| Literature DB >> 28474961 |
M Pejchinovski1, J Siwy1, W Mullen2, H Mischak1,2, M A Petri3, L C Burkly4, R Wei4.
Abstract
Background Systematic lupus erythematosus (SLE) is characterized with various complications which can cause serious organ damage in the human body. Despite the significant improvements in disease management of SLE patients, the non-invasive diagnosis is entirely missing. In this study, we used urinary peptidomic biomarkers for early diagnosis of disease onset to improve patient risk stratification, vital for effective drug treatment. Methods Urine samples from patients with SLE, lupus nephritis (LN) and healthy controls (HCs) were analyzed using capillary electrophoresis coupled to mass spectrometry (CE-MS) for state-of-the-art biomarker discovery. Results A biomarker panel made up of 65 urinary peptides was developed that accurately discriminated SLE without renal involvement from HC patients. The performance of the SLE-specific panel was validated in a multicentric independent cohort consisting of patients without SLE but with different renal disease and LN. This resulted in an area under the receiver operating characteristic (ROC) curve (AUC) of 0.80 ( p < 0.0001, 95% confidence interval (CI) 0.65-0.90) corresponding to a sensitivity and a specificity of 83% and 73%, respectively. Based on the end terminal amino acid sequences of the biomarker peptides, an in silico methodology was used to identify the proteases that were up or down-regulated. This identified matrix metalloproteinases (MMPs) as being mainly responsible for the peptides fragmentation. Conclusions A laboratory-based urine test was successfully established for early diagnosis of SLE patients. Our approach determined the activity of several proteases and provided novel molecular information that could potentially influence treatment efficacy.Entities:
Keywords: SLE; protease prediction; urine peptide biomarkers
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Year: 2017 PMID: 28474961 PMCID: PMC6037307 DOI: 10.1177/0961203317707827
Source DB: PubMed Journal: Lupus ISSN: 0961-2033 Impact factor: 2.911