Urinary Proteome Profile Research Articles

Urinary proteomic biomarkers to predict cardiovascular events.

We have previously demonstrated associations between the urinary proteome profile and coronary artery disease (CAD) in cross-sectional studies. Here, we evaluate the potential of a urinary proteomic panel as a predictor of CAD in the hypertensive atherosclerotic cardiovascular disease (HACVD) substudy population of the Anglo-Scandinavian Cardiac Outcomes Trial study. Thirty-seven cases with primary CAD endpoint were matched for sex and age to controls who had not reached a CAD endpoint during the study. Spot urine samples were analyzed using CE coupled to Micro-TOF MS. A previously developed 238-marker CE-MS model for diagnosis of CAD (CAD238 ) was assessed for its predictive potential. Sixty urine samples (32 cases; 28 controls; 88% male, mean age 64 ± 5 years) were analyzed. There was a trend toward healthier values in controls for the CAD model classifier (-0.432 ± 0.326 versus -0.587 ± 0.297, p = 0.170), and the CAD model showed statistical significance on Kaplan-Meier survival analysis p = 0.021. We found 190 individual markers out of 1501 urinary peptides that separated cases and controls (AUC >0.6). Of these, 25 peptides were also components of CAD238 . A urinary proteome panel originally developed in a cross-sectional study predicts CAD endpoints independent of age and sex in a well-controlled prospective study.

Urinary proteomic profiling in severe obesity and obstructive sleep apnoea with CPAP treatment

IntroductionObstructive sleep apnoea (OSA) is common in obesity and is associated with cardiovascular and metabolic complications. Continuous positive airway pressure (CPAP) in OSA may lead to physiological changes reflected in the urinary proteome. The aim of this study was to characterise the urinary proteome in severely obese adult subjects with OSA who were receiving CPAP compared with severely obese subjects without OSA. MethodsSeverely obese subjects with and without OSA were recruited. Subjects with OSA were receiving CPAP. Body composition and blood pressure measurements were recorded. Urinary samples were analysed by Capillary Electrophoresis–Mass Spectrometry (CE–MS). ResultsTwenty-seven subjects with OSA-on-CPAP (age 49±7years, BMI 43±7kg/m2) and 25 controls without OSA (age 52±9years, BMI 39±4kg/m2) were studied. Age and BMI were not significantly different between groups. Mean CPAP use for OSA patients was 14.5±1.0 months. Metabolic syndrome was present in 14(52%) of those with OSA compared with 6(24%) of controls (p=0.039). A urinary proteome comprising 15 peptides was identified showing differential expression between the groups (p<0.01). Although correction for multiple testing did not reach significance, sequences were determined for 8 peptides demonstrating origins from collagens, fibrinogen beta chain and T-cadherin that may be associated with underlying cardiovascular disease mechanisms in OSA. ConclusionsThe urinary proteome is compared in OSA with CPAP and without OSA in severe obesity. The effects of CPAP on OSA may lead to changes in the urinary peptides but further research work is needed to investigate the potential role for urinary proteomics in characterising urinary peptide profiles in OSA.

Urinary proteomics and metabolomics in the diagnosis of pediatric disorders.

Proteomics is the study of structures and functions of proteins, while metabolomics is the study of small-molecule metabolites in the cells, tissues, and organs of the organism. Proteomic technologies have wide applications in medical field. The current revolution in proteomics has led to the discovery of several new protein markers for various disorders. Urinary proteomics and metabolomics have also evolved in the recent years, for the diagnosis of both renal and nonrenal disorders. The urinary proteome varies in normal and abnormal conditions. Different techniques are employed for the analysis of pediatric urinary proteome, the commonest being MS. Before introduction into clinical use, there is the need for careful standardization. Available data suggest that there are differences in urinary proteome between adult and pediatric populations. It is noted that infant urine contains proteins involved in translation and transcription, cellular growth, and metabolic processes, which are not predominant in adult urine. Available data on urinary proteomic and metabolomic profile in common pediatric disorders are also reviewed here.

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Objectives Urine as a biofluid is commonly used in clinical diagnostics, including during pregnancy. Urine is a rich source of polypeptides and protein degradation products. Electron transfer dissociation (ETD) techniques have recently been applied to peptides, and improved fragmentation of long polypeptides has been demonstrated; ETD further facilitates analysis of labile post-translational modifications. We therefore applied this advanced technique for peptide dissociation to analyse and identify urinary polypeptides for the first time. Methods We examined the urinary peptidome from normal pregnant women during pregnancy, to demonstrate that peptides are readily observed. We utilised conventional MS/MS techniques and then used ETD (LC–MS/MS performed on an orbitrap equipped with ETD source, coupled to a nanoAcquity HPLC) to increase the identification rate of the peptides within these samples, as the polypeptide species observed are large and highly charged. Results An increase in the number of peptides whose identities could be ascribed using routine database searching methods was enabled via use of ETD. These peptides, as anticipated, were large and highly charged (typically giving charge states of 4–8+ over a mass-to-charge range of 400–2000 m/z). Conclusions Urinary proteomic profiling has not been able to discriminate between normal and pre-eclampsia pregnancies at gestations early enough to enable preventative strategies. Enhanced polypeptide identification achieved through ETD may facilitate clinically useful predictive tests. Disclosures S. Hart: None. L. Kenny: Commercial Interest: Metabolomic Diagnostics. J. Myers: None. P. Baker: Commercial Interest: Metabolomic Diagnostics.

Urinary proteomics in obstructive sleep apnoea and obesity.

Obstructive sleep apnoea (OSA) is a common complication of obesity and can have a substantial negative impact on a patient's quality of life and risk of cardiovascular disease. The aim of this case-control study was to undertake discovery profiling of urinary peptides using capillary electrophoresis-mass spectrometry (CE-MS) in obese subjects with and without OSA, without a history of coronary artery disease. Urinary samples were analysed by CE-MS. Body composition and blood pressure measurements were recorded. Overnight polysomnography was conducted to confirm or refute OSA. OSA patients were naïve to continuous positive airway pressure treatment. Sixty-one subjects with OSA (age 47 ± 9 years, BMI 43 ± 8 kg/m(2)) and 31 controls (age 49 ± 10 years, BMI 40 ± 5 kg/m(2)) were studied; P = ns for age and BMI. Apnoea-hypopnoea Index was higher in patients with OSA (24 ± 18·6) than controls without OSA (non-OSA) (2·6 ± 1·1; P < 0·0001). Metabolic syndrome was present in 35 (57%) of those with OSA compared with 4 (13%) of controls (P < 0·0001). Twenty-four polypeptides were candidates for differential distribution (P < 0·01), although these differences did not reach significance after multiple testing. Sequences were determined for eight peptides demonstrating origins from collagens and fibrinogen alpha. In this study, we report for the first time, urinary proteomic profile analyses using CE-MS in OSA and non-OSA obese groups. The differences in urinary proteomic profiles prior to adjustment for multiple testing, with increased metabolic syndrome in obese OSA subjects, suggest that there may be a role for CE-MS in characterising urinary profiles in severely obese populations with OSA.

The application of urinary proteomics for the detection of biomarkers of kidney diseases.

Urine is a biological material that can be easily obtained in the clinic. The identification of proteins excreted in urine provides useful biological information about the kidney as well as a unique opportunity to examine physiological and pathological changes in the kidney in a noninvasive manner. Recent technological advances in urinary proteomic profiling have provided the foundation for a number of urinary proteomic studies directed at identifying markers of kidney disease diagnosis, prognosis, or responsiveness to therapy. In this review, we describe the strengths of different urinary proteomic methods for the discovery of potential biomarkers of kidney diseases. We also highlight the limitations and future goals of these approaches.

Urinary proteome profile predictive of disease activity in rheumatoid arthritis.

Current serum biomarkers for rheumatoid arthritis (RA) are not highly sensitive or specific to changes of disease activities. Thus, other complementary biomarkers have been needed to improve assessment of RA activities. In many diseases, urine has been studied as a window to provide complementary information to serum measures. Here, we conducted quantitative urinary proteome profiling using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and identified 134 differentially expressed proteins (DEPs) between RA and osteoarthritis (OA) urine samples. By integrating the DEPs with gene expression profiles in joints and mononuclear cells, we initially selected 12 biomarker candidates related to joint pathology and then tested their altered expression in independent RA and OA samples using enzyme-linked immunosorbent assay. Of the initial candidates, we selected four DEPs as final candidates that were abundant in RA patients and consistent with those observed in LC-MS/MS analysis. Among them, we further focused on urinary soluble CD14 (sCD14) and examined its diagnostic value and association with disease activity. Urinary sCD14 had a diagnostic value comparable to conventional serum measures and an even higher predictive power for disease activity when combined with serum C-reactive protein. Thus, our urinary proteome provides a diagnostic window complementary to current serum parameters for the disease activity of RA.

Urinary proteomic and non-prefractionation quantitative phosphoproteomic analysis during pregnancy and non-pregnancy

BackgroundProgress in the fields of protein separation and identification technologies has accelerated research into biofluids proteomics for protein biomarker discovery. Urine has become an ideal and rich source of biomarkers in clinical proteomics. Here we performed a proteomic analysis of urine samples from pregnant and non-pregnant patients using gel electrophoresis and high-resolution mass spectrometry. Furthermore, we also apply a non-prefractionation quantitative phosphoproteomic approach using mTRAQ labeling to evaluate the expression of specific phosphoproteins during pregnancy comparison with non-pregnancy.ResultsIn total, 2579 proteins (10429 unique peptides) were identified, including 1408 from the urine of pregnant volunteers and 1985 from the urine of non-pregnant volunteers. One thousand and twenty-three proteins were not reported in previous studies at the proteome level and were unique to our study. Furthermore, we obtained 237 phosphopeptides, representing 105 phosphoproteins. Among these phosphoproteins, 16 of them were found to be significantly differentially expressed, of which 14 were up-regulated and two were down-regulated in urine samples from women just before vaginal delivery.ConclusionTaken together, these results offer a comprehensive urinary proteomic profile of healthy women during before and after vaginal delivery and novel information on the phosphoproteins that are differentially regulated during the maintenance of normal pregnancy. Our results may provide a better understanding of the mechanisms of pregnancy maintenance, potentially leading to the development of biomarker-based sensitive assays for understanding pregnancy.

Abstract 516: Urinary Proteomic Biomarkers to Predict Cardiovascular Events

We have previously demonstrated associations between the urinary proteome profile and coronary artery disease (CAD) in cross-sectional studies. Here we evaluated the potential of urinary proteomics as a predictor of CAD in the Hypertension Associated Cardiovascular Disease (HACVD) sub-study population of the ASCOT study. Thirty-seven cases with the primary endpoint CAD (fatal CAD, non-fatal myocardial infarction and coronary revascularisation) but without established cardiovascular disease at baseline were selected and matched for sex and age within ±2 years to controls who had not reached a CAD endpoint during the study (median observation time, 5 years). A spot urine sample collected at 1 to 1.5 years post randomisation was analysed using capillary electrophoresis (CE) on-line coupled to Micro-TOF mass spectrometry (MS). A previously developed 238-marker CE-MS model for diagnosis of CAD (CAD 238 ) was assessed for its predictive potential. Sixty urine samples (32 cases; 28 controls; 88% male, mean age 64±5 years) passed quality control for proteomic analysis. There was a trend towards lower ("healthier") values in controls for the CAD model classifier (-0.432±0.326 vs -0.587±0.297, P =0.062), and the CAD model showed statistical significance on Kaplan-Meier survival analysis (Log Rank (Mantel-Cox) P =0.021). After unblinding we found 190 individual markers out of 1501 urinary peptides that separated cases and controls with an AUC&gt;0.6. Of these, 28 peptides including fragments of PGRC1, PTGDS, CO1A1, CO3A1, COGA1, PXDC2, B3GT6 and RET4 were also components of CAD 238 . A urinary proteome panel that was originally developed in a cross-sectional study predicts CAD endpoints independent of age and sex in a well controlled prospective study. Proteomic analysis may have the potential to detect subclinical cardiovascular damage that is associated with increased cardiovascular risk.

PP046. A unique urinary proteome profile at 15 weeks’ gestation in low-risk women with subsequent pre-eclampsia

Pre-eclampsia remains one of the leading causing of maternal and perinatal morbidity and mortality. Recent plasma biomarker discovery has improved the diagnosis of pre-eclampsia; however no factors which are quantitatively different remote from disease onset have been identified. Urine represents an ideal non-invasive fluid for analysis and potentially rich source of biomarker detection. Proteomics is a rapidly developing technique which allows the detection and identification of individual proteins. We propose that early glomerular changes will result in significant differences in the urinary proteome of women destined to develop pre-eclampsia, prior to detection of the clinical syndrome. To define a urinary profile at 15 weeks' gestation, predictive of subsequent pre-eclampsia, in low risk nulliparous women. Urine samples from twelve women at 15 weeks' gestation who subsequently developed pre-eclampsia (cases) and twelve gestation-, BMI- and age-matched controls were selected from the SCreening Of Pregnancy Endpoints (SCOPE) cohort. A proteome profile was established using a validated workflow, involving selective immunodepletion, 1D SDS-PAGE gel fractionation, in-gel digestion of gel sections, LC-MS/MS analysis and normalised spectral analysis. More than 900 proteins were identified using minimal stringency in Scaffold. Spectral counts revealed 24 proteins were significantly upregulated in cases and absent in controls and 3 proteins were absent in cases but present in controls. For protection of intellectual property protein identities are omitted. A urinary proteomic signature can be identified in the urine of women at 15 weeks' gestation who subsequently develop pre-eclampsia. Formal quantitative analysis will be performed with selective reactive-monitoring analysis, followed by subsequent validation of this differential proteomic profile using a larger number samples per groups.

Urinary proteomic profiling reveals diclofenac-induced renal injury and hepatic regeneration in mice

Diclofenac (DF) is a widely used non-steroidal anti-inflammatory drug for the treatment of rheumatic disorders, but is often associated with liver injury. We applied urinary proteomic profiling using MALDI-TOF MS to identify biomarkers for DF-induced hepatotoxicity in mice. Female CH3/HeOUJIco mice were treated with 75mg/kg bw DF by oral gavage and 24h urine was collected. Proteins identified in urine of DF-treated mice included epidermal growth factor, transthyretin, kallikrein, clusterin, fatty acid binding protein 1 and urokinase, which are related to liver regeneration but also to kidney injury. Both organs showed enhanced levels of oxidative stress (TBARS, p<0.01). Kidney injury was confirmed by histology and increased Kim1 and Il-6 mRNA expression levels (p<0.001 and p<0.01). Liver histology and plasma ALT levels in DF-treated mice were not different from control, but mRNA expression of Stat3 (p<0.001) and protein expression of PCNA (p<0.05) were increased, indicating liver regeneration. In conclusion, urinary proteome analysis revealed that DF treatment in mice induced kidney and liver injury. Within 24h, however, the liver was able to recover by activating tissue regeneration processes. Hence, the proteins found in urine of DF-treated mice represent kidney damage rather than hepatic injury.

The Interaction of Thiol Drugs and Urine pH in the Treatment of Cystinuria

Pharmacological therapy for cystinuria consists of alkali salts to increase urine pH and thiol drugs to form soluble cysteine-drug complexes. The effect of alkalinizing urine on thiol drug activity has not been well studied. Urine samples were obtained from 5 healthy subjects and pH was adjusted (range 6.0 to 8.0) in each urine aliquot. Urine samples were incubated with cystine crystals at 37C for 5, 15 and 60 minutes, and 48 hours. We compared cystine solubility in urine samples spiked with thiol drugs at a final concentration of 2 mM to that in control urine samples at the various pH levels and time points. In samples incubated for 48 hours, which is the standard time frame for solubility studies, cystine solubility more than doubled with thiol drugs compared to control and did not depend on pH. However, when incubation time was shortened to 5 minutes, representing the dwell time of urine in the renal pelvis, the effect of thiol drugs to solubilize cystine greatly depended on urine pH with less cystine dissolved at lower pH. Increasing urine pH greatly increased the efficacy of thiol drugs to solubilize cystine in a clinically relevant time frame. These findings suggest that to maximize the benefit of thiol drugs alkali therapy should be used in conjunction with thiol drugs with the goal of keeping urine pH at 7.5 or above. Clinical trials are needed to confirm these in vitro findings.

Diagnostic Potential of Urinary α1-Antitrypsin and Apolipoprotein E in the Detection of Bladder Cancer

The ability to reliably diagnose bladder cancer in voided urine samples would be a major advance. Using high throughput technologies, we identified a panel of bladder cancer associated biomarkers with potential clinical usefulness. In this study we tested 4 potential biomarkers for the noninvasive detection of bladder cancer. We examined voided urine specimens from 124 patients, including 63 newly diagnosed with bladder cancer and 61 controls. Concentrations of proteins were assessed by enzyme-linked immunosorbent assay, including α1-antitrypsin, apolipoprotein E, osteopontin and pentraxin 3. Data were compared to the results of urinary cytology and the BTA Trak® enzyme-linked immunosorbent assay based bladder cancer detection assay. We used the AUC of ROC curves to compare the usefulness of each biomarker to detect bladder cancer. Urinary levels of α1-antitrypsin, apolipoprotein E and bladder tumor antigen were significantly increased in subjects with bladder cancer. α1-Antitrypsin (AUC 0.9087, 95% CI 0.8555-0.9619) and apolipoprotein E (AUC 0.8987, 95% CI 0.8449-0.9525) were the most accurate biomarkers. The combination of α1-antitrypsin and apolipoprotein E (AUC 0.9399) achieved 91% sensitivity, 89% specificity, and a positive and negative predictive value of 89% and 90%, respectively. Multivariate regression analysis highlighted only apolipoprotein E as an independent predictor of bladder cancer (OR 24.9, 95% CI 4.22-146.7, p = 0.0004). Alone or in combination, α1-antitrypsin and apolipoprotein E show promise for the noninvasive detection of bladder cancer (OR 24.9, 95% CI 4.22-146.7, p = 0.0004). Larger, prospective studies including more low grade, low stage tumors are needed to confirm these results.

IL-8 as a urinary biomarker for the detection of bladder cancer

BackgroundCurrent urine-based assays for bladder cancer (BCa) diagnosis lack accuracy, so the search for improved biomarkers continues. Through genomic and proteomic profiling of urine, we have identified a panel of biomarkers associated with the presence of BCa. In this study, we evaluated the utility of three of these biomarkers, interleukin 8 (IL-8), Matrix metallopeptidase 9 (MMP-9) and Syndecan in the diagnosis of BCa through urinalysis.MethodsVoided urines from 127 subjects, cancer subjects (n = 64), non-cancer subjects (n = 63) were analyzed. The protein concentrations of IL-8, MMP-9, and Syndecan were assessed by enzyme-linked immunosorbent assay (ELISA). Data were also compared to a commercial ELISA-based BCa detection assay (BTA-Trak©) and urinary cytology. We used the area under the curve of a receiver operating characteristic (AUROC) to compare the performance of each biomarker.ResultsUrinary protein concentrations of IL-8, MMP-9 and BTA were significantly elevated in BCa subjects. Of the experimental markers compared to BTA-Trak©, IL-8 was the most prominent marker (AUC; 0.79; 95% confidence interval [CI], 0.72-0.86). Multivariate regression analysis revealed that only IL-8 (OR; 1.51; 95% CI, 1.16-1.97, p = 0.002) was an independent factor for the detection of BCa.ConclusionsThese results suggest that the measurement of IL-8 in voided urinary samples may have utility for urine-based detection of BCa. These findings need to be confirmed in a larger, prospective cohort.

Evaluation of urine biomarkers of kidney injury in polycystic kidney disease

Progressive disruption of renal tubular integrity in the setting of increased cellular proliferation and apoptosis is a feature of ADPKD. Here we evaluated the effect of these processes on the expression of NGAL and IL-18, markers of tubular injury, in rodent models and in the cyst fluid and urine of patients with ADPKD. Two mouse models where Pkd2 was inactivated which resulted in early or adult onset cysts, were used to evaluate NGAL levels. Further, the Han:SPRD rat model of polycystic disease was used to study IL-18 levels. In four annual serial urine samples from 107 patients with ADPKD in the Consortium for Radiologic Imaging for the Study of Polycystic Kidney Disease (CRISP) study, NGAL and IL-18 excretion rates were determined in conjunction with measures of total kidney volume and estimated GFR (eGFR) by the MDRD equation. Kidneys from affected mice and rats showed prominent expression of NGAL and IL-18/IL-18R, respectively, in epithelial cells lining kidney cysts. In human ADPKD cyst fluid, both NGAL and IL-18 were elevated. In CRISP patients, the mean percentage increase in total kidney volume was 5.4 /year and the mean decline in eGFR 2.4 mL/min/year. The trend of increased mean urine NGAL and IL-18 over three years was statistically significant; however, there was no association of tertiles of IL-18 or quartiles of NGAL and the change in total kidney volume or eGFR over this period. Thus, urinary NGAL and IL-18 excretion are mildly and stably elevated in ADPKD, but do not correlate with changes in total kidney volume or kidney function. This may be due, in part, to the lack of communication between individual cysts and the urinary collecting system in this disorder.

Urine proteomic profiling for biomarkers of acetaminophen-induced acute liver injury in mice and humans

Urine proteomic profiling for biomarkers of acetaminophen-induced acute liver injury in mice and humans

“Cheek-to-cheek” urinary proteome profiling via combinatorial peptide ligand libraries: A novel, unexpected elution system

A new method is here reported for facile elution of the human urinary proteome after being captured with combinatorial peptide ligand libraries (CPLL, ProteoMiner). It consists in challenging the beads with 100mM Tris, pH 7.4, or with 100mM Lys, pH 7.4 or even better with a mixture of Lys, Arg, Asp and Glu (150mM final concentration). These elutions permit recovery of species in a native form, for monitoring any biological activity of the eluted species, while avoiding the noxious presence of sodium dodecyl sulphate (SDS), reported as the best eluant so far from CPLL beads. SDS, albeit permitting quantitative recovery from the beads, has to be removed from the sample prior to mass spectrometry analysis. This unorthodox elution, which most likely will work only for urine samples, seems to be due to the fact that bile salts and urinary pigments are massively adsorbed by the beads, thus masking the hydrophobic binding sites of aromatic and non-aromatic amino acids. The binding thus occurs mostly via ionic and hydrogen bond interactions via the "Grand Catchers" Arg, Lys, His, which can then be easily challenged by positively charged species, such a Tris, free Lys and free Arg in the eluant as well as by negatively charged compounds, such as Glu and Asp. When eluting with the four-amino acid mix, at least 3300 spots can be visualized in a 2D map.

Urine proteome profile: An attempt to biomarker discovery for the non-invasive diagnosis of IgA nephropathy

Urine proteome profile: An attempt to biomarker discovery for the non-invasive diagnosis of IgA nephropathy

Identification of β2‐microglobulin as a urinary biomarker for chronic allograft nephropathy using proteomic methods

Chronic allograft nephropathy (CAN) remains the leading cause of renal graft loss after the first year following renal transplantation. This study aimed to identify novel urinary proteomic profiles, which could distinguish and predict CAN in susceptible individuals. The study included 34 renal transplant patients with histologically proven CAN and 36 patients with normal renal transplant function. High-throughput proteomic profiles were generated from urine samples with three different ProteinChip arrays by surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Following SELDI, a biomarker pattern software analysis was performed which led to the identification of a novel biomarker pattern that could distinguish patients with CAN from those with normal renal function. An 11.7 kDa protein identified as β2 microglobulin was the primary protein of this biomarker pattern, distinguishing CAN from control patients (receiver operator characteristic [ROC]=0.996). SELDI-TOF-MS comparison of purified β2 microglobulin protein and CAN urine demonstrated identical 11.7 kDa protein peaks. Significantly, higher concentrations of 2 microglobulin were found in the urine of patients with CAN compared with the urine of normal renal function transplant recipients (p<0.001). Although further validation in a larger more diverse patient population is required to determine if this β2 microglobulin protein biomarker will provide a potential means of diagnosing CAN by noninvasive methods in a clinical setting, this study clearly shows a capability to stratify control and disease patients.

Identification of a novel urinary proteomic signature at time-of-disease in women with pre-eclampsia

BackgroundEarly detection/diagnosis of pre-eclampsia allows appropriate monitoring and targeting of therapeutic strategies. Urinary proteomics is a rapidly advancing technique which gives functional insight into gene expression in living organisms. Urine...