Urine proteomics by mass spectrometry identifies proteins involved in key pathogenic pathways in patients with juvenile dermatomyositis

Abstract

Objectives To identify and validate biomarkers in juvenile dermatomyositis (JDM) patients using a multiplexing tandem mass tag urine proteome profiling approach. Methods First morning void urine samples were collected from JDM patients (n = 20) and healthy control subjects (n = 21) and processed for analysis using a standardized Liquid Chromatography-Tandem Mass Spectrometry approach. Biomarkers with significantly altered levels were correlated with clinical measures of myositis disease activity and damage. A subset of candidate biomarkers was validated using commercially available ELISA kits. Results In total, 2348 proteins were detected in the samples, with 275 proteins quantified across all samples. Among the differentially altered proteins, Cathepsin D and Galectin-3 binding protein were significantly increased in the urine of JDM patients (adj p< 0.05), supporting previous findings in myositis patients. These two candidate biomarkers were confirmed with ELISAs. Cathepsin D positively correlated with Myositis Damage Index (r = 0.57, p< 0.05) and negatively correlated with the Childhood Myositis Assessment Scale (r=-0.54, p< 0.05). We also identified novel JDM candidate biomarkers involved with key features of myositis, including extracellular matrix remodeling proteins. Conclusion This study confirmed the presence of several proteins in the urine of JDM patients that were previously found to be elevated in the blood of myositis patients and identified novel candidate biomarkers that require validation. These results support the use of urine as a source for biomarker development in JDM.

Retrospective Study Shows That Serum Levels of Chemokine CXCL10 and Cytokine GDF15 Support a Diagnosis of Sporadic Inclusion Body Myositis and Immune-Mediated Necrotizing Myopathy

“…Another innovation could be to attempt the least invasive sample collection available, which involves analyzing a urine sample. The urine proteome as a possible source of biomarkers has been explored for the juvenile form of DM [42]. In chronic kidney disease, urine GDF15 levels have already been shown predictors of mortality with an AUC of 0.95 [43].…”

Detection of prodromal Parkinson’s disease using a urine proteomics panel and machine learning

“…The urine proteome is an interesting source for non-invasive biomarker development, as it is readily available in large quantities, the majority of its´ content independent of diurnal variability and proteolytic degradation, and accessible to mass spectrometer measurement 42 . First studies have capitalised on these characteristics for biomarker detection in patients with cognitive decline 43,44 , neural ceroid lipofuscinosis 45 , kidney disease 46 , cancer 47 , dermatomyositis 48 but also Parkinson´s disease 49,50 .…”