Abstract

Renal activity and smoldering disease is difficult to assess in anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) because of renal scarring. Even repeated biopsies suffer from sampling errors in this focal disease especially in patients with chronic renal insufficiency. We applied capillary electrophoresis coupled to mass spectrometry toward urine samples from patients with active renal AAV to identify and validate urinary biomarkers that enable differential diagnosis of disease and assessment of disease activity. The data were compared with healthy individuals, patients with other renal and non-renal diseases, and patients with AAV in remission. 113 potential biomarkers were identified that differed significantly between active renal AAV and healthy individuals and patients with other chronic renal diseases. Of these, 58 could be sequenced. Sensitivity and specificity of models based on 18 sequenced biomarkers were validated using blinded urine samples of 40 patients with different renal diseases. Discrimination of AAV from other renal diseases in blinded samples was possible with 90% sensitivity and 86.7-90% specificity depending on the model. 10 patients with active AAV were followed for 6 months after initiation of treatment. Immunosuppressive therapy led to a change of the proteome toward "remission." 47 biomarkers could be sequenced that underwent significant changes during therapy together with regression of clinical symptoms, normalization of C-reactive protein, and improvement of renal function. Proteomics analysis with capillary electrophoresis-MS represents a promising tool for fast identification of patients with active AAV, indication of renal relapses, and monitoring for ongoing active renal disease and remission without renal biopsy.

Highlights

  • Renal activity and smoldering disease is difficult to assess in anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) because of renal scarring

  • Identification of Urinary Biomarkers for Differential Diagnosis of Vasculitis—Data from capillary electrophoresis (CE)-MS analysis of 18 patients with active anti-neutrophil cytoplasmic antibodies (ANCAs)-associated vasculitis were compared with data obtained from healthy volunteers (n ϭ 200) and focal segmental glomerulosclerosis (FSGS) (n ϭ 30), diabetic nephropathy (n ϭ 78), IgA nephropathy (IgAN) (n ϭ 57), minimal change disease (MCD) (n ϭ 25), and membranous glomerulonephritis (MNGN) (n ϭ 35) patients

  • A graphic depiction of the distribution of these 113 potential biomarkers in the seven different groups is shown in Fig. 3; all data, including the area under the ROC curve (AUC) values for the individual biomarkers and the p value after adjustment of the false discovery rate (FDR) according to the method of Benjamini and Hochberg [32], are given in supplemental Table 1

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Summary

EXPERIMENTAL PROCEDURES

Procedures, and Demographics—Informed consent was obtained from all patients and healthy controls after local ethics committee approval. This relative distance of signal intensities between the disease and control samples was provided using the formula (Aki Ϫ meanaverages)(2/͉x៮case Ϫ x៮control) where Aki is the logtransformed signal intensity of the ith biomarker in the kth sample in either the test set or the blinded set, meanaverages is the average of the mean intensity of all possible markers for test set samples, x៮case represents the mean observed signal intensity of the possible biomarker from all vasculitis samples, and x៮control represents the mean signal intensity of the possible biomarker from the combined control samples (apparently healthy individuals and patients with chronic renal disease other than vasculitis) This linear classification procedure is in some way a simplified version of the nearest centroid classification approaches. All sequences obtained from human urine can be accessed as described previously [23]

RESULTS
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Lin model
DISCUSSION
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