Predictive Biomarker Panel in Proliferative Lupus Nephritis- Two-Dimensional Shotgun Proteomics.

INTRODUCTION: Lupus nephritis (LN) is one of the most serious complications of systemic lupus erythematous (SLE). With no specific clinical or laboratory manifestation to predict response to treatment, this study was aimed to provide a panel of predictive biomarkers of response before initiation of treatment. METHODS: Liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis was performed on plasma and urine samples of 11 patients with biopsy proven proliferative LN at the time of biopsy. Unsupervised principal component analysis (PCA), orthogonal projection to latent structures discriminant analysis (OPLS-DA), gene ontology annotation and protein mapping were performed on 326 proteins in plasma and 1381 proteins in urine samples. RESULTS: Samples of eight patients achieved complete remission and three reached partial remission were analyzed. The mean 24-hour protein excretion was 3259 mg/day and the mean eGFR was 87.73 cc/min. OPLS-DA analysis of plasma samples showed a clear discrimination for complete and partial remission patients. Twenty plasma proteins and ten urine proteins with the highest fold changes and AUCs were selected as candidate biomarkers (IGHV1-18, PI16, IGHD, C3, FCER2, EPS8L2, CTTN, BLVRB). This plasma and urine biomarker panel is involved in oxidative stress, acute inflammation, reduction in regulatory T cells, complement pathway consumption, and proximal tubule bicarbonate reclamation. CONCLUSION: Our suggested panel of plasma and urine biomarkers can precisely discriminate patients with possibility of complete response to treatment. It seems that the higher indices of inflammation will associate with better chance of achieving complete remission.

Urinary epidermal growth factor is a novel biomarker for early diagnosis of antibody mediated kidney allograft rejection: A urinary proteomics analysis.

Although antibody mediated rejection (AMR) accounts for 20-30% of all acute renal allograft rejections, introducing biomarkers for a timely detection of allograft rejection has been remained challenging. This study investigated novel diagnostic biomarkers of AMR by examining of urine proteome in renal transplant patients. Thirty-six patients with kidney transplantation including 22 AMR patients and 14 patients with stable renal function (control group) were enrolled in this study. Urinary samples were collected and Label free quantification (LFQ) proteomics technique was applied on urine samples and data was subjected to Random Forest (RF) algorithm to predict main candidate proteins contributing in AMR. Finally, applicability of candidate diagnostic biomarkers was evaluated in new sets of AMR subjects, stable patients and healthy volunteers. A total of 1020 proteins were detected in urine proteome. RF algorithm predicted 20 differentially expressed proteins with the highest sensitivity and specificity and combination of EGF, COL6A, and NID-1 was identified as possible panel for early diagnosis of AMR. Applicability of EGF as diagnostic biomarker was validated in urine samples of independent set of AMR subjects. This is the first urinary proteomics study in AMR patients demonstrating that urinary EGF might be used as early diagnostic biomarker for AMR. SIGNIFICANCE: Renal antibody mediated rejection (AMR) accounts for 20-30% of all acute rejections of allografted kidneys. Although several possible biomarkers have been proposed to predict AMR, ineffectiveness of current urinary biomarkers in early diagnosing of AMR patients and in distinguishing AMR subjects from patients with stable kidney function casts doubts on their applicability in clinic. Here for the first time and based on the analysis of urinary proteome we showed that uEGF and uEGF/Cr might be candidate biomarkers to predict AMR with high diagnostic power.