Urine peptidomic biomarkers for diagnosis of patients with systematic lupus erythematosus

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

Advanced methods and novel biomarkers in autoimmune diseases ‑ a review of the recent years progress in systemic lupus erythematosus

There are several autoimmune and rheumatic diseases affecting different organs of the human body. Multiple sclerosis (MS) mainly affects brain, rheumatoid arthritis (RA) mainly affects joints, Type 1 diabetes (T1D) mainly affects pancreas, Sjogren’s syndrome (SS) mainly affects salivary glands, while systemic lupus erythematosus (SLE) affects almost every organ of the body. Autoimmune diseases are characterized by production of autoantibodies, activation of immune cells, increased expression of pro-inflammatory cytokines, and activation of type I interferons. Despite improvements in treatments and diagnostic tools, the time it takes for the patients to be diagnosed is too long, and the main treatment for these diseases is still non-specific anti-inflammatory drugs. Thus, there is an urgent need for better biomarkers, as well as tailored, personalized treatment. This review focus on SLE and the organs affected in this disease. We have used the results from various rheumatic and autoimmune diseases and the organs involved with an aim to identify advanced methods and possible biomarkers to be utilized in the diagnosis of SLE, disease monitoring, and response to treatment

Biomarkers of lupus nephritis determined by serial urine proteomics

Lupus nephritis is a frequent and serious complication of systemic lupus erythematosus (SLE), the treatment of which often requires the use of immunosuppressives that can have severe side effects. Here we determined the low-molecular weight proteome of serial lupus urine samples to uncover novel and predictive biomarkers of SLE renal flare. Urine from 25 flare cycles of 19 patients with WHO Class III, IV, and V SLE nephritis were obtained at baseline, pre-flare, flare and post-flare. Each sample was first fractionated to remove proteins larger than 30kDa, then applied onto weak cation exchanger protein chips for analysis by SELDI-TOF mass spectrometry. We found 176 protein ions of which 27 were differentially expressed between specific flare intervals. On-chip peptide sequencing by integrated tandem mass spectrometry positively identified the 20 and 25 amino-acid isoforms of hepcidin, as well as fragments of α1-antitrypsin and albumin among the selected differentially expressed protein ions. Hepcidin 20 increased 4 months before renal flare and returned to baseline at renal flare, whereas hepcidin 25 decreased at renal flare and returned to baseline 4 months after the flare. These studies provide a beginning proteomic analysis aimed at predicting impending renal relapse, relapse severity, and the potential for recovery after SLE nephritis flare

Accelerating Medicines Partnership: Organizational Structure and Preliminary Data From the Phase 1 Studies of Lupus Nephritis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153724/1/acr24066_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153724/2/acr24066.pd

Identification of Stage‐Specific Genes Associated With Lupus Nephritis and Response to Remission Induction in (NZB × NZW)F1 and NZM2410 Mice

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108024/1/art38679.pd

PeptiCKDdb-peptide- and protein-centric database for the investigation of genesis and progression of chronic kidney disease

The peptiCKDdb is a publicly available database platform dedicated to support research in the field of chronic kidney disease (CKD) through identification of novel biomarkers and molecular features of this complex pathology. PeptiCKDdb collects peptidomics and proteomics datasets manually extracted from published studies related to CKD. Datasets from peptidomics or proteomics, human case/control studies on CKD and kidney or urine profiling were included. Data from 114 publications (studies of body fluids and kidney tissue: 26 peptidomics and 76 proteomics manuscripts on human CKD, and 12 focusing on healthy proteome profiling) are currently deposited and the content is quarterly updated. Extracted datasets include information about the experimental setup, clinical study design, discovery-validation sample sizes and list of differentially expressed proteins (P-value < 0.05). A dedicated interactive web interface, equipped with multiparametric search engine, data export and visualization tools, enables easy browsing of the data and comprehensive analysis. In conclusion, this repository might serve as a source of data for integrative analysis or a knowledgebase for scientists seeking confirmation of their findings and as such, is expected to facilitate the modeling of molecular mechanisms underlying CKD and identification of biologically relevant biomarkers.Database URL: www.peptickddb.com