Plasma and Urine Proteomics in Nephrotic Syndrome
Ontology highlight
ABSTRACT:
INSTRUMENT(S): LTQ Orbitrap, instrument model
ORGANISM(S): Homo Sapiens (human)
TISSUE(S): Urine
SUBMITTER: 
Johan Palmfeldt
PROVIDER: PRD000551 | Pride | 2012-04-18
REPOSITORIES: Pride
Dataset's files
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Project description:BACKGROUND:Nephrotic syndrome (NS) is a nonspecific kidney disorder, commonly caused by minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), and membranous nephropathy (MN). Here we analyzed urinary protein profiles, aiming to discover disease-specific biomarkers of these three common diseases in NS. METHODS:Sixteen urine samples were collected from patients with biopsy-proven NS and healthy controls. After removal of high-abundance proteins, the urinary protein profile was analyzed by LC-MS/MS to generate a discovery set. For validation, ELISA was used to analyze the selected proteins in 61 urine samples. RESULTS:The discovery set included 228 urine proteins, of which 22 proteins were differently expressed in MCD, MN, and FSGS. Among these, C9, CD14, and SERPINA1 were validated by ELISA. All three proteins were elevated in MCD, MN, and FSGS groups compared with in IgA nephropathy and healthy controls. When a regression model was applied, receiver operating characteristic analysis clearly discriminated MCD from the other causative diseases in NS. CONCLUSIONS:We developed a disease-specific protein panel that discriminated between three main causes of NS. Through this pilot study, we suggest that urine proteomics could be a non-invasive and clinically available tool to discriminate MCD from MN and FSGS.
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Project description:Maternal plasma samples collected longitudinally from pregnant women were profiled using SomaLogic aptamer-based assays in women with normal pregnancy and those who delivered preterm. DiagnosisGA is the gestational age at diagnosis with any disease indicated by the Group variable, and it is set to NA for normal pregnancies. In the Group variable, sPTD stands for spontaneous preterm delivery, and PPROM for preterm premature rupture of membranes. Additional longitudinal samples of the controls, including the two samples included herein, are also available and described in PMID: 28738067.
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Project description:Introduction:Nephrotic syndrome (NS) is a characterized by massive proteinuria, edema, hypoalbuminemia, and dyslipidemia. Glucocorticoids (GCs), the primary therapy for >60 years, are ineffective in approximately 50% of adults and approximately 20% of children. Unfortunately, there are no validated biomarkers able to predict steroid-resistant NS (SRNS) or to define the pathways regulating SRNS. Methods:We performed proteomic analyses on paired pediatric NS patient plasma samples obtained both at disease presentation before glucocorticoid initiation and after approximately 7 weeks of GC therapy to identify candidate biomarkers able to either predict steroid resistance before treatment or define critical molecular pathways/targets regulating steroid resistance. Results:Proteomic analyses of 15 paired NS patient samples identified 215 prevalent proteins, including 13 candidate biomarkers that predicted SRNS before GC treatment, and 66 candidate biomarkers that mechanistically differentiated steroid-sensitive NS (SSNS) from SRNS. Ingenuity Pathway Analyses and protein networking pathways approaches further identified proteins and pathways associated with SRNS. Validation using 37 NS patient samples (24 SSNS/13 SRNS) confirmed vitamin D binding protein (VDB) and APOL1 as strong predictive candidate biomarkers for SRNS, and VDB, hemopexin (HPX), adiponectin (ADIPOQ), sex hormone-binding globulin (SHBG), and APOL1 as strong candidate biomarkers to mechanistically distinguish SRNS from SSNS. Logistic regression analysis identified a candidate biomarker panel (VDB, ADIPOQ, and matrix metalloproteinase 2 [MMP-2]) with significant ability to predict SRNS at disease presentation (P = 0.003; area under the receiver operating characteristic curve = 0.78). Conclusion:Plasma proteomic analyses and immunoblotting of serial samples in childhood NS identified a candidate biomarker panel able to predict SRNS at disease presentation, as well as candidate molecular targets/pathways associated with clinical steroid resistance.
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Project description:The choice of treatment for primary nephrotic syndrome depends on the pathologic type of the disorder. Renal biopsy is necessary for a definitive diagnosis, but it is burdensome for the patients, and can be avoided if tests could be performed using urine or plasma. In this study, we analyzed 100 urinary proteins, 141 plasma proteins, and 57 urine/plasma ratios in cases of diabetic nephropathy (DN; n = 11), minimal change nephrotic syndrome (MCNS; n = 14), and membranous nephropathy (MN; n = 23). We found that the combination of urinary retinol-binding protein 4 and SH3 domain-binding glutamic acid-rich-like protein 3 could distinguish between MCNS and DN, with an area under the curve (AUC) of 0.9740. On the other hand, a selectivity index (SI) based on serotransferrin and immunoglobulin G, which is often used in clinical practice, distinguished them with an AUC of 0.9091. Similarly, the combination of urinary afamin and complement C3 urine/plasma ratio could distinguish between MN and DN with an AUC of 0.9842, while SI distinguished them with an AUC of 0.8538. Evidently, the candidates identified in this study were superior to the SI method. Thus, the aim was to test these biomarkers for accurate diagnosis and to greatly reduce the burden on patients.
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Project description:Antiphospholipid syndrome (APS) is a multisystem disorder characterized by thrombosis and/or recurrent fetal loss. This clinical phenotype heterogeneity may result in differences in response to treatment and prognosis. In this study, we aimed to identify primary thrombotic APS (TAPS) from primary obstetric APS (OAPS) using urine proteomics as a non-invasive method. Only patients with primary APS were enrolled in this study from 2016 to 2018 at a single clinical center in Shanghai. Urine samples from 15 patients with TAPS, 9 patients with OAPS, and 15 healthy controls (HCs) were collected and analyzed using isobaric tags for relative and absolute quantification (iTRAQ) labeling combined with liquid chromatography-tandem mass spectrometry analysis to identify differentially expressed proteins. Cluster analysis of urine proteomics identified differentiated proteins among the TAPS, OAPS, and HC groups. Urinary proteins were enriched in cytokine and cytokine receptor pathways. Representative secreted cytokines screened out (fold change >1.20, or <0.83, p<0.05) in these differentiated proteins were measured by enzyme-linked immunosorbent assay in a validation cohort. The results showed that the levels of C-X-C motif chemokine ligand 12 (CXCL12) were higher in the urine of patients with TAPS than in those with OAPS (p=0.035), while the levels of platelet-derived growth factor subunit B (PDGFB) were lower in patients with TAPS than in those with OAPS (p=0.041). In addition, correlation analysis showed that CXCL12 levels were positively correlated with immunoglobulin G anti-β2-glycoprotein I antibody (r=0.617, p=0.016). Our results demonstrated that urinary CXCL12 and PDGFB might serve as potential non-invasive markers to differentiate primary TAPS from primary OAPS.
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Project description:BackgroundNephrotic syndrome (NS) is a common renal disorder in children attributed to podocyte injury. However, children with the same diagnosis have markedly variable treatment responses, clinical courses, and outcomes, suggesting molecular heterogeneity.PurposeThis study aimed to explore the molecular responses of podocytes to nephrotic plasma to identify specific genes and signaling pathways differentiating various clinical NS groups as well as biological processes that drive injury in normal podocytes.MethodsTranscriptome profiles from immortalized human podocyte cell line exposed to the plasma of 8 subjects (steroidsensitive nephrotic syndrome [SSNS], n=4; steroid-resistant nephrotic syndrome [SRNS], n=2; and healthy adult individuals [control], n=2) were generated using microarray analysis.ResultsUnsupervised hierarchical clustering of global gene expression data was broadly correlated with the clinical classification of NS. Differential gene expression (DGE) analysis of diseased groups (SSNS or SRNS) versus healthy controls identified 105 genes (58 up-regulated, 47 down-regulated) in SSNS and 139 genes (78 up-regulated, 61 down-regulated) in SRNS with 55 common to SSNS and SRNS, while the rest were unique (50 in SSNS, 84 genes in SRNS). Pathway analysis of the significant (P≤0.05, -1≤ log2 FC ≥1) differentially expressed genes identified the transforming growth factor-β and Janus kinase-signal transducer and activator of transcription pathways to be involved in both SSNS and SRNS. DGE analysis of SSNS versus SRNS identified 2,350 genes with values of P≤0.05, and a heatmap of corresponding expression values of these genes in each subject showed clear differences in SSNS and SRNS.ConclusionOur study observations indicate that, although podocyte injury follows similar pathways in different clinical subgroups, the pathways are modulated differently as evidenced by the heatmap. Such transcriptome profiling with a larger cohort can stratify patients into intrinsic subtypes and provide insight into the molecular mechanisms of podocyte injury.
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