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Recent evidence has shown that proteins in normal human urine can inhibit calcium oxalate (CaOx) kidney stone formation. Herein, we performed fast protein liquid chromatography (FPLC) to fractionate normal human urinary proteins using anion-exchange (DEAE) and size-exclusion (Superdex 200) materials. FPLC fractions (F1-F15) were examined by CaOx crystallization, growth, aggregation and crystal-cell adhesion assays. The fractions with potent inhibitory activities against CaOx crystals were then subjected to mass spectrometric protein identification. The data revealed that 13 of 15 fractions showed inhibitory activities in at least one crystal assay. Integrating CaOx inhibitory scores demonstrated that F6, F7 and F8 had the most potent inhibitory activities. NanoLC-ESI-Qq-TOF MS/MS identified 105, 93 and 53 proteins in F6, F7 and F8, respectively. Among them, 60 were found in at least two fractions and/or listed among known inhibitors with solid experimental evidence in the StoneMod database (https://www.stonemod.org). Interestingly, 10 of these 60 potential inhibitors have been reported with lower urinary levels in CaOx stone formers compared with healthy (non-stone) individuals, strengthening their roles as potent CaOx stone inhibitors. Our study provides the largest dataset of potential CaOx stone inhibitory proteins that will be useful for further elucidations of stone-forming mechanisms and ultimately for therapeutic/preventive applications.

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Bladder cancer (BCa) is the predominant malignancy of the urinary system. Herein, a comprehensive urine proteomic feature was initially established for the noninvasive diagnosis and recurrence monitoring of bladder cancer. 279 cases (63 primary BCa, 87 nontumor controls (NT), 73 relapsed BCa (BCR), and 56 nonrelapsed BCa (BCNR)) were collected to screen urinary protein biomarkers. 4761 and 3668 proteins were qualified and quantified by DDA and sequential window acquisition of all theoretical mass spectra (SWATH-MS) analysis in two discovery sets, respectively. Upregulated proteins were validated by multiple reaction monitoring (MRM) in two independent combined sets. Using the multi-support vector machine-recursive feature elimination (mSVM-RFE) algorithm, a model comprising 13 proteins exhibited good performance between BCa and NT with an AUC of 0.821 (95% CI: 0.675-0.967), 90.9% sensitivity (95% CI: 72.7-100%), and 73.3% specificity (95% CI: 53.3-93.3%) in the diagnosis test set. Meanwhile, an 11-marker classifier significantly distinguished BCR from BCNR with 75.0% sensitivity (95% CI: 50.0-100%), 81.8% specificity (95% CI: 54.5-100%), and an AUC of 0.784 (95% CI: 0.609-0.959) in the test cohort for relapse surveillance. Notably, six proteins (SPR, AK1, CD2AP, ADGRF1, GMPS, and C8A) of 24 markers were newly reported. This paper reveals novel urinary protein biomarkers for BCa and offers new theoretical insights into the pathogenesis of bladder cancer (data identifier PXD044896).

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PURPOSE: T1 bladder cancer is known for its high progression and recurrence rates. Identifying aggressive tumours at the non-muscle-invasive stage is crucial to allow early interventions and subsequently increase patient survival. This study aimed to investigate the potential of the cubilin/myeloperoxidase (CUBN/MPO) ratio as a high-grade T1 bladder cancer biomarker. METHODS: Urine samples were collected from 30 patients who underwent transurethral resection of the tumour with high-grade T1 bladder cancer (June 2015 to December 2019) before surgery. The urinary proteome was analysed using high-resolution mass spectrometry and the CUBN/MPO ratio was calculated. The primary outcome was the recurrence during the follow-up (around 31.5 months after resection). Univariate Cox regression and Kaplan-Meier curves were used for data analysis. RESULTS: Patients with a low CUBN/MPO ratio exhibited upregulated MPO and/or downregulated CUBN. This group of patients had a higher incidence of disease recurrence and progression. Low CUBN/MPO ratio was significantly associated with a higher likelihood of recurrence, progression, and death. It is worth noting that this study was exploratory and conducted on a small sample size, so further research is needed to validate these findings in larger cohorts. CONCLUSION: This study highlights the potential of the CUBN/MPO ratio as a prognostic biomarker for high-grade T1 bladder cancer.

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BACKGROUND: Focal segmental glomerulosclerosis (FSGS) is a primary podocytopathy characterized by primary podocyte detection and high proteinuria. The search for biomarkers and factors associated with the progression of this disease is an important task nowdays. AIM: To assess the proteomic profile of urine in patients with FSGS and to isolate urinary biomarkers of podocytopathies. MATERIALS AND METHODS: The study included 41 patients diagnosed with chronic glomerulonephritis, 27 men and 14 women. According to the morphological study, 28 patients were diagnosed with FSGS, 9 with steroid-sensitive nephrotic syndrome and 14 with steroid-resistant nephrotic syndrome. The comparison group included 13 patients with membranous nephropathy. The study of the urinary proteome was carried out by targeted liquid chromatography-mass spectrometry using multiple reaction monitoring with synthetic stable isotope labelled peptide standards. RESULTS: The main differences in the protein profile of urine were found in the subgroups of steroid-sensitive (SS) and steroid-resistant (SR) FSGS. In the FSGS SR group, at the onset of the disease, there was a high concentration of proteins reflecting damage to the glomerular filter (apo-lipoprotein A-IV, orosomucoid, cadherin, hemopexin, vitronectin), as well as proteins associated with tubulo-interstitial inflammation and accumulation of extracellular matrix (retinol- and vitamin D-binding proteins, kininogen-1, lumican and neurophilin-2). Compared with the membranous nephropathy group, FSGS patients had significantly higher urinary concentrations of carnosinase, orosomucoid, cadherin-13, tenascin X, osteopontin, and zinc-alpha-2-glycoprotein. CONCLUSION: Thus, in patients with SR FSGS, the proteomic profile of urine includes more proteins at elevated concentrations, which reflects severe damage to various parts of the nephron compared with patients with SS FSGS and membranous nephropathy.

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It is widely accepted that circadian rhythm disruption caused short- or long-term adverse effects on health. Although many previous studies have focused on exploration of the molecular mechanisms, there is no rapid, convenient, and non-invasive method to reveal the influence on health after circadian rhythm disruption. Here, we performed a high-resolution mass spectrometry-based data-independent acquisition (DIA) quantitative urinary proteomic approach in order to explore whether urine could reveal stress changes to those brought about by circadian rhythm disruption after sleep deprivation. After sleep deprivation, the subjects showed a significant increase in both systolic and diastolic blood pressure compared with routine sleep. More than 2000 proteins were quantified and they contained specific proteins for various organs throughout the body. And a total of 177 significantly up-regulated proteins and 68 significantly down-regulated proteins were obtained after sleep deprivation. These differentially expressed proteins (DEPs) were associated with multiple organs and pathways, which reflected widespread influences of sleep deprivation. Besides, machine learning identified a panel of five DEPs (CD300A, SCAMP3, TXN2, EFEMP1, and MYH11) that can effectively discriminate circadian rhythm disruption. Taken together, our results validate the value of urinary proteome in predicting and diagnosing the changes by circadian rhythm disruption.

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Diabetic kidney disease (DKD) is a major microvascular complication of type 2 diabetes mellitus (T2DM). Monitoring the early diagnostic period and disease progression plays a crucial role in treating DKD. In this study, to comprehensively elucidate the molecular characteristics of urinary proteins and urinary exosome proteins in type 2 DKD, we performed large-scale urinary proteomics (n=144) and urinary exosome proteomics (n=44) analyses on T2DM patients with albuminuria in varying degrees. The dynamics analysis of the urinary and exosome proteomes in our study provides a valuable resource for discovering potential urinary biomarkers in patients with DKD. A series of potential biomarkers, such as SERPINA1 and transferrin (TF), were detected and validated to be used for DKD diagnosis or disease monitoring. The results of our study comprehensively elucidated the changes in the urinary proteome and revealed several potential biomarkers reflecting the progression of DKD, which provide a reference for DKD biomarker screening.

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The objective of our study was to search for survival biomarkers (SB) and treatment response monitoring biomarkers (TRMB) in the urinary proteome of dogs with renal disease secondary to canine leishmaniosis (CanL), using UHPLC-MS/MS. The proteomic data are available via ProteomeXchange with identifier PXD042578. Initially, a group of 12 dogs was evaluated and divided into survivors (SG; n = 6) and nonsurvivors (NSG; n = 6). A total of 972 proteins were obtained from the evaluated samples. Then, bioinformatic analysis reduced them to 6 proteins like potential SB increased in the NSG, specifically, Haemoglobin subunit Alpha 1, Complement Factor I, Complement C5, Fibrinogen beta chain (fragment), Peptidase S1 domain-containing protein, and Fibrinogen gamma chain. Afterwards, SG was used to search for TRMB, studying their urine at 0, 30, and 90 days, and 9 proteins that decreased after treatment were obtained: Apolipoprotein E, Cathepsin B, Cystatin B, Cystatin-C-like, Lysozyme, Monocyte differentiation CD14, Pancreatitis-associated precursor protein, Profilin, and Protein FAM3C. Finally, enrichment analysis provided information about the biological mechanisms in which these proteins are involved. In conclusion, this study provides 15 new candidate urinary biomarkers and an improved understanding of the pathogenesis of kidney disease in CanL.

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To date, studies of development have mainly focused on the embryonic stage and a short time thereafter. There has been little research on the whole life of an individual from childhood to aging and death. For the first time, we used noninvasive urinary proteome technology to track changes in several important developmental time points in a group of rats, covering 10 time points from childhood, adolescence, young adulthood, middle adulthood, and near-death in old age. Similar to previous studies on puberty, proteins were detected and they are involved in sexual or reproductive maturation, mature spermatozoa in seminiferous tubules (first seen), gonadal hormones, decline of estradiol, brain growth, and central nervous system myelination, and our differential protein enrichment pathways also included reproductive system development, tube development, response to hormone, response to estradiol, brain development, and neuron development. Similar to previous studies in young adults, proteins were detected and they are involved in musculoskeletal maturity, peak bone mass, development of the immune system, and growth and physical development, and our differential proteins enrichment pathways also included skeletal system development, bone regeneration, system development, immune system processes, myeloid leukocyte differentiation, and developmental growth. Studies on aging-related changes in neurons and neurogenesis have been reported, and we also found relevant pathways in aged rats, such as regulation of neuronal synaptic plasticity and positive regulation of long-term neuronal synaptic plasticity. However, at all time points throughout life, there were many biological pathways revealed by differential urinary protein enrichment involving multiple organs, tissues, systems, etc. that have not been mentioned in existing studies. This study shows comprehensive and detailed changes in rat lifetime development through the urinary proteome, helping to fill the gap in development research. Moreover, it provides a new approach to monitoring changes in human health and diseases of aging using the urinary proteome.

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Cardiovascular disease is currently the leading cause of death worldwide. Atherosclerosis is an important pathological basis of cardiovascular disease, and its early diagnosis is of great significance. Urine bears no need nor mechanism to be stable, so it accumulates many small changes and is therefore a good source of biomarkers in the early stages of disease. In this study, ApoE-/- mice were fed a high-fat diet for 5 months. Urine samples from the experimental group and control group (C57BL/6 mice fed a normal diet) were collected at seven time points. Proteomic analysis was used for comparison within the experimental group and for comparison between the experimental group and the control group. The results of the comparison within the experimental group showed a significant difference in the urinary proteome before and after a one-week high-fat diet, and several of the differential proteins have been reported to be associated with atherosclerosis and/or as biomarker candidates. The results of the comparison between the experimental group and the control group indicated that the biological processes enriched by the GO analysis of the differential proteins correspond to the progression of atherosclerosis. The differences in chemical modifications of urinary proteins have also been reported to be associated with the disease. This study demonstrates that urinary proteomics has the potential to sensitively monitor changes in the body and provides the possibility of identifying early biomarkers of atherosclerosis.

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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, ß-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.

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BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory airway disease caused by inhalation of cigarette smoke (CS) and other harmful gases and particles. METHODS: This study aimed to explore potential urinary biomarkers for CS-induced COPD based on LC-MS/MS analysis. RESULTS: A total of 340 urinary proteins were identified, of which 79 were significantly changed (30, 31, and 37 at week 2, 4 and 8, respectively). GO annotation of the differential urinary proteins revealed that acute-phase response, response to organic cyclic compounds, complement activation classical pathway, and response to lead ion were significantly enriched at week 2 and 4. Another four processes were only enriched at week 8, namely response to oxidative stress, positive regulation of cell proliferation, thyroid hormone generation, and positive regulation of apoptotic process. The PPI network indicated that these differential proteins were biologically connected in CS-exposed rats. Of the 79 differential proteins in CS-exposed rats, 56 had human orthologs. Seven proteins that had changed at week 2 and 4 when there were no changes of pulmonary function and pathological morphology were verified as potential biomarkers for early screening of CS-induced COPD by proteomic analysis. Another six proteins that changed at week 8 when obvious airflow obstruction was detected were verified as potential biomarkers for prognostic assessment of CS-induced COPD. CONCLUSIONS: These results reveal that the urinary proteome could sensitively reflect pathological changes in CS-exposed rats, and provide valuable clues for exploring COPD biomarkers.

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Mass spectrometry (MS)-based urinary proteomics is increasingly used for clinical research. A critical step in urinary proteomic analysis comprises the implementation of a reliable sample preparation method with high yields of peptides and proteins. In this study, we developed a urinary sample preparation method, DRA-Urine (Direct reduction/alkylation in urine), which urinary proteins were directly reduced/alkylated in urine, and then precipitated by acetone, washed and digestion on an ultrafilter unit. The qualitative and quantitative comparison of different urinary sample preparation methods (in-solution methods and ultrafilter-assisted methods) showed that DRA-Urine could achieve better results. Adapting DRA-Urine protocol to a 96-well format, namely 96DRA-Urine, shortened the time for buffer change and improved sample preparation throughput. The results showed that 96DRA-Urine displayed similar proteomic performance to DRA-Urine. Finally, the 96DRA-Urine method was used in a label-free, small pilot biomarker discovery analysis for differential urinary proteome analysisof bladder cancer urine. The results showed that urinary proteins could differentiate bladder cancer (BCa) patients from healthy controls and distinguish high-grade BCa from low-grade BCa with area under the curve (AUC) values of 0.972 and 0.847, respectively. Consequently, the 96DRA-Urine method might be a high-throughput method for preparing body fluid samples used in clinical research but needs to be further verified.

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Pregnancy involves a significant number of physiological changes. A normal pregnancy is essential to ensure healthy maternal and fetal development. We sought to explore whether the urinary proteome could reflect the pregnancy process. Urine samples were collected from pregnant and control rats on various gestational days. The urinary proteome was profiled by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), and differential proteins were obtained by comparing to the gestational day 1 of the same group at each time point. Many pathways related to embryo implantation and trophoblast differentiation were enriched in the early days in urine. Liver, kidney, and bone development started early to be enriched in the pregnant group, but not in the control group. Interestingly, the developmental processes of the fetal heart such as heart looping and endocardial cushion formation could be seen in urine of pregnant rats. Moreover, the timings were consistent with those of embryological studies. The timing of the surfactant appearance in urine was right before birth. The differential proteins related to pancreas development appeared in urine at the time during reported time of pancreatic cell proliferation and differentiation. These processes were enriched only in the pregnant group and not in the control group. Furthermore, coagulation-associated pathways were found to be increasingly prominent before labor. Our results indicated that the urine proteome of pregnant rats can reflect the process of pregnancy, even fetal embryonic development. Maternal urinary proteome detection was earlier than the developmental time point of tissue sections observed by microscopy.

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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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The prevalence of Parkinson's disease (PD) is increasing but the development of novel treatment strategies and therapeutics altering the course of the disease would benefit from specific, sensitive, and non-invasive biomarkers to detect PD early. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomic workflow for urinary proteome profiling. Our workflow enabled the reproducible quantification of more than 2,000 proteins in more than 200 urine samples using minimal volumes from two independent patient cohorts. The urinary proteome was significantly different between PD patients and healthy controls, as well as between LRRK2 G2019S carriers and non-carriers in both cohorts. Interestingly, our data revealed lysosomal dysregulation in individuals with the LRRK2 G2019S mutation. When combined with machine learning, the urinary proteome data alone were sufficient to classify mutation status and disease manifestation in mutation carriers remarkably well, identifying VGF, ENPEP, and other PD-associated proteins as the most discriminating features. Taken together, our results validate urinary proteomics as a valuable strategy for biomarker discovery and patient stratification in PD.

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Key processes characterizing human aging are immunosenescence and inflammaging. The capacity of the immune system to adequately respond to external perturbations (e.g., pathogens, injuries, and biochemical irritants) and to repair somatic mutations that may cause cancers or cellular senescence declines. An important goal remains to identify genetic or biochemical, predictive biomarkers for healthy aging. We recruited two cohorts in the age range 70 to 82, one afflicted by chronic illnesses (non-healthy aging, NHA) and the other in good health (healthy aging, HA). NHA criteria included major cardiovascular, neurodegenerative, and chronic pulmonary diseases, diabetes, and cancers. Quantitative analysis of forty proinflammatory cytokines in blood plasma and more than 500 proteins in urine was performed to identify candidate biomarkers for and biological pathway implications of healthy aging. Nine cytokines revealed lower quantities in blood plasma for the NHA compared with the HA groups (fold change > 1.5; p value < 0.025) including IL-12p40 and IL-12p70. We note that, sampling at two timepoints, intra-individual cytokine abundance patterns clustered in 86% of all 60 cases, indicative of person-specific, highly controlled multi-cytokine signatures in blood plasma. Twenty-three urinary proteins were differentially abundant (HA versus NHA; fold change > 1.5; p value < 0.01). Among the proteins increased in abundance in the HA cohort were glycoprotein MUC18, ephrin type-B receptor 4, matrix remodeling-associated protein 8, angiopoietin-related protein 2, K-cadherin, and plasma protease C1 inhibitor. These proteins have been linked to the extracellular matrix, cell adhesion, and vascular remodeling and repair processes. In silico network analysis identified the regulation of coagulation, antimicrobial humoral immune responses, and the IL-12 signaling pathway as enriched GO terms. To validate links of these preliminary biomarkers and IL-12 signaling with healthy aging, clinical studies using larger cohorts and functional characterization of the genes/proteins in cellular models of aging need to be conducted.

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BACKGROUND: Posterior urethral valves (PUVs) account for 17% of pediatric renal failure. The management of pregnancies involving fetuses with PUV is hampered by the fact that current clinical parameters obtained from fetal ultrasound and/or fetal urine biochemistry are insufficient to predict postnatal renal function. We previously have developed a fetal urine peptide signature (12PUV) that predicted with high precision postnatal renal failure at 2 years of age in fetuses with PUV. Here, we evaluated the accuracy of this signature to predict postnatal renal outcome in fetuses with PUV in an independent single-center study. METHODS: Thirty-three women carrying fetuses with suspected PUV were included. Twenty-five fetuses received vesicoamniotic shunts during pregnancy. PUV was confirmed postnatally in 23 patients. Of those 23 fetuses, 2 were lost in follow-up. Four and 3 patients died in the pre- and perinatal periods, respectively. Follow-up renal function at 6 months of age was obtained for the remaining 14 patients. The primary outcome was early renal failure, defined by an eGFR < 60 mL/min/1.73 m2 before 6 months of age or pre- or perinatal death. RESULTS: The peptide signature predicted postnatal renal outcome in postnatally confirmed PUV fetuses with an AUC of 0.94 (95%CI 0.74-1.0) and an accuracy of 90% (95%CI 78-100). The signature predicted postnatal renal outcome for the suspected PUV cases with an AUC of 0.89 (95%CI 0.72-0.97) and an accuracy of 84% (95%CI 71-97). CONCLUSIONS: This single-center study confirms the predictive power of the previously identified 12PUV fetal urinary peptide signature.

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INTRODUCTION AND HYPOTHESIS: Previous studies have indicated a hereditary component of stress urinary incontinence; however, evidence on candidate genes or single-nucleotide polymorphisms (SNPs) is scarce. We hypothesize a genetic association of female stress urinary incontinence based on significant differences of the urinary and serum proteomic pattern in the identical study population. METHODS: Case-control study of 19 patients and 19 controls. We searched for known SNPs of SUI candidate genes (COL1A1, MMP1, SERPINA5, UMOD) in the database of short genetic variations and PubMed. Genomic DNA was isolated using QIAamp DNA Blood Midi Kit (Qiagen). We performed Sanger sequencing of selected exons and introns. RESULTS: The rs885786 SNP of the SERPINA5 gene was identified in 15 cases and 10 controls (p = 0.09). The rs6113 SNP of the SERPINA5 gene was present in 4 controls compared to 0 cases (p = 0.105). The rs4293393, rs13333226 and rs13335818 SNPs of the UMOD gene were identified in five cases and two controls (p = 0.20), the rs1800012 SNP of the COL1A1 gene in five cases versus four controls (p = 0.24) and the homozygous rs1799750 SNP of the MMP1 gene in eight cases versus five controls (p = 0.18). The combination of the rs885786 SNP of the SERPINA5 gene and rs179970 SNP of the MMP1 gene was detected in ten cases versus five controls (p = 0.072). CONCLUSIONS: We found nonsignificant trends toward associations of SNPs on the SERPINA5, UMOD and MMP1 gene and SUI.

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The hypercoagulable state occurs in a group of prothrombotic disorders associated with an increased risk for thromboembolic events, but it is difficult to diagnose due to the lack of available biomarkers. This study aimed to investigate systematic changes of urinary proteome in acute hypercoagulable state induced by certain antifibrinolytics. To reduce the effects of both genetic and environmental factors on the urinary proteome, we used a rat model of acute hypercoagulable state induced by an antifibrinolytic agent ε-aminocaproic acid, resembling human hypercoagulable state. Urine samples were collected during acute hypercoagulable state for analysis by liquid chromatography-tandem mass spectrometry (LCMS/MS). Of 65 significantly changed proteins in acute hypercoagulable state, 38 proteins had human orthologs, and 18 proteins were identified as stable in normal human urine. None of the identified proteins have been found to be clotting factors, but 4 proteins are known to be involved in the regulation of blood coagulation factors. Two proteins were verified as the markers associated with acute hypercoagulable state by Western blot analysis. In addition, four common differential urinary proteins have been found in acute hypercoagulable state induced by another antifibrinolytics tranexamic acid. These four proteins are potential biomarkers for early diagnosis of hypercoagulable state to prevent the development of thrombotic diseases.

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Urine is a better source than plasma for biomarker studies, as it can accumulate all changes in the body. Various candidate urinary biomarkers of physiological condition, kidney disease and even brain dysfunction, have been detected in urine; however, urine has rarely been used to reflect cardiac diseases. In this study, urine at day 0, 14, 21 and 28 were collected from the myosin-induced autoimmune myocarditis rat models. The candidate urinary biomarkers were then characterized using the isobaric tandem mass tag labeling approach coupled with offline two-dimensional reverse-phase liquid chromatography and high-resolution mass spectrometry. Compared with controls, forty-six urinary proteins were significantly changed in the myocarditis rats; among them, ten had previously been associated with myocarditis, twelve corresponding gene products had annotated as mainly cardiovascular network genes by the Ingenuity Pathway Analysis, four urinary proteins were validated by western blot, thirteen were reported in previous urine proteome studies of other diseases and twenty-six were reported the first time to be related to myocarditis. SIGNIFICANCE: This is the first study to use isobaric tandem mass tag labeling approach in the urine proteome analysis of experimental autoimmune myocarditis. These findings may provide clues for the pathogenesis of myocarditis. And the study showed that urine can be a good source of myocarditis biomarkers.

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