Urinary Proteome Analysis Research Articles

Proteomics Analysis of Renal Cell Line Caki-2 with AFMID Overexpression and Potential Biomarker Discovery in Urine.

Aromatic caninurine formamase (AFMID) is an enzyme involved in the tryptophan pathway, metabolizing N-formylkynurenine to kynurenine. AFMID had been found significantly downregulated in clear cell renal cell carcinoma (ccRCC) in both tissue and urine samples. Although ccRCC is characterized by a typical Warburg-like phenotype, mitochondrial dysfunction, and elevated fat deposition, it is unknown whether AFMID plays a role in tumorigenesis and the development of ccRCC. In the present study, AFMID overexpression had inhibitory effects for ccRCC cells, decreasing the rate of cell proliferation. Quantitative proteomics showed that AFMID overexpression altered cellular signaling pathways involved in cell growth and cellular metabolism pathways, including lipid metabolism and inositol phosphate metabolism. Further urine proteomic analysis indicated that cellular function dysfunction with AFMID overexpression could be reflected in the urine. The activity of predicted upregulators DDX58, TREX1, TGFB1, SMARCA4, and TNF in ccRCC cells and urine showed opposing change trends. Potential urinary biomarkers were tentatively discovered and further validated using an independent cohort. The protein panel of APOC3, UMOD, and CILP achieved an AUC value of 0.862 for the training cohort and 0.883 for the validation cohort. The present study is of significance in terms of highlighting various aspects of pathway changes associated with AFMID enzymes, discovering potential specific biomarkers for potential patient diagnosis, and therapeutic targeting.

Exploring urinary proteomics and peptidomics biomarkers for the diagnosis of mekong schistosomiasis

Schistosomiasis caused by Schistosoma mekongi is one of the causative agents of human blood fluke infection in the lower Mekong River. Traditionally, the detection of egg morphology in stool samples has served as the prevailing method for diagnosing Schistosoma infection. Nonetheless, this approach exhibits low sensitivity, particularly in early infection detection. Urine has been extensively studied as a noninvasive clinical sample for diagnosing infectious diseases. Despite this, urine proteomic analysis of S. mekongi infection has been less investigated. This study aimed to characterize proteins and peptides present in mouse urine infected with S. mekongi both before infection and at intervals of 1, 2, 4, and 8 weeks post-infection using mass spectrometry-based proteomics. Proteomics analysis revealed 13 up- and only one down-regulated mouse protein consistently found across all time points. Additionally, two S. mekongi uncharacterized proteins were detected throughout the infection period. Using a peptidomics approach, we consistently identified two peptide sequences corresponding to S. mekongi collagen alpha-1(V) in mouse urine across all time points. These findings highlight the potential of these unique proteins, particularly the S. mekongi uncharacterized proteins and collagen alpha-1(V), as potential biomarkers for early detection of S. mekongi infection. Such insights could significantly advance diagnostic strategies for human Mekong schistosomiasis.

Quantitative urinary proteome analysis reveals potential biomarkers for disease activity of Behcet’s disease uveitis

PurposeBehçet’s disease-associated uveitis (BDU) is a severe, recurrent inflammatory condition affecting the eye and is part of a systemic vasculitis with unknown etiology, making biomarker discovery essential for disease management. In this study, we intend to investigate potential urinary biomarkers to monitor the disease activity of BDU.MethodsFirstly, label-free data-dependent acquisition (DDA) and tandem mass tag (TMT)-labeled quantitative proteomics methods were used to profile the proteomes of urine from active and quiescent BDU patients, respectively. For further exploration, the remaining fifty urine samples were analyzed by a data-independent acquisition (DIA) quantitative proteomics method.ResultsTwenty-nine and 21 differential proteins were identified in the same urine from BDU patients by label-free DDA and TMT-labeled analyses, respectively. Seventy-nine differentially expressed proteins (DEPs) were significantly changed in other active BDU urine samples compared to those in quiescent BDU urine samples by IDA analysis. Gene Ontology (GO) and protein-protein interaction (PPI) analyses revealed that the DEPs were associated with multiple functions, including the immune and neutrophil activation responses. Finally, seven proteins were identified as candidate biomarkers for BDU monitoring and recurrence prediction, namely, CD38, KCRB, DPP4, FUCA2, MTPN, S100A8 and S100A9.ConclusionsOur results showed that urine can be a good source of biomarkers for BDU. These dysregulated proteins provide potential urinary biomarkers for BDU activity monitoring and provide valuable clues for the analysis of the pathogenic mechanisms of BDU.

Urine Proteomic Signatures of Mild Hypothermia Treatment in Cerebral Ischemia–Reperfusion Injury in Rats

Mild hypothermia (MH) is an effective measure to alleviate cerebral ischemia–reperfusion (I/R) injury. However, the underlying biological mechanisms remain unclear. This study set out to investigate dynamic changes in urinary proteome due to MH in rats with cerebral I/R injury and explore the neuroprotective mechanisms of MH. A Pulsinelli’s four-vessel occlusion (4-VO) rat model was used to mimic global cerebral I/R injury. Liquid chromatography-tandem mass spectrometry (LC–MS/MS) was employed to profile the urinary proteome of rats with/without MH (32 °C) treatment after I/R injury. Representative differentially expressed proteins (DEPs) associated with MH were validated by western blotting in hippocampus. A total of 597 urinary proteins were identified, among which 119 demonstrated significant changes associated with MH. Gene Ontology (GO) annotation of the DEPs revealed that MH significantly enriched in endopeptidase activity, inflammatory response, aging, response to oxidative stress and reactive oxygen species, blood coagulation, and cell adhesion. Notably, changes in 12 DEPs were significantly reversed by MH treatment. Among them, 8 differential urinary proteins were previously reported to be closely associated with brain disease, including NP, FZD1, B2M, EPCR, ATRN, MB, CA1and VPS4A. Two representative proteins (FZD1, B2M) were further validated by western blotting in the hippocampus and the results were shown to be consistent with urinary proteomic analysis. Overall, this study strengthens the idea that urinary proteome can sensitively reflect pathophysiological changes in the brain, and appears to be the first study to explore the neuroprotective effects of MH by urinary proteomic analysis. FZD1 and B2M may be involved in the most fundamental molecular biological mechanisms of MH neuroprotection.Graphical In a 4-VO rat model, 119 urinary proteins demonstrated significant changes associated with MH. MH is enriched in endopeptidase activity, inflammatory response, oxidative stress, etc, and significantly reversed changes in 12 DEPs. FZD1 and B2M are thought to be involved in the most fundamental molecular biological mechanisms of MH neuroprotection.

Identification of urine biomarkers of endometriosis-Protein mass spectrometry.

Endometriosis is a chronic inflammatory disease that leads to a series of pathological reactions. The basis is a changed proinflammatory activated immune system, which results in more pronounced oxidative stress, disturbed function of proteolysis and cell apoptosis. These processes are crucial in the development of the disease because their dysfunctional activities cause the progression of the disease. It is believed that the proteins excreted in the urine interact with each other and promote pathological processes in endometriosis. We analyzed the urine proteome of patients and aimed to detect a potential protein biomarker for endometriosis in the urine proteome. We collected urine samples from 16 patients with endometriosis and 16 patients in the control group with functional ovarian cysts. The diagnosis for all patients was confirmed through pathohistological analysis. After the preanalytical preparation of the urine, chromatography and mass spectrometry (LC-MS/MS) used the technology of urine proteome analysis. The main finding was a significantly different concentration of 14 proteins in the urine samples. We recorded a considerably higher concentration of proteins that have a significant role in activating the immune system (SELL), iron metabolism (HAMP) and cell apoptosis (CHGA) in endometriosis compared to controls. Proteins having an antioxidant function (SOD1) and a role in proteolysis of the extracellular matrix (MMP-9) were significantly reduced in endometriosis compared to controls. Consistent with the known pathogenesis of endometriosis, the study results complement the pathological responses that occur with disease progression.

An effective urobilin clearance strategy based on paramagnetic beads facilitates microscale proteomic analysis of urine.

Urine provides an ideal source for disease biomarker discovery. High-adhesion contaminants such as urobilin, which are difficult to remove from urine, can severely interfere with urinary proteomic analysis. Here, we aimed to establish a strategy based on single-pot, solid-phase-enhanced sample preparation (SP3) technology to prepare samples for urinary proteomics analysis that almost completely eliminates the impact of urobilin. A systematic evaluation of the effects of two urinary protein precipitation methods, two types of protein lysis buffers, and different ratios of magnetic digestion beads on the identification and quantification of the microscale urinary proteome was conducted. Our results indicate that methanol-chloroform precipitation, coupled with efficient lysis facilitated by urea, and subsequent enzymatic digestion using a mix of hydrophilic and hydrophobic magnetic beads offers the best performance. Further applying this strategy to the urine of patients with benign prostatic hyperplasia, prostate cancer and healthy individuals, combined with a narrow window of data-independent acquisition, FGFR4, MYLK, ORM2, GOLM1, SPP1, CD55, CSF1, DLD and TIMP3 were identified as potential biomarkers to discriminate benign prostatic hyperplasia and prostate cancer patients.

A comparative urinary proteomic and metabolomic analysis between renal aa amyloidosis and membranous nephropathy with clinicopathologic correlations

Urinary omics has become a powerful tool for elucidating pathophysiology of glomerular diseases. However, no urinary omics analysis has been performed yet on renal AA amyloidosis. Here, we performed a comparative urine proteomic and metabolomic analysis between recently diagnosed renal AA amyloidosis (AA) and membranous nephropathy (MN) patients. Urine samples of 22 (8 AA, 8 MN and 6 healthy control) patients were analyzed with nLC-MS/MS and GC/MS for proteomic and metabolomic studies, respectively. Pathological specimens were scored for glomerulosclerosis and tubulointerstitial fibrosis grades. Functional enrichment analysis between AA and control groups showed enrichment in cell adhesion related sub-domains. Uromodulin (UMOD) was lower, whereas ribonuclease 1 (RNase1) and α-1-microglobulin/bikunin precursor (AMBP) were higher in AA compared to MN group. Correlations were demonstrated between UMOD-proteinuria (r = −0.48, p = 0.03) and AMBP-eGFR (r = −0.69, p = 0.003) variables. Metabolomic analysis showed myo-inositol and urate were higher in AA compared to MN group. A positive correlation was detected between RNase1 and urate independent of eGFR values (r = 0.63, p = 0.01). Enrichment in cell adhesion related domains suggested a possible increased urinary shear stress due to amyloid fibrils. UMOD, AMBP and myo-inositol were related with tubulointerstitial damage, whereas RNase1 and urate were believed to be related with systemic inflammation in AA amyloidosis. SignificanceUrinary omics studies have become a standard tool for biomarker studies. However, no urinary omics analysis has been performed yet on renal AA amyloidosis. Here, we performed a comparative urinary omics analysis between recently diagnosed renal AA amyloidosis (AA), membranous nephropathy (MN) patients and healthy controls. Pathological specimens were scored with glomerulosclerosis (G) and tubulointerstitial fibrosis (IF) grades to consolidate the results of the omics studies and correlation analyzes. Functional enrichment analysis showed enrichment in cell adhesion related sub-domains due to downregulation of cadherins; which could be related with increased urinary shear stress due to amyloid deposition and disruption of tissue micro-architecture. In comparative proteomic analyzes UMOD was lower, whereas RNase1 and AMBP were higher in AA compared to MN group. Whereas in metabolomic analyzes; myo-inositol, urate and maltose were higher in AA compared to MN group. Correlations were demonstrated between UMOD-proteinuria (r = −0.48, p = 0.03), AMBP-eGFR (r = −0.69, p = 0.003) and between RNase1-Urate independent of eGFR values (r = 0.63, p = 0.01). This study is the first comprehensive urinary omics analysis focusing on renal AA Amyloidosis to the best of our knowledge. Based on physiologic roles and clinicopathologic correlations of the molecules; UMOD, AMBP and myo-inositol were related with tubulointerstitial damage, whereas RNase1 and urate were believed to be increased with systemic inflammation and endothelial damage in AA amyloidosis.

Urinary proteomic analysis for biomarker discovery of pulmonary arterial hypertension-induced right ventricular failure

Abstract Background Right ventricular failure (RVF) is one of the independent and strong predictors of mortality in pulmonary arterial hypertension (PAH). Urine is more suitable and sensitive for biomarker discovery with no need for homeostatic control compared to blood. Purpose The purpose of this study is to investigate candidate urinary biomarkers for RV structural and functional monitoring during PAH progression. Methods The urinary proteome of 21 monocrotaline (MCT)-induced PAH rats (8 controls, 8 of compensated RV group, 5 of decompensated RV group) were identified using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). And the differential proteins were verified by parallel reaction monitoring (PRM)-targeted quantitative proteomics. Candidate biomarkers were further validated using ELISA in the urine of PAH patients. Results In total, 1811 urinary proteins were identified with at least 1 unique peptide (FDR≤1%). Compared to the control group of rats, 118 and 184 proteins were altered in the compensated and decompensated groups, respectively, and 62 differential proteins were found between the two stages (2.0-fold change, p< 0.05). The canonical pathways revealed that complement system, glutathione metabolism and iron homeostasis were enriched in the compensated stage, while interferon signaling, fibrosis, Wnt signaling and epithelial-mesenchymal transition were enriched in the failing stage. Four proteins confirmed by PRM, which were also of good discrimination ability of two RV stages were selected for further validation. ELISA results of the urine of PAH patients showed that IL18BP, IFNABR, LGALS3BP and α2-AP were sequentially elevated as disease progressed. Correlation analysis with clinical indicators showed that these proteins were positively correlated with right atrial pressure and right heart dilation, and negatively correlated with cardiac index and tricuspid annular plane systolic excursion. The combination of these four proteins panel could significantly distinguish PAH patients from healthy controls (AUC=0.985, 95%CI 0.955-1) and performs well in distinguishing high-risk PAH patients from low-risk ones (AUC=0.922, 95%CI 0.807-1). Conclusions Novel RVF candidate urinary biomarkers were found through in-depth proteomic analysis of PAH rat model. The panel of these four proteins, which were significantly correlated with RV structural remodeling and systolic function, showed good performance in diagnosis and risk stratification of PAH patients.Figure 1.Study workflowFigure 1.Main results of the study

Urine proteomic analysis of the rat e-cigarette model.

We were curious if the urinary proteome could reflect the effects of e-cigarettes on the organism. Urine samples were collected from a rat e-cigarette model before, during, and after two weeks of e-cigarette smoking. Urine proteomes before and after smoking of each rat were compared individually, while the control group was set up to rule out differences caused by rat growth and development. Fetuin-B, a biomarker of chronic obstructive pulmonary disease (COPD), and annexin A2, which is recognized as a multiple tumour marker, were identified as differential proteins in five out of six smoking rats on day 3. To our surprise, odourant-binding proteins expressed in the olfactory epithelium were also found and were significantly upregulated. Pathways enriched by the differential proteins include the apelin signalling pathway, folate biosynthesis pathway, arachidonic acid metabolism, chemical carcinogenesis-DNA adducts and chemical carcinogenesis-reactive oxygen species. They have been reported to be associated with immune system, cardiovascular system, respiratory system, etc. Urinary proteome could reflect the effects of e-cigarettes in rats.

#4952 CLINICOPATHOLOGIC CORRELATIONS OF URINARY PROTEOMIC AND METABOLOMIC ANALYSIS IN PATIENTS WITH RENAL AA AMYLOIDOSIS AND MEMBRANOUS NEPHROPATHY

Abstract Background and Aims AA Amyloidosis is a multisystemic amyloidosis subtype that develops on the background of various chronic inflammatory etiologies. Urinary omics studies have become a promising tool for elucidating pathophysiology and prognosis of glomerular diseases. However, no urinary omics analysis has been performed focusing on renal AA amyloidosis in literature to the best of our knowledge. Our main aim in this study is to perform a comparative urine proteomic and metabolomic analysis of recently diagnosed renal AA amyloidosis and to investigate the correlation of bioinformatic results with clinical and pathological data. Method Urine samples of 8 recently diagnosed AA amyloidosis (AA), 8 membranous nephropathy (MN) and 6 healthy control group patients were collected before kidney biopsy procedure. Proteomic analyzes were performed with nLC/Q-TOF MS/MS and metabolomic analyzes were performed by GC/MS in all patients. Biopsy specimens were scored according to glomerulosclerosis (G), tubular atrophy (TA) and interstitial fibrosis (IF) grades by two pathologists. Raw spectroscopic data was analyzed using MaxQuant and MS-DIAL programs for proteomic and metabolomic studies, respectively. Statistical analysis of the differences in molecules between study groups were performed with ANOVA and HSD-Tukey tests. Principal component (PCA) and heatmap analyzes were made in R language, while gene ontology (GO), network and functional enrichment analysis of bioinformatic results were performed with PANTHER, STRING and MetaboAnalyst databases. Results In comparison between AA and MN groups, median eGFR values tend to be lower in the AA group (67.6 vs 112 ml/min/1.73 m2 respectively, p = 0.08). Median 24-hour urine protein levels did not show statistically significant difference (9499 vs 9512 mg/day respectively, p = 0.9). Percentage of patients with moderate/severe IF/TA was higher and G score was tend to be in AA group compared to MN group (p values 0.02 and 0.07 for IF/TA and G scores, respectively). As a result of proteomic analysis, a total of 859 proteins were determined. Statistical analysis showed 51 proteins that were significantly differ in AA group compared to the control group. GO and functional enrichment analyzes showed that statistically most significant sub-domains were mainly related with cell-cell adhesion (Figure 1 & 2). In comparative analysis between AA and MN patients, uromodulin (UMOD) was lower in the AA group than in the MN group (log2FC -3.37), whereas ribonuclease 1 (RNASE1) and α-1-microglobulin/bikunin precursor protein (AMBP) were higher in the AA group (log2FC 3.41 and 3.07, respectively). In Spearman correlation analyzes, significant negative correlations were demonstrated between UMOD-proteinuria (r = -0.48, p = 0.03) and between AMBP-eGFR (r = -0.69, p = 0.003) variables. Metabolomic analysis showed 9 metabolites that were significantly different between AA and other study groups. Myo-inositol and urate were higher in AA group compared to MN group, while D-mannitol and N-acetylglutamate were higher in AA group compared to the control group. Significant positive correlation independent of GFR was detected between RNASE1 and urate (r = 0.63, p = 0.01). Conclusion Our study is the first urinary comparative omics analysis performed on renal AA amyloidosis patients to the best of our knowledge. We demonstrated specific protein and metabolites that distinguish AA group from the control and MN groups. Enrichment and GO analyzes between AA and the control group showed a negative enrichment in cell-cell adhesion related sub-domains, suggesting a possible increased urinary shear stress resulting in downregulation of cadherins in AA amyloidosis. In comparative analysis between AA and MN groups, UMOD and AMBP proteins and myo-inositol were thought to be associated with high tubulointerstitial damage, whereas RNASE1 and urate were believed to be related with systemic inflammation and endothelial damage [1].

PREDICTION OF CORONARY ARTERY DISEASE USING URINARY PROTEOMICS

Objective: Coronary artery disease (CAD) is multifactorial, caused by complex pathophysiology, and contributes to a high burden of mortality worldwide. Urinary proteomic analyses may help to identify predictive biomarkers and provide insights into the pathogenesis of CAD. Design and method: Urinary proteome was analyzed in 965 participants using capillary electrophoresis coupled with mass spectrometry. A proteomic classifier was developed in a discovery cohort with 36 individuals with CAD and 36 matched controls using the support vector machine. The classifier was tested in a validation cohort with 115 individuals who progressed to CAD and 778 controls and compared with a previously developed CAD-associated classifier, ACSP75. The Framingham risk score was available in 737 participants. Bioinformatics analysis was performed based on the CAD-associated peptides. Results: The novel proteomic classifier was comprised of 160 urinary peptides, mainly related to collagen turnover, lipid metabolism, and inflammation. In the validation cohort, the classifier provided an AUC of 0.82 (95% CI: 0.78-0.87) for the CAD prediction in 8 years, superior to ACSP75 (AUC: 0.53, 95% CI: 0.47-0.60). On top of ACSP75, the addition of the novel classifier improved the AUC to 0.84 (95% CI: 0.80-0.89). In a multivariable Cox model, a 1-SD increment in the novel classifier was associated with CAD (HR: 1.54, 95% CI: 1.26-1.89, P<0.0001) higher risk of CAD. The new classifier further improved the risk reclassification of CAD on top of the Framingham risk score (net reclassification index: 0.61, 95% CI: 0.25-0.95, P = 0.001). Conclusions: A novel urinary proteomic classifier related to collagen metabolism, lipids, and inflammation showed potential for the risk prediction of CAD. Urinary proteome provides an alternative approach to personalized prevention.

Identification of novel urine proteomic biomarkers for high stamina in high-altitude adaptation.

Introduction: We aimed to identify urine biomarkers for screening individuals with adaptability to high-altitude hypoxia with high stamina levels. Although most non-high-altitude natives experience rapid decline in physical ability when ascending to high altitudes, some individuals with high-altitude adaptability continue to maintain high endurance levels. Methods: We divided the study population into two groups: the LC group (low change in endurance from low to high altitude) and HC group (high change in endurance from low to high altitude). We performed blood biochemistry testing for individuals at high altitudes and sea level. We used urine peptidome profiling to compare the HH (high-altitude with high stamina) and HL (high-altitude with low stamina) groups and the LC and HC groups to identify urine biomarkers. Results: Routine blood tests revealed that the concentration of white blood cells, lymphocytes and platelets were significantly higher in the HH group than in the HL group. Urine peptidome profiling showed that the proteins ITIH1, PDCD1LG2, NME1-NME2, and CSPG4 were significantly differentially expressed between the HH and HL groups, which was tested using ELISA. Urine proteomic analysis showed that LRG1, NID1, VASN, GPX3, ACP2, and PRSS8 were urine proteomic biomarkers of high stamina during high-altitude adaptation. Conclusion: This study provides a novel approach for identifying potential biomarkers for screening individuals who can adapt to high altitudes with high stamina.

Targeted MRM Quantification of Urinary Proteins in Chronic Kidney Disease Caused by Glomerulopathies.

Glomerulopathies with nephrotic syndrome that are resistant to therapy often progress to end-stage chronic kidney disease (CKD) and require timely and accurate diagnosis. Targeted quantitative urine proteome analysis by mass spectrometry (MS) with multiple-reaction monitoring (MRM) is a promising tool for early CKD diagnostics that could replace the invasive biopsy procedure. However, there are few studies regarding the development of highly multiplexed MRM assays for urine proteome analysis, and the two MRM assays for urine proteomics described so far demonstrate very low consistency. Thus, the further development of targeted urine proteome assays for CKD is actual task. Herein, a BAK270 MRM assay previously validated for blood plasma protein analysis was adapted for urine-targeted proteomics. Because proteinuria associated with renal impairment is usually associated with an increased diversity of plasma proteins being present in urine, the use of this panel was appropriate. Another advantage of the BAK270 MRM assay is that it includes 35 potential CKD markers described previously. Targeted LC-MRM MS analysis was performed for 69 urine samples from 46 CKD patients and 23 healthy controls, revealing 138 proteins that were found in ≥2/3 of the samples from at least one of the groups. The results obtained confirm 31 previously proposed CKD markers. Combination of MRM analysis with machine learning for data processing was performed. As a result, a highly accurate classifier was developed (AUC = 0.99) that enables distinguishing between mild and severe glomerulopathies based on the assessment of only three urine proteins (GPX3, PLMN, and A1AT or SHBG).

Prediction of coronary artery disease using urinary proteomics.

Coronary artery disease (CAD) is multifactorial, caused by complex pathophysiology, and contributes to a high burden of mortality worldwide. Urinary proteomic analyses may help to identify predictive biomarkers and provide insights into the pathogenesis of CAD. Urinary proteome was analysed in 965 participants using capillary electrophoresis coupled with mass spectrometry. A proteomic classifier was developed in a discovery cohort with 36 individuals with CAD and 36 matched controls using the support vector machine. The classifier was tested in a validation cohort with 115 individuals who progressed to CAD and 778 controls and compared with two previously developed CAD-associated classifiers, CAD238 and ACSP75. The Framingham and SCORE2 risk scores were available in 737 participants. Bioinformatic analysis was performed based on the CAD-associated peptides. The novel proteomic classifier was comprised of 160 urinary peptides, mainly related to collagen turnover, lipid metabolism, and inflammation. In the validation cohort, the classifier provided an area under the receiver operating characteristic curve (AUC) of 0.82 [95% confidence interval (CI): 0.78-0.87] for the CAD prediction in 8 years, superior to CAD238 (AUC: 0.71, 95% CI: 0.66-0.77) and ACSP75 (AUC: 0.53 and 95% CI: 0.47-0.60). On top of CAD238 and ACSP75, the addition of the novel classifier improved the AUC to 0.84 (95% CI: 0.80-0.89). In a multivariable Cox model, a 1-SD increment in the novel classifier was associated with a higher risk of CAD (HR: 1.54, 95% CI: 1.26-1.89, P < 0.0001). The new classifier further improved the risk reclassification of CAD on top of the Framingham or SCORE2 risk scores (net reclassification index: 0.61, 95% CI: 0.25-0.95, P = 0.001; 0.64, 95% CI: 0.28-0.98, P = 0.001, correspondingly). A novel urinary proteomic classifier related to collagen metabolism, lipids, and inflammation showed potential for the risk prediction of CAD. Urinary proteome provides an alternative approach to personalized prevention.

A randomised study of rituximab and belimumab sequential therapy in PR3 ANCA-associated vasculitis (COMBIVAS): design of the study protocol

BackgroundSequential B cell-targeted immunotherapy with BAFF antagonism (belimumab) and B cell depletion (rituximab) may enhance B cell targeting in ANCA-associated vasculitis (AAV) through several mechanisms.MethodsStudy design: COMBIVAS is a randomised, double-blind, placebo-controlled trial designed to assess the mechanistic effects of sequential therapy of belimumab and rituximab in patients with active PR3 AAV. The recruitment target is 30 patients who meet the criteria for inclusion in the per-protocol analysis. Thirty-six participants have been randomised to one of the two treatment groups in a 1:1 ratio: either rituximab plus belimumab or rituximab plus placebo (both groups with the same tapering corticosteroid regimen), and recruitment is now closed (final patient enrolled April 2021). For each patient, the trial will last for 2 years comprising a 12-month treatment period followed by a 12-month follow-up period.Participants: Participants have been recruited from five of seven UK trial sites. Eligibility criteria were age ≥ 18 years and a diagnosis of AAV with active disease (newly diagnosed or relapsing disease), along with a concurrent positive test for PR3 ANCA by ELISA.Interventions: Rituximab 1000 mg was administered by intravenous infusions on day 8 and day 22. Weekly subcutaneous injections of 200 mg belimumab or placebo were initiated a week before rituximab on day 1 and then weekly through to week 51. All participants received a relatively low prednisolone (20 mg/day) starting dose from day 1 followed by a protocol-specified corticosteroid taper aiming for complete cessation by 3 months.Outcomes: The primary endpoint of this study is time to PR3 ANCA negativity. Key secondary outcomes include change from baseline in naïve, transitional, memory, plasmablast B cell subsets (by flow cytometry) in the blood at months 3, 12, 18 and 24; time to clinical remission; time to relapse; and incidence of serious adverse events. Exploratory biomarker assessments include assessment of B cell receptor clonality, B cell and T cell functional assays, whole blood transcriptomic analysis and urinary lymphocyte and proteomic analysis. Inguinal lymph node and nasal mucosal biopsies have been performed on a subgroup of patients at baseline and month 3.DiscussionThis experimental medicine study provides a unique opportunity to gain detailed insights into the immunological mechanisms of belimumab-rituximab sequential therapy across multiple body compartments in the setting of AAV.Trial registrationClinicalTrials.gov NCT03967925. Registered on May 30, 2019.

Differential Urinary Proteomic Analysis of High-Risk Cervical Intraepithelial Neoplasia.

Human papillomavirus (HPV)-associated lesions and malignancies exhibit alterations in the composition and functionality of the extracellular matrix (ECM) that represent the complex molecular pathways present between infection and disease. A total of 20 urine samples were used, including from 10 patients with cervical intraepithelial neoplasia grade 3 (CIN3) and 10 healthy controls to perform the label-free quantitative analysis using the nano-HPLC and ESI-MS ion trap mass analyzer and matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF/MS) fast screening. Among 476 identified/quantified proteins, 48 were significantly changed (log2-fold change ≥1.0 or ≤-1.0, -log10 (bbinominal, p-value ≥ 1.3), of which were 40 proteins (down-regulated) and 8 proteins (up-regulated) in CIN3, in comparison to healthy controls. The biological function and key pathway enrichment of the gene set using gen set enrichment analysis (GSEA) were analyzed. The ECM-receptor interaction pathway (NES = -1.64, p = 0.026) was down-regulated by 13 proteins (HSPG2, COL6A1, COL6A3, SPP1, THBS1, TNC, DAG1, FN1, COMP, GP6, VTN, SDC1, and CD44; log2 FC range from -0.03 to -1.48) for the CIN3 group in the KEGG database. The MALDI-TOF/MS screening showed the difference of protein profiles between the control and CIN3 groups, i.e., using the scatter plot with a well-separated shape, as well as effectively distinguishing both groups (control and CIN3) using genetic algorithms (GA) with cross-validation (51.56%) and recognition capability (95.0%). Decreased levels of ECM-receptor interaction proteins may cause disturbances in the interactions of cells with the ECM and play an important role in the development and progression of cervical cancer.

Pathway-guided monitoring of the disease course in bladder cancer with longitudinal urine proteomics

BackgroundMonitoring bladder cancer over time requires invasive and costly procedures. Less invasive approaches are required using readily available biological samples such as urine. In this study, we demonstrate a method for longitudinal analysis of the urine proteome to monitor the disease course in patients with bladder cancer.MethodsWe compared the urine proteomes of patients who experienced recurrence and/or progression (n = 13) with those who did not (n = 17). We identified differentially expressed proteins within various pathways related to the hallmarks of cancer. The variation of such pathways during the disease course was determined using our differential personal pathway index (dPPi) calculation, which could indicate disease progression and the need for medical intervention.ResultsSeven hallmark pathways are used to develop the dPPi. We demonstrate that we can successfully longitudinally monitor the disease course in bladder cancer patients through a combination of urine proteomic analysis and the dPPi calculation, over a period of 62 months.ConclusionsUsing the information contained in the patient’s urinary proteome, the dPPi reflects the individual’s course of bladder cancer, and helps to optimise the use of more invasive procedures such as cystoscopy.

Urinary proteome analysis of acute kidney injury in post-cardiac surgery patients using enrichment materials with high-resolution mass spectrometry.

Background: Cardiac surgery-associated acute kidney injury (CSA-AKI) may increase the mortality and incidence rates of chronic kidney disease in critically ill patients. This study aimed to investigate the underlying correlations between urinary proteomic changes and CSA-AKI. Methods: Nontargeted proteomics was performed using nano liquid chromatography coupled with Orbitrap Exploris mass spectrometry (MS) on urinary samples preoperatively and postoperatively collected from patients with CSA-AKI. Gemini C18 silica microspheres were used to separate and enrich trypsin-hydrolysed peptides under basic mobile phase conditions. Differential analysis was conducted to screen out urinary differential expressed proteins (DEPs) among patients with CSA-AKI for bioinformatics. Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis was adopted to identify the altered signal pathways associated with CSA-AKI. Results: Approximately 2000 urinary proteins were identified and quantified through data-independent acquisition MS, and 324 DEPs associated with AKI were screened by univariate statistics. According to KEGG enrichment analysis, the signal pathway of protein processing in the endoplasmic reticulum was enriched as the most up-regulated DEPs, and cell adhesion molecules were enriched as the most down-regulated DEPs. In protein–protein interaction analysis, the three hub targets in the up-regulated DEPs were α-1-antitrypsin, β-2-microglobulin and angiotensinogen, and the three key down-regulated DEPs were growth arrest-specific protein 6, matrix metalloproteinase-9 and urokinase-type plasminogen activator. Conclusion: Urinary protein disorder was observed in CSA-AKI due to ischaemia and reperfusion. The application of Gemini C18 silica microspheres can improve the protein identification rate to obtain highly valuable resources for the urinary DEPs of AKI. This work provides valuable knowledge about urinary proteome biomarkers and essential resources for further research on AKI.

Urinary Proteome Analysis of Global Cerebral Ischemia–Reperfusion Injury Rat Model via Data-Independent Acquisition and Parallel Reaction Monitoring Proteomics

Cerebral ischemia–reperfusion (I/R) injury is the leading cause of death in severe hypotension caused by cardiac arrest, drowning, and excessive blood loss. Urine can sensitively reflect pathophysiological changes in the brain even at an early stage. In this study, a rat model of global cerebral I/R injury was established via Pulsinelli’s four-vessel occlusion (4-VO) method. Overall, 164 urinary proteins significantly changed in the 4-VO rat urine samples compared to the control samples by data-independent acquisition (DIA) proteomics technique (1.5-fold change, p < 0.05). Gene Ontology annotation showed that the acute-phase response, the ERK1 and ERK2 cascade, endopeptidase activity, blood coagulation, and angiogenesis were overrepresented. After parallel reaction monitoring (PRM) validation, 15 differential proteins having human orthologs were verified as the potential urinary markers associated with cerebral I/R injury. Of these potential biomarkers, 8 proteins were reported to be closely associated with cerebral I/R injury. Nine differential proteins changed even when there were no clinical manifestations or histopathological cerebral damage, including FGG, COMP, TFF2, HG2A, KNG1, CATZ, PTGDS, PRVA, and HEPC. These 9 proteins are potential biomarkers for early screening of cerebral I/R injury to prevent the development of cerebral injury. KNG1, CATZ, PTGDS, PRVA, and HEPC showed an overall trend of upregulation or downregulation at 12 and 48 h after I/R injury, reflecting the progression of cerebral I/R injury. These 5 proteins may serve as potential biomarkers for prognostic evaluation of cerebral I/R injury. These findings provide important clues to inform the monitoring of cerebral I/R injury and further the current understanding of its molecular biological mechanisms.

Urinary proteomic analysis during pregnancy and its potential application in early prediction of gestational diabetes mellitus and spontaneous abortion.

BackgroundThe maternal physiological changes which occur during gestation are complex and affect diverse systems in the body. Elucidating the various changes that occur during pregnancy may assist with understanding maternal health and the factors affecting pregnancy outcomes.MethodsA longitudinal cohort of 84 pregnant women was established. The urinary proteomes of women in different trimesters of pregnancy (6–8, 22–24, and 32–34 weeks) were characterized using data-independent acquisition tandem mass spectrometry. Gestational diabetes mellitus (GDM) was diagnosed at 24 to 28 weeks. Functional analysis of serial changed proteins was performed.ResultsFifteen women had GDM, 50 were healthy, and 19 experienced spontaneous abortion (SA). Functional analysis showed that the urinary proteome reflected physiological and pathological changes during pregnancy. Compared to those of women with a normal pregnancy, the urinary proteomes of women with GDM and SA showed significant disease-related changes in insulin secretion and estrogen receptor activity, respectively, during the first trimester. Urinary protein during the first trimester of pregnancy achieved an area under the curve of 0.91 and 0.81 for GDM and SA, respectively.ConclusionsThe urinary proteome has the potential to reflect serial changes of pregnancy progression; therefore, its use might facilitate early diagnosis of pregnancy complications.