20), active nonrenal AAV (n = 16), and AAV in longterm remission (n = 14) were identified within a longitudinal cohort. Urinary biomarker concentrations (by ELISA) were normalized for urine creatinine. Marker levels during active AAV were compared to baseline remission levels (from 1-4 visits) for each patient. Areas under receiver-operating characteristic curves (AUC), sensitivities, specificities, and likelihood ratios (LR) comparing disease states were calculated.

Results: Baseline biomarker levels varied among patients. All 4 markers increased during renal flares (p < 0.05). MCP-1 discriminated best between active renal disease and remission: a 1.3-fold increase in MCP-1 had 94% sensitivity and 89% specificity for active renal disease (AUC = 0.93, positive LR 8.5, negative LR 0.07). Increased MCP-1 also characterized 50% of apparently nonrenal flares. Change in AGP, KIM-1, or NGAL showed more modest ability to distinguish active renal disease from remission (AUC 0.71-0.75). Hematuria was noted in 83% of active renal episodes, but also 43% of nonrenal flares and 25% of remission samples.

Conclusion: Either urinary MCP-1 is not specific for GN in AAV, or it identifies early GN not detected by standard assessment and thus has potential to improve care. A followup study with kidney biopsy as the gold standard is needed.

Keywords: BIOMARKERS; GLOMERULONEPHRITIS; MONOCYTE CHEMOATTRACTANT PROTEIN-1; VASCULITIS; WEGENER GRANULOMATOSIS.

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Figures

Figure 1
Figure 1
Trajectories of urinary biomarker concentrations in individual patients, divided into groups based on the presence of a flare of vasculitis with renal involvement (left panels), flare without evidence of renal involvement (middle panels), or remission for at least 2 years (right panels). Flare was defined as Day 0, and time before or after that visit was calculated for every other sample. For patients in longterm remission, the middle of the 3 visits was defined as Day 0. Concentrations of all markers were divided by the urine creatinine concentration. AGP: alpha-1 acid glycoprotein; KIM-1: kidney injury molecule-1; MCP-1: monocyte chemoattractant protein-1; NGAL: neutrophil gelatinase-associated lipocalin; Cr: urine creatinine.
Figure 2
Figure 2
Ability of fold-change in biomarker concentration to distinguish active renal disease, active nonrenal disease, and remission. Concentrations of all markers were divided by the urine creatinine (Cr) concentration. The marker level for each sample was divided by the mean level during remission for each patient. Such fold-changes are shown in the left panels, with patients divided into groups as in Figure 1. Receiver-operating characteristic curves (ROC; right panels) were calculated using fold-changes in marker levels as the independent variables and disease state (active renal disease vs remission) as the dichotomous dependent variable; areas under the ROC curves (AUC) are shown. AGP: alpha-1 acid glycoprotein; KIM-1: kidney injury molecule-1; MCP-1: monocyte chemoattractant protein-1; NGAL: neutrophil gelatinase-associated lipocalin.
Figure 3
Figure 3
Association of urinary biomarker concentration with total urine protein concentration (A) and urinalysis results (B). A. Data points from the same patients are connected by broken lines. Solid lines show results of linear regression, and correlation coefficients (r) are shown. Both marker and protein concentrations were divided by urinary creatinine (Cr) concentrations, which is equivalent to simply plotting marker versus total protein concentration without such normalization. B. All samples from patients in remission (top panels) or with active nonrenal vasculitis (bottom panels) that also had urinalysis data were classified into 4 groups based on the presence of urinary red blood cells (RBC; by microscopy) and/or protein (on dipstick). P values from Kruskal-Wallis tests are shown in the top panels; p values for comparisons in the bottom panels were all > 0.3, but power to detect differences was low. AGP: alpha-1 acid glycoprotein; KIM-1: kidney injury molecule-1; MCP-1: monocyte chemoattractant protein-1; NGAL: neutrophil gelatinase-associated lipocalin.
Figure 4
Figure 4
Relationship between urinary biomarker concentrations and urinary protein concentration (A), glomerular filtration rate (B), age (C), and sex (D). Concentrations of all markers were divided by the urine creatinine concentration. Results of all samples are shown in the top set of panels in A; only data from samples with urine protein/creatinine (Pr/Cr) between 0.15 and 0.7 are shown in the bottom set of panels in A. In B to D, the mean remission value for each patient is plotted, and in B, glomerular filtration rate (GFR) was calculated at the last remission visit. Spearman correlation coefficients (r) and associated p values are shown; in D, p values were determined by Wilcoxon rank-sum tests. AGP: alpha-1 acid glycoprotein; KIM-1: kidney injury molecule-1; MCP-1: monocyte chemoattractant protein-1; NGAL: neutrophil gelatinase-associated lipocalin.

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