Urine protein profiling with surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry

Co-Analysis of Serum and Urine Differentially Expressed Proteins in Mucopolysaccharidosis Type I

Mucopolysaccharidosis type I (MPS I) is a lysosomal storage disease caused by the deficiency of the enzyme α-l-iduronidase (IDUA), typically leading to devastating secondary pathophysiological cascades. Due to the irreversible nature of the disease's progression, early diagnosis and interventional treatment has become particularly crucial. Considering the fact that serum and urine are the most commonly used specimens in clinical practice for detection, we conducted an analysis to identify the differential protein profile in the serum and urine of MPS I patients using the tandem mass tag (TMT) technique. A total of 182 differentially expressed proteins (DEPs) were detected in serum, among which 9 showed significant differences as confirmed by parallel reaction monitoring (PRM) analysis. The proteins APOA1 and LGFBP3 were downregulated in serum, while the expression levels of ALDOB, CD163, CRTAC1, DPP4, LAMP2, SHBG, and SPP2 exhibited an increase. In further exploratory studies of urinary proteomics, 32 identified DEPs were consistent with the discovered findings in serum tests, specifically displaying a high diagnostic area under the curve (AUC) value. Thus, our study demonstrates the value of serum-urine integrated proteomic analysis in evaluating the clinical course of MPS I and other potential metabolic disorders, shedding light on the importance of early detection and intervention in these conditions.

Comparison of clean catch and bag urine using LC-MS/MS proteomics in infants

BACKGROUND

Urinary proteomics identifies the totality of urinary proteins and can therefore help in getting an early and precise diagnosis of various pathological processes in the kidneys. In infants, non-invasive urine collection is most commonly accomplished with a urine bag or clean catch. The influence of those two collection methods on urinary proteomics was assessed in this study.

METHODS

Thirty-two urine samples were collected in infants using urine bag and clean catch within 24 h. Nine boys and seven girls with a mean age of 4.3 ± 2.9 months were included (5 × post-pyelonephritis, 10 × non-kidney disease, 1 × chronic kidney disease (CKD)). Liquid chromatography-mass spectrometry (LC-MS/MS) was performed in data-independent acquisition (DIA) mode. Protein identification and quantification were achieved using Spectronaut.

RESULTS

A total of 1454 urinary proteins were detected. Albumin and α-1-microglobulin were detected the most. The 18 top-abundant proteins accounted for 50% of total abundance. The number of proteins was slightly, but insignificantly higher in clean catch (957 ± 245) than in bag urine (876 ± 255). The median intensity was 1.2 × higher in the clean catch. Overall, differential detection of proteins was 29% between the collection methods; however, it diminished to 3% in the 96 top-abundant proteins. Pearson's correlation coefficient was 0.81 ± 0.11, demonstrating a high intraindividual correlation. A principal component analysis and a heat map showed clustering according to diagnoses and patients rather than to the collection method.

CONCLUSION

Urinary proteomics shows a high correlation with minor variation in low-abundant proteins between the two urine collection methods. The biological characteristics overrule this variation. Graphical abstract A higher resolution version of the Graphical abstract is available as Supplementary information.

Systematic Review: Urine Biomarker Discovery for Inflammatory Bowel Disease Diagnosis

Inflammatory bowel diseases (IBDs) are chronic, heterogeneous, and inflammatory conditions mainly affecting the gastrointestinal tract. Currently, endoscopy is the gold standard test for assessing mucosal activity and healing in clinical practice; however, it is a costly, time-consuming, invasive, and uncomfortable procedure for the patients. Therefore, there is an urgent need for sensitive, specific, fast and non-invasive biomarkers for the diagnosis of IBD in medical research. Urine is an excellent biofluid for discovering biomarkers because it is non-invasive to sample. In this review, we aimed to summarize proteomics and metabolomics studies performed in both animal models of IBD and humans that identify urinary biomarkers for IBD diagnosis. Future large-scale multi-omics studies should be conducted in collaboration with clinicians, researchers, and industry to make progress toward the development of sensitive and specific diagnostic biomarkers, thereby making personalized medicine possible.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer (PanCa) presents a major concern and health burden. The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics; however, they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting. Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures. The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians. Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages. In this review, we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

Urinary proteomics combined with home blood pressure telemonitoring for health care reform trial: rational and protocol

BACKGROUND

Hypertension and diabetes cause chronic kidney disease (CKD) and diastolic left ventricular dysfunction (DVD) as forerunners of disability and death. Home blood pressure telemonitoring (HTM) and urinary peptidomic profiling (UPP) are technologies enabling prevention.

METHODS

UPRIGHT-HTM (Urinary Proteomics Combined with Home Blood Pressure Telemonitoring for Health Care Reform [NCT04299529]) is an investigator-initiated 5-year clinical trial with patient-centred design, which will randomise 1148 patients to be recruited in Europe, sub-Saharan Africa and South America. During the whole study, HTM data will be collected and freely accessible for patients and caregivers. The UPP, measured at enrolment only, will be communicated early during follow-up to 50% of patients and their caregivers (intervention), but only at trial closure in 50% (control). The hypothesis is that early knowledge of the UPP risk profile will lead to more rigorous risk factor management and result in benefit. Eligible patients, aged 55-75 years old, are asymptomatic, but have ≥5 CKD- or DVD-related risk factors, preferably including hypertension, type-2 diabetes, or both. The primary endpoint is a composite of new-onset intermediate and hard cardiovascular and renal outcomes. Demonstrating that combining UPP with HTM is feasible in a multicultural context and defining the molecular signatures of early CKD and DVD are secondary endpoints.

EXPECTED OUTCOMES

The expected outcome is that application of UPP on top of HTM will be superior to HTM alone in the prevention of CKD and DVD and associated complications and that UPP allows shifting emphasis from treating to preventing disease, thereby empowering patients.

Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties

Peptidomics allows the identification of peptides that are derived from proteins. Urinary peptidomics has revolutionized the field of diagnostics as the samples represent complete systemic changes happening in the body. Moreover, it can be collected in a non-invasive manner. We profiled the peptides in urine collected from different physiological states (heifer, pregnancy, and lactation) of Sahiwal cows. Endogenous peptides were extracted from 30 individual cows belonging to three groups, each group comprising of ten animals (biological replicates n = 10). Nano Liquid chromatography Mass spectrometry (nLC-MS/MS) experiments revealed 5239, 4774, and 5466 peptides in the heifer, pregnant and lactating animals respectively. Urinary peptides of <10 kDa size were considered for the study. Peptides were extracted by 10 kDa MWCO filter. Sequences were identified by scanning the MS spectra ranging from 200 to 2200 m/z. The peptides exhibited diversity in sequences across different physiological states and in-silico experiments were conducted to classify the bioactive peptides into anti-microbial, anti-inflammatory, anti-hypertensive, and anti-cancerous groups. We have validated the antimicrobial effect of urinary peptides on Staphylococcus aureus and Escherichia coli under an in-vitro experimental set up. The origin of these peptides was traced back to certain proteases viz. MMPs, KLKs, CASPs, ADAMs etc. which were found responsible for the physiology-specific peptide signature of urine. Proteins involved in extracellular matrix structural constituent (GO:0005201) were found significant during pregnancy and lactation in which tissue remodeling is extensive. Collagen trimers were prominent molecules under cellular component category during lactation. Homophilic cell adhesion was found to be an important biological process involved in embryo attachment during pregnancy. The in-silico study also highlighted the enrichment of progenitor proteins on specific chromosomes and their relative expression in context to specific physiology. The urinary peptides, precursor proteins, and proteases identified in the study offers a base line information in healthy cows which can be utilized in biomarker discovery research for several pathophysiological studies.

A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients

BACKGROUND

COVID-19 prediction models based on clinical characteristics, routine biochemistry and imaging, have been developed, but little is known on proteomic markers reflecting the molecular pathophysiology of disease progression.

METHODS

The multicentre (six European study sites) Prospective Validation of a Proteomic Urine Test for Early and Accurate Prognosis of Critical Course Complications in Patients with SARS-CoV-2 Infection Study (Crit-COV-U) is recruiting consecutive patients (≥ 18 years) with PCR-confirmed SARS-CoV-2 infection. A urinary proteomic biomarker (COV50) developed by capillary-electrophoresis-mass spectrometry (CE-MS) technology, comprising 50 sequenced peptides and identifying the parental proteins, was evaluated in 228 patients (derivation cohort) with replication in 99 patients (validation cohort). Death and progression along the World Health Organization (WHO) Clinical Progression Scale were assessed up to 21 days after the initial PCR test. Statistical methods included logistic regression, receiver operating curve (ROC) analysis and comparison of the area under the curve (AUC).

FINDINGS

In the derivation cohort, 23 patients died, and 48 developed worse WHO scores. The odds ratios (OR) for death per 1 standard deviation (SD) increment in COV50 were 3·52 (95% CI, 2·02-6·13, p <0·0001) unadjusted and 2·73 (1·25-5·95, p = 0·012) adjusted for sex, age, baseline WHO score, body mass index (BMI) and comorbidities. For WHO scale progression, the corresponding OR were 2·63 (1·80-3·85, p<0·0001) and 3·38 (1·85-6·17, p<0·0001), respectively. The area under the curve (AUC) for COV50 as a continuously distributed variable was 0·80 (0·72-0·88) for mortality and 0·74 (0·66-0·81) for worsening WHO score. The optimised COV50 thresholds for mortality and worsening WHO score were 0·47 and 0·04 with sensitivity/specificity of 87·0 (74·6%) and 77·1 (63·9%), respectively. On top of covariates, COV50 improved the AUC, albeit borderline for death, from 0·78 to 0·82 (p = 0·11) and 0·84 (p = 0·052) for mortality and from 0·68 to 0·78 (p = 0·0097) and 0·75 (p = 0·021) for worsening WHO score. The validation cohort findings were confirmatory.

INTERPRETATION

This first CRIT-COV-U report proves the concept that urinary proteomic profiling generates biomarkers indicating adverse COVID-19 outcomes, even at an early disease stage, including WHO stages 1-3. These findings need to be consolidated in an upcoming final dataset.

FUNDING

The German Federal Ministry of Health funded the study.

Noninvasive diagnostic of periprosthetic joint infection by urinary peptide markers: A preliminary study

Previous immunohistochemical analyses revealed altered protein expression in the periprosthetic membranes of patients with periprosthetic joint infection (PJI). Proteins are degraded to peptides that may pass the blood-kidney barrier depending on their size. The aim of this study was to evaluate if PJI can be diagnosed based on the urinary peptide excretion pattern. Thirty patients undergoing removal of their hip or knee prostheses due to septic or aseptic loosening were enrolled. Specimen sampling was performed according to the MusculoSkeletal Infection Society criteria. A urinary sample was analyzed before surgery using capillary electrophoresis coupled with mass spectrometry. Peptides with differential urinary excretion between groups were used to establish a multimarker model. A total of 137 peptides were differentially excreted between the septic and aseptic groups. The majority of identified peptide markers were fragments of structural extracellular matrix proteins, potentially due to their origin from the periprosthetic membrane. A marker model with 83 peptides achieved the best diagnostic performance for diagnosing PJI with a sensitivity of 95%, a specificity of 90%, and an area under the curve of 0.96. The altered protein expression pattern in the periprosthetic membrane of PJI is most likely reflected in excreted urinary peptides. Thus, the diagnosis of PJI by urinary peptide markers seems to be a reasonable approach.

Lessons learned from proteome analysis of perinatal neurovascular pathologies

INTRODUCTION

Perinatal and pediatric diseases related to neurovascular disorders cause significant problems during life, affecting a population with a long life expectancy. Early diagnosis and assessment of the severity of these diseases are crucial to establish an appropriate neuroprotective treatment. Currently, physical examination, neuroimaging and clinical judgment are the main tools for diagnosis, although these tests have certain limitations. There is growing interest in the potential value of noninvasive biomarkers that can be used to monitor child patients at risk of brain damage, allowing accurate, and reproducible measurements.

AREAS COVERED

This review describes potential biomarkers for the diagnosis of perinatal neurovascular diseases and discusses the possibilities they open for the classification and treatment of neonatal neurovascular diseases.

EXPERT OPINION

Although high rates of ischemic and hemorrhagic stroke exist in pediatric populations, most studies have focused on biomarkers of hypoxic-ischemic encephalopathy. Inflammatory and neuronal biomarkers such as S-100B and GFAP, in combination with others yet to be discovered, could be considered as part of multiplex panels to diagnose these diseases and potentially for monitoring response to treatments. Ideally, noninvasive biofluids would be the best source for evaluating these biomarkers in proteomic assays in perinatal patients.

Proteomic identification of early urinary-biomarkers of acute kidney injury in preterm infants

The immature preterm kidney is likely to be vulnerable to acute kidney injury (AKI). However, the biomarkers currently used for AKI are not sensitive or specific and are also inadequate for the timely detection of AKI in preterm infants. The objectives of this study were to identify novel urinary biomarkers of AKI using proteomic techniques, and to verify and validate that the candidates can serve as early predictive biomarkers for AKI. In total, 1,810 proteins were identified in the discovery phase. Among those proteins, 174 were selected as the 1^st targeted proteins. A total of 168 proteins were quantified, and the levels of 6 were significantly increased in the AKI group in the verification phase. Using a clinical assay, the results were confirmed and validated using samples of the first urine after birth from the biorepository. Finally, enzyme-linked immunosorbent assays revealed that the levels of annexin A5, neutrophil gelatinase-associated lipocalin (NGAL), and protein S100-P were significantly higher in the samples of the first urine from patients with AKI than in those from patients without AKI. In conclusion, urinary annexin A5, NGAL and protein S100-P levels are promising biomarkers for early, accurate prediction of AKI in preterm infants.

Immunomics in Pediatric Rheumatic Diseases

The inherent complexity in the immune landscape of pediatric rheumatic disease necessitates a holistic system approach. Uncertainty in the mechanistic workings and etiological driving forces presents difficulty in personalized treatments. The development and progression of immunomics are well suited to deal with this complexity. Immunomics encompasses a spectrum of biological processes that entail genomics, transcriptomics, epigenomics, proteomics, and cytomics. In this review, we will discuss how various high dimensional technologies in immunomics have helped to grow a wealth of data that provide salient clues and biological insights into the pathogenesis of autoimmunity. Interfaced with critical unresolved clinical questions and unmet medical needs, these platforms have helped to identify candidate immune targets, refine patient stratification, and understand treatment response or resistance. Yet the unprecedented growth in data has presented both opportunities and challenges. Researchers are now facing huge heterogeneous data sets from different origins that need to be integrated and exploited for further data mining. We believe that the utilization and integration of these platforms will help unravel the complexities and expedite both discovery and validation of clinical targets.

Urinary Peptidomic Biomarker for Personalized Prevention and Treatment of Diastolic Left Ventricular Dysfunction

Diastolic heart failure (DHF) is characterized by slow left ventricular (LV) relaxation, increased LV stiffness, interstitial deposition of collagen, and a modified extracellular matrix proteins. Among Europeans, the frequency of asymptomatic diastolic LV dysfunction (DD) is 25%. This constitutes a large pool of people at high risk of DHF. The goal of this review was to describe the discovery and the initial validation of new multidimensional urinary peptidomic biomarkers (UPB) indicative of DD, mainly consisting of collagen fragments, and to describe a roadmap for their introduction into clinical practice. The availability of new drugs creates a window of opportunity for mounting a randomized clinical trial consolidating the clinical applicability of UPB to screen for DD. If successfully completed, such trial will benefit ≈25% of all people older than 50 years and open a large market for a UPB diagnostic tool and the drug tested. Moreover, sequenced peptides making up UPB will generate novel insights in the pathophysiology of DD and facilitate personalized treatment of patients with DHF for whom prevention came too late. If proven cost‐effective, the clinical application of UPB will contribute to the sustainability of health care in aging population in epidemiologic transition.

Epidemiologic observations guiding clinical application of a urinary peptidomic marker of diastolic left ventricular dysfunction

Hypertension, obesity, and old age are major risk factors for left ventricular (LV) diastolic dysfunction (LVDD), but easily applicable screening tools for people at risk are lacking. We investigated whether HF1, a urinary biomarker consisting of 85 peptides, can predict over a 5-year time span mildly impaired diastolic LV function as assessed by echocardiography. In 645 white Flemish (50.5% women; 50.9 years [mean]), we measured HF1 by capillary electrophoresis coupled with mass spectrometry in 2005-2010. We measured early (E) and late (A) peak velocities of the transmitral blood flow and early (e') and late (a') mitral annular peak velocities and their ratios in 2009-2013. In multivariable-adjusted analyses, per 1-standard deviation increment in HF1, e' was -0.193 cm/s lower (95% confidence interval: -0.352 to -0.033; P = .018) and E/e' 0.174 units higher (0.005-0.342; P = .043). Of 645 participants, 179 (27.8%) had LVDD at follow-up, based on impaired relaxation in 69 patients (38.5%) or an elevated filling pressure in the presence of a normal (74 [43.8%]) or low (36 [20.1%]) age-specific E/A ratio. For a 1-standard deviation increment in HF1, the adjusted odds ratio was 1.37 (confidence interval, 1.07-1.76; P = .013). The integrated discrimination (+1.14%) and net reclassification (+31.7%) improvement of the optimized HF1 threshold (-0.350) in discriminating normal from abnormal diastolic LV function at follow-up over and beyond other risk factors was significant (P ≤ .024). In conclusion, HF1 may allow screening for LVDD over a 5-year horizon in asymptomatic people.

New developments in transplant proteomics

PURPOSE OF REVIEW

Despite modern immunosuppression, renal allograft rejection remains a major contributor to graft loss. Novel biomarkers may help improve posttransplant outcomes through the early detection and treatment of rejection. Our objective is to provide an overview of proteomics, review recent discovery-based rejection studies, and explore innovative approaches in biomarker development.

RECENT FINDINGS

Urine MMP7 was identified as a biomarker of subclinical and clinical rejection using two-dimensional liquid chromatography tandem-mass spectrometry (LC-MS/MS) and improved the overall diagnostic discrimination of urine CXCL10 : Cr alone for renal allograft inflammation. A novel peptide signature to classify stable allografts from acute rejection, chronic allograft injury, and polyoma virus (BKV) nephropathy was identified using isobaric tag for relative and absolute quantitation (TRAQ) and label-free MS, with independent validation by selected reaction monitoring mass spectrometry (SRM-MS). Finally, an in-depth exploration of peripheral blood mononuclear cells identified differential proteoform expression in healthy transplants versus rejection.

SUMMARY

There is still much in the human proteome that remains to be explored, and further integration of renal, urinary, and exosomal data may offer deeper insight into the pathophysiology of rejection. Functional proteomics may be more biologically relevant than protein/peptide quantity alone, such as assessment of proteoforms or activity-based protein profiling. Discovery-based studies have identified potential biomarker candidates, but external validation studies are required.

Optimization for Peptide Sample Preparation for Urine Peptidomics

Analysis of native or endogenous peptides in biofluids can provide valuable insight into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for noninvasive monitoring of human diseases. The noninvasive nature of urine collection and the abundance of peptides in the urine make analysis by high-throughput "peptidomics" methods an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regard to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements, in that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS-based peptidome analysis. We report on a novel adaptation of the standard solid-phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS-based peptidomics, in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. The mSPE method provides significantly improved efficiencies for the preparation of samples from urine. The mSPE method is found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis, due to optimized sample cleanup that provides improved experimental inference from confidently identified peptides.

Understanding the Characteristics of Mass Spectrometry Data through the use of Simulation

Background

Mass spectrometry is actively being used to discover disease-related proteomic patterns in complex mixtures of proteins derived from tissue samples or from easily obtained biological fluids. The potential importance of these clinical applications has made the development of better methods for processing and analyzing the data an active area of research. It is, however, difficult to determine which methods are better without knowing the true biochemical composition of the samples used in the experiments.

Methods

We developed a mathematical model based on the physics of a simple MALDI-TOF mass spectrometer with time-lag focusing. Using this model, we implemented a statistical simulation of mass spectra. We used the simulation to explore some of the basic operating characteristics of MALDI or SELDI instruments.

Results

The simulation reproduced several characteristics of actual instruments. We found that the relative mass error is affected by the time discretization of the detector (about 0.01%) and the spread of initial velocities (about 0.1%). The accuracy of calibration based on external standards decays rapidly outside the range spanned by the calibrants. Natural isotope distributions play a major role in broadening peaks associated with individual proteins. The area of a peak is a more accurate measure of its size than the height.

Conclusions

The model described here is capable of simulating realistic mass spectra. The simulation should become a useful tool for generating spectra where the true inputs are known, allowing researchers to evaluate the performance of new methods for processing and analyzing mass spectra.

Availability

http://bioinformatics.mdanderson.org/cromwell.html

Urinary Proteomics in Predicting Heart Transplantation Outcomes (uPROPHET)-Rationale and database description

OBJECTIVES

Urinary Proteomics in Predicting Heart Transplantation Outcomes (uPROPHET; NCT03152422) aims: (i) to construct new multidimensional urinary proteomic (UP) classifiers that after heart transplantation (HTx) help in detecting graft vasculopathy, monitoring immune system activity and graft performance, and in adjusting immunosuppression; (ii) to sequence UP peptide fragments and to identify key proteins mediating HTx-related complications; (iii) to validate UP classifiers by demonstrating analogy between UP profiles and tissue proteomic signatures (TP) in diseased explanted hearts, to be compared with normal donor hearts; (iv) and to identify new drug targets. This article describes the uPROPHET database construction, follow-up strategies and baseline characteristics of the HTx patients.

METHODS

HTx patients enrolled at the University Hospital Gasthuisberg (Leuven) collected mid-morning urine samples. Cardiac biopsies were obtained at HTx. UP and TP methods and the statistical work flow in pursuit of the research objectives are described in detail in the Data supplement.

RESULTS

Of 352 participants in the UP study (24.4% women), 38.9%, 40.3%, 5.7% and 15.1% had ischemic, dilated, hypertrophic or other cardiomyopathy. The median interval between HTx and first UP assessment (baseline) was 7.8 years. At baseline, mean values were 56.5 years for age, 25.2 kg/m2 for body mass index, 142.3/84.8 mm Hg and 124.2/79.8 mm Hg for office and 24-h ambulatory systolic/diastolic pressure, and 58.6 mL/min/1.73 m2 for the estimated glomerular filtration rate. Of all patients, 37.2% and 6.5% had a history of mild (grade = 1B) or severe (grade ≥ 2) cellular rejection. Anti-body mediated rejection had occurred in 6.2% patients. The number of follow-up urine samples available for future analyses totals over 950. The TP study currently includes biopsies from 7 healthy donors and 15, 14, and 3 patients with ischemic, dilated, and hypertrophic cardiomyopathy.

CONCLUSIONS

uPROPHET constitutes a solid resources for UP and TP research in the field of HTx and has the ambition to lay the foundation for the clinical application of UP in risk stratification in HTx patients.

Whole-genome gene expression analysis in urine samples of patients with prostate cancer and benign prostate hyperplasia

OBJECTIVE

There is an urgent need to find new biomarkers with higher specificity and sensitivity for using early detection of prostate cancer (PrCa) and reducing recurrent unnecessary biopsy rates, psychological and physical stress on the patient, and costs. Being noninvasive, urine-based tests might be suitable in routine practice. The aim of this study was to report the first whole-genome gene expression analysis in urine samples, as noninvasive method, that were obtained from PrCa, benign prostate hyperplasia (BPH), and control groups by using the microarray system from Turkey, to our knowledge.

METHODS

Whole-genome gene expression profiling was conducted in urine samples of 25 patients with PrCa, 24 patients with BPH, and 11 healthy males by using the Illumina Hi Scan microarray system.

RESULTS

The number of probes showing a significant change at the level of expression were 101 and 75 in PrCa-control and BPH-control comparison groups, respectively. Further, 51 of them were the same in both comparison groups. There was no significant change at the level of expression in PrCa-BPH comparison group.

CONCLUSION

This study revealed several candidate biomarkers for early diagnosis of PrCa and contributed to the literature by detecting the differences of gene expression profiles in urine samples of PrCa-control and BPH-control comparison groups using the microarray. However, further studies are needed in larger groups.

The impact of advanced proteomics in the search for markers and therapeutic targets of bladder cancer

Bladder cancer is the most common cancer of the urinary tract and can be avoided through proper surveillance and monitoring. Several genetic factors are known to contribute to the progression of bladder cancer, many of which produce molecules that serve as cancer biomarkers. Blood, urine, and tissue are commonly analyzed for the presence of biomarkers, which can be derived from either the nucleus or the mitochondria. Recent advances in proteomics have facilitated the high-throughput profiling of data generated from bladder cancer-related proteins or peptides in parallel with high sensitivity and specificity, providing a wealth of information for biomarker discovery and validation. However, the transmission of screening results from one laboratory to another remains the main disadvantage of these methods, a fact that emphasizes the need for consistent and standardized procedures as suggested by the Human Proteome Organization. This review summarizes the latest discoveries and progress of biomarker identification for the early diagnosis, projected prognosis, and therapeutic response of bladder cancer, informs the readers of the current status of proteomic-based biomarker findings, and suggests avenues for future work.

Urinary biomarkers for renal tract malformations

INTRODUCTION

Renal tract malformations (RTMs) are congenital anomalies of the kidneys and urinary tract, which are the major cause of end-stage renal disease in children. Using immunoassay-based approaches (ELISA, western blot), individual urinary proteins including transforming growth factor β, tumor necrosis factor and monocyte attractant proteins 1 were found to be associated to RTMs. However, only mass spectrometry (MS) based methods leading to the identification of panels of protein-based markers composed of fragments of the extracellular matrix allowed the prediction of progression of RTMs and its complications. Areas covered: In this review, we summarized relevant studies identified in "Pubmed" using the keywords "urinary biomarkers" and "proteomics" and "renal tract malformations" or "hydronephrosis" or "ureteropelvic junction obstruction" or "posterior urethral valves" or "vesicoureteral reflux". These publications represent studies on potential protein-based biomarkers, either individually or combined in panels, of RTMs in human and animal models. Expert commentary: Successful use in the clinic of these protein-based biomarkers will need to involve larger scale studies to reach sufficient power. Improved performance will potentially come from combining immunoassay- and MS-based markers.

Urinary biomarkers in childhood lupus nephritis

Juvenile-onset systemic lupus erythematosus (JSLE) is a rare, severe multisystem autoimmune disease affecting the kidney (Lupus Nephritis, LN) in up to 80% of children. LN is more severe in children than adults, with potential for irreversible kidney damage requiring dialysis or transplant. Renal biopsy is currently the gold standard for diagnosing and monitoring LN, however, it is invasive and associated with complications. Urine biomarkers have been shown to be better than serum biomarkers in differentiating renal disease from other organ manifestations. Over the past decade, there have been an increasing number of studies investigating specific candidate biomarkers implicated in the pathogenesis of LN or screening for urinary biomarkers using hypothesis free methods. In this review, developments in urine biomarkers for LN will be reviewed, highlighting those that are of relevance to children and have gone through validation in independent international patient cohorts, bringing them close to clinical translation.

Acute kidney injury prediction in cardiac surgery patients by a urinary peptide pattern: a case-control validation study

Background

Acute kidney injury (AKI) is a prominent problem in hospitalized patients and associated with increased morbidity and mortality. Clinical medicine is currently hampered by the lack of accurate and early biomarkers for diagnosis of AKI and the evaluation of the severity of the disease.

In 2010, we established a multivariate peptide marker pattern consisting of 20 naturally occurring urinary peptides to screen patients for early signs of renal failure. The current study now aims to evaluate if, in a different study population and potentially various AKI causes, AKI can be detected early and accurately by proteome analysis.

Methods

Urine samples from 60 patients who developed AKI after cardiac surgery were analyzed by capillary electrophoresis-mass spectrometry (CE-MS). The obtained peptide profiles were screened by the AKI peptide marker panel for early signs of AKI. Accuracy of the proteomic model in this patient collective was compared to that based on urinary neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) ELISA levels. Sixty patients who did not develop AKI served as negative controls.

Results

From the 120 patients, 110 were successfully analyzed by CE-MS (59 with AKI, 51 controls). Application of the AKI panel demonstrated an AUC in receiver operating characteristics (ROC) analysis of 0.81 (95 % confidence interval: 0.72–0.88). Compared to the proteomic model, ROC analysis revealed poorer classification accuracy of NGAL and KIM-1 with the respective AUC values being outside the statistical significant range (0.63 for NGAL and 0.57 for KIM-1).

Conclusions

This study gives further proof for the general applicability of our proteomic multimarker model for early and accurate prediction of AKI irrespective of its underlying disease cause.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-016-1344-z) contains supplementary material, which is available to authorized users.

Significance of detection of urinary cathepsin D in patients with colorectal cancer liver metastasis

AIM: To find a more economical method for monitoring colorectal carcinoma liver metastasis by detecting whether cathepsin D can be used as a urinary biomarker of colorectal carcinoma liver metastasis.

METHODS: Random mid-stream urine samples were collected from patients with colorectal carcinoma with or without liver metastasis. The urine protein was enriched on NC membrane through pumping filtration, and Western blot was used to detect the concentration of cathepsin D after elution. Urine creatine was used to normalise the result.

RESULTS: The enriched protein showed a good quality and Western blot results indicated that the concentration of cathepsin D in urine of patients with colorectal carcinoma liver metastasis was significantly higher than those of healthy controls and CRC patients without metastasis.

CONCLUSION: The method of urine protein enrichment allows to obtain high quality urine protein quickly, and urinary cathepsin D may serve as a potential biomarker of colorectal carcinoma liver metastasis.

Biomarkers in lupus nephritis

Lupus nephritis (LN) has significant impact on the outcome of patients with systemic lupus erythematosus (SLE). In the absence of any new breakthrough for management of LN over the last few years, using existing treatment modalities in a more effective manner is the mainstay of improving outcomes. For effectively using the drugs, disease activity needs to be assessed accurately and more objectively, which is not possible with present clinical assessment tools. Biomarkers help in accurate assessment of disease activity and enable the physician to individualize the therapy. Conventional disease activity markers have limitations which need to be addressed and research in the area of biomarker discovery in LN has immensely expanded over the last two decades as evident by the literature. Moreover, biomarkers for LN should be different from the markers of overall disease activity as LN requires significant immunosuppression, unlike other non-renal manifestations of SLE. Newly discovered biomarkers exhibit qualities pertaining to different aspects of disease activity and damage. In this review, we discuss the established as well as new biomarkers of SLE in the light of their role in LN diagnosis, follow-up, prediction of renal flare and correlation with renal histology findings.

Application of Proteomics in Cancer Biomarker Discovery: GeLC-MS/MS

Proteomic approaches are being increasingly applied to study multiple facets of healthy and diseased processes. In particular, the application of global proteome profiling in the field of oncology is already starting to shape the diagnostic, prognostic, monitoring, and therapeutic approaches. At the heart of such approaches lies a quest for clinically relevant biomarkers, particularly arising from global analyses of body fluids, as, in major part, they represent easily accessible and noninvasive matrices. A detailed protocol of one of the popular approaches for global proteome profiling, SDS-PAGE-liquid chromatography-tandem mass spectrometry or GeLC-MS/MS, and its application for biomarker discovery in urine is provided here.

Comparative study of seven commercial kits for human DNA extraction from urine samples suitable for DNA biomarker-based public health studies

Human genomic DNA extracted from urine could be an interesting tool for large-scale public health studies involving characterization of genetic variations or DNA biomarkers as a result of the simple and noninvasive collection method. These studies, involving many samples, require a rapid, easy, and standardized extraction protocol. Moreover, for practicability, there is a necessity to collect urine at a moment different from the first void and to store it appropriately until analysis. The present study compared seven commercial kits to select the most appropriate urinary human DNA extraction procedure for epidemiological studies. DNA yield has been determined using different quantification methods: two classical, i.e., NanoDrop and PicoGreen, and two species-specific real-time quantitative (q)PCR assays, as DNA extracted from urine contains, besides human, microbial DNA also, which largely contributes to the total DNA yield. In addition, the kits giving a good yield were also tested for the presence of PCR inhibitors. Further comparisons were performed regarding the sampling time and the storage conditions. Finally, as a proof-of-concept, an important gene related to smoking has been genotyped using the developed tools. We could select one well-performing kit for the human DNA extraction from urine suitable for molecular diagnostic real-time qPCR-based assays targeting genetic variations, applicable to large-scale studies. In addition, successful genotyping was possible using DNA extracted from urine stored at -20°C for several months, and an acceptable yield could also be obtained from urine collected at different moments during the day, which is particularly important for public health studies.

Preanalytical Variables Affecting the Integrity of Human Biospecimens in Biobanking

BACKGROUND

Most errors in a clinical chemistry laboratory are due to preanalytical errors. Preanalytical variability of biospecimens can have significant effects on downstream analyses, and controlling such variables is therefore fundamental for the future use of biospecimens in personalized medicine for diagnostic or prognostic purposes.

CONTENT

The focus of this review is to examine the preanalytical variables that affect human biospecimen integrity in biobanking, with a special focus on blood, saliva, and urine. Cost efficiency is discussed in relation to these issues.

SUMMARY

The quality of a study will depend on the integrity of the biospecimens. Preanalytical preparations should be planned with consideration of the effect on downstream analyses. Currently such preanalytical variables are not routinely documented in the biospecimen research literature. Future studies using biobanked biospecimens should describe in detail the preanalytical handling of biospecimens and analyze and interpret the results with regard to the effects of these variables.

Mass spectral analysis of urine proteomic profiles of dairy cows suffering from clinical ketosis

BACKGROUND

Ketosis is an important metabolic disorder in dairy cows during the transition period. The urine proteomics of ketosis has not been investigated using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS).

OBJECTIVE

The aim is to determine differences between urine proteomic profiles of healthy cows and those with clinical ketosis, and facilitate studies of the underlying physiological and biochemical mechanisms that lead to liver pathology in ketosis.

ANIMALS AND METHODS

We analyzed the urine samples of 20 cows with clinical ketosis (group 1) and 20 control cows (group 2) using SELDI-TOF-MS.

RESULTS

Thirty-nine peptide peaks differed between both groups. Polypeptides corresponding to 26 of these differential peptide peaks were identified using the SWISS-PROT protein database. We found that the peaks of 11 distinct polypeptides from the urine samples of the ketosis group were significantly reduced, compared with those of the control group as based on the Wilcoxon rank sum test. Among these were VGF (non-acronymic) protein, amyloid precursor protein, serum amyloid A (SAA), fibrinogen, C1INH, apolipoprotein C-III, cystatin C, transthyretin, hepcidin, human neutrophil peptides, and osteopontin.

CONCLUSION

These proteins may represent novel biomarkers of the metabolic changes that occur in dairy cows with ketosis. Our results will help to better understand the physiological changes and pathogenesis observed in cows with ketosis.

CLINICAL IMPORTANCE

The SELDI-TOF-MS can be used to understand the physiological and biochemical mechanisms of ketosis and identify biomarkers of the disease.

The Difference Quantity of Urinary Peptides between Two Groups of Type 2 Diabetic Patients with or without Coronary Artery Disease

Objectives. We aim to explore urinary biomarkers that could monitor CAD in type 2 diabetic patients. Materials and Methods. Urine samples from two groups, twenty-eight type 2 diabetic patients with coexisting CAD and thirty type 2 diabetic patients without CAD, were purified by MB-WCX and then analyzed by MALDI-TOF-MS. Subsequently, we compared the urinary peptide signatures of the two groups by use of ClinProTools2.1 and evaluated the potential ability of the differently expressed peptides to distinguish type 2 diabetic patients with coexisting CAD from type 2 diabetic patients without CAD by ROC analysis. Finally, the differently expressed peptides were identified by nanoliquid chromatography-tandem mass spectrometry. Results. There were six differently expressed peptides (m/z 1305.2, 1743.9, 2184.9, 2756.1, 3223.2, and 6196.1) between the two groups of subjects, and they were identified as fragments of isoform 1 of fibrinogen alpha chain precursor, prothrombin precursor, and interalpha-trypsin inhibitor heavy chain H4. The diagnostic efficacy of m/z 2756.1 and m/z 3223.2 was better than the other peptides. Area under ROC of the m/z 2756.1, and m/z 3223.2 was 0.98 and 0.93, respectively. Conclusions. These urinary peptides are potential urinary biomarkers for monitoring of type 2 diabetic patients with CAD.

Urine proteomic studies in preeclampsia

Preeclampsia (PE) is a multisystem disorder of pregnancy that develops after 20 wk of gestation in previously normotensive women and complicates 5-8% of pregnancies. This rapidly progressive syndrome is usually diagnosed when the mother develops hypertension and proteinuria. The only effective treatment is delivery of the baby although early low-dose aspirin has been shown to significantly reduce the risk for PE. Recent advances in proteomic methods of protein separation, identification, and quantitation may allow for the identification of proteins and peptides that could facilitate early detection of disease, improve assessment of prognosis, and allow closer monitoring of women at risk for PE. This review summarizes all currently available markers for prediction and diagnosis of PE and presents urine proteomic studies performed for the identification of novel biomarkers.

An analysis of the impact of pre-analytical factors on the urine proteome: Sample processing time, temperature, and proteolysis

Purpose

We have examined the impact of sample processing time delay, temperature, and the addition of protease inhibitors (PIs) on the urinary proteome and peptidome, an important aspect of biomarker studies.

Experimental design

Ten urine samples from patients with varying pathologies were each divided and PIs added to one‐half, with aliquots of each then processed and frozen immediately, or after a delay of 6 h at 4°C or room temperature (20–22°C), effectively yielding 60 samples in total. Samples were then analyzed by 2D‐PAGE, SELDI‐TOF‐MS, and immunoassay.

Results

Interindividual variability in profiles was the dominant feature in all analyses. Minimal changes were observed by 2D‐PAGE as a result of delay in processing, temperature, or PIs and no changes were seen in IgG, albumin, β₂‐microglobulin, or α₁‐microglobulin measured by immunoassay. Analysis of peptides showed clustering of some samples by presence/absence of PIs but the extent was very patient‐dependent with most samples showing minimal effects.

Conclusions and clinical relevance

The extent of processing‐induced changes and the benefit of PI addition are patient‐ and sample‐dependent. A consistent processing methodology is essential within a study to avoid any confounding of the results.

Hepcidin levels in hyperprolactinemic women monitored by nanopore thin film based assay: correlation with pregnancy-associated hormone prolactin

Hepcidin is a central regulator in human iron metabolism. Although it is often regarded as a promising indicator of iron status, the lack of effective quantification method has impeded the comprehensive assessment of its physiological and clinical significance. Herein we applied a newly established, nanopore film enrichment based hepcidin assay to examine the correlation between hepcidin and prolactin, the hormone with an important role during pregnancy and lactation. Women with pathologically elevated prolactin secretion (hyperprolactinemia) were found to have lower serum hepcidin compared to those with normal prolactin levels, without showing significant difference in other hepcidin-regulating factors. Moreover, prolactin-reducing drug bromocriptine mesylate resulted in elevated expression of the hepcidin in hyperprolactinemia patients. These findings suggest a possible role of prolactin in regulation of hepcidin, and may render hepcidin a useful biomarker for progress monitoring and treatment of iron-related diseases under hyperprolactinemic conditions.

FROM THE CLINICAL EDITOR

The level of hepcidin has been shown to reflect the underlying iron status of the patient. Nonentheless, there is an urgent need of reliable, fast and easy-to-do hepcidin assay in the clinical setting. In this paper, the authors described a further modification of their previously described nanopore silica film-based enrichment approach for quantification of hepcidin and found correlation between hepcidin and prolactin. This new knowledge may add to current understanding of iron homeostasis during pregnancy.

Methods in capillary electrophoresis coupled to mass spectrometry for the identification of clinical proteomic/peptidomic biomarkers in biofluids

Proteomic biomarkers hold the promise of enabling assessment of patients according to a pathological condition aiming at improvements in diagnosis, prognosis, in general clinical patient management. Capillary electrophoresis coupled to an electrospray ionization time-of-flight mass spectrometer (CE-MS) allows the detection of thousands of small proteins and peptides in various biofluids, in a single, reproducible and time-limited step, enabling the simultaneous comparison of multiple individual proteins and peptides in biomarker discovery, but also in clinical applications. The reliability of the CE-MS platform, together with the use of a validated approach for data processing and mining is, to date, the most advanced technique for biomarker discovery of clinical significance. In this chapter, we report on the materials, methods and protocols used for CE-MS-based clinical proteomics allowing the reproducible profiling of biofluids.

Advances in urinary protein biomarkers for urogenital and non-urogenital pathologies

The discovery of protein biomarkers that reflect the biological state of the body is of vital importance to disease management. Urine is an ideal source of biomarkers that provides a non-invasive approach to diagnosis, prognosis and prediction of diseases. Consequently, the study of the human urinary proteome has increased dramatically over the last 10 years, with many studies being published. This review focuses on urinary protein biomarkers that have shown potential, in initial studies, for diseases affecting the urogenital tract, specifically chronic kidney disease and prostate cancer, as well as other non-urogenital pathologies such as breast cancer, diabetes, atherosclerosis and osteoarthritis. PubMed was searched for peer-reviewed literature on the subject, published in the last 10 years. The keywords used were "urine, biomarker, protein, and/or prostate cancer/breast cancer/chronic kidney disease/diabetes/atherosclerosis/osteoarthritis". Original studies on the subject, as well as a small number of reviews, were analysed including the strengths and weaknesses, and we summarized the performance of biomarkers that demonstrated potential. One of the biggest challenges found is that biomarkers are often shared by several pathologies so are not specific to one disease. Therefore, the trend is shifting towards implementing a panel of biomarkers, which may increase specificity. Although there have been many advances in urinary proteomics, these have not resulted in similar advancements in clinical practice due to high costs and the lack of large data sets. In order to translate these potential biomarkers to clinical practice, vigorous validation is needed, with input from industry or large collaborative studies.

Quantitative mass spectrometry of urinary biomarkers

The effectiveness of treatment of renal diseases is limited because the lack of diagnostic, prognostic and therapeutic markers. Despite the more than a decade of intensive investigation of urinary biomarkers, no new clinical biomarkers were approved. This is in part because the early expectations toward proteomics in biomarkers discovery were significantly higher than the capability of technology at the time. However, during the last decade, proteomic technology has made dramatic progress in both the hardware and software methods. In this review we are discussing modern quantitative methods of mass-spectrometry and providing several examples of their applications for discovery and validation of renal disease biomarkers. We are optimistic about future prospects for the development of novel of specific clinical urinary biomarkers.

Urinary protein biomarkers in the early detection of lung cancer

The early detection of lung cancer has the potential to greatly impact disease burden through the timely identification and treatment of affected individuals at a manageable stage of development. The insufficient specificity demonstrated by currently used screening and diagnostic techniques has led to intense investigation into biomarkers as diagnostic tools. Urine may represent a noninvasive alternative matrix for diagnostic biomarker development. We performed an analysis of 242 biomarkers in urines obtained from 83 patients with non-small cell lung carcinomas (NSCLC), 74 patients diagnosed with benign pulmonary conditions, and 77 healthy donors. A large number of significant alterations were observed between the NSCLC and control groups. A multivariate analysis identified a three-biomarker panel consisting of IGFBP-1, sIL-1Ra, CEACAM-1, which discriminated NSCLC from healthy controls with a sensitivity/specificity of 84/95 in an initial training set and 72/100 in an independent validation set. This panel performed well among multiple subtypes of NSCLC and early-stage disease but demonstrated only limited efficacy for the discrimination of NSCLC from benign controls and limited specificity for patients with several other cancers and tuberculosis. These findings demonstrate that urine biomarkers may provide screening and diagnostic properties which exceed those reported for serum biomarkers and approach a level necessary for further clinical development.

Mass spectrometry-based proteomics in Chest Medicine, Gerontology, and Nephrology: subgroups omics for personalized medicine

Mass spectrometry (MS) is currently the most promising tool for studying proteomics to investigate largescale proteins in a specific proteome. Emerging MS-based proteomics is widely applied to decipher complex proteome for discovering potential biomarkers. Given its growing usage in clinical medicine for biomarker discovery to predict, diagnose and confer prognosis, MS-based proteomics can benefit study of personalized medicine. In this review we introduce some fundamental MS theory and MS-based quantitative proteomic approaches as well as several representative clinical MS-based proteomics issues in Chest Medicine, Gerontology, and Nephrology.

Urine sample preparation for proteomic analysis

Sample preparation for both environmental and more importantly biological matrices is a bottleneck of all kinds of analytical processes. In the case of proteomic analysis this element is even more important due to the amount of cross-reactions that should be taken into consideration. The incorporation of new post-translational modifications, protein hydrolysis, or even its degradation is possible as side effects of proteins sample processing. If protocols are evaluated appropriately, then identification of such proteins does not bring difficulties. However, if structural changes are provided without sufficient attention then protein sequence coverage will be reduced or even identification of such proteins could be impossible. This review summarizes obstacles and achievements in protein sample preparation of urine for proteome analysis using different tools for mass spectrometry analysis. The main aim is to present comprehensively the idea of urine application as a valuable matrix. This article is dedicated to sample preparation and application of urine mainly in novel cancer biomarkers discovery.

From hundreds to thousands: Widening the normal human Urinome (1)

It is currently unknown how many proteins can be detected in urine. Improving the analytical approach would increase their number and potentially strengthen their predictive potential in diseases. We developed a combination of analytical procedures for maximizing sensitivity and reproducibility of normal human urinary proteome analysis based on ultracentrifugation, vesicles separation, combinatorial peptide ligand libraries (CPLL) and solvent removal of pigments. Proteins were identified by an Orbitrap Velos Mass Spectrometry. Overall, 3429 proteins were characterized: most components (1615) were contained in vesicles while the remaining 1794 were equally distributed among CPLL and butanol insoluble fractions. Several proteins were detected exclusively in one of the phases of the procedure, suggesting that each step is crucial in the fractionation strategy. Many (1724) proteins are described here whose presence in urine has never been reported and represents a potential source of information considering that urine is the unique site of excretion of products of interaction of metabolic processes. Improving the characterization of normal urinary proteome would also represent the basis for the analysis of urine biomarkers in human diseases.

BIOLOGICAL SIGNIFICANCE

Sub-fractionating normal urine by successive steps (vesicle separation, CPLL and solvent treatments) allowed the identification of 3429 proteins, a relevant part (1724) being detected for the first time in urine. Several proteins of new description have been implicated in physiology pathways and in pathologies thus representing a potential source of new information on both metabolic processes and diseases.

Peptidomics of Urine and Other Biofluids for Cancer Diagnostics

BACKGROUND

Cancer is a leading cause of death worldwide. The low diagnostic sensitivity and specificity of most current cancer biomarkers make early cancer diagnosis a challenging task. The comprehensive study of peptides and small proteins in a living system, known as “peptidomics,” represents an alternative technological approach to the discovery of potential biomarkers for the assessment of a wide variety of pathologies. This review examines the current status of peptidomics for several body fluids, with a focus on urine, for cancer diagnostics applications.

CONTENT

Several studies have used high-throughput technologies to characterize the peptide content of different body fluids. Because of its noninvasive collection and high stability, urine is a valuable source of candidate cancer biomarkers. A wide variety of preanalytical issues concerning patient selection and sample handling need to be considered, because not doing so can affect the quality of the results by introducing bias and artifacts. Optimization of both the analytical strategies and the processing of bioinformatics data is also essential to minimize the false-discovery rate.

SUMMARY

Peptidomics-based studies of urine and other body fluids have yielded a number of biomolecules and peptide panels with potential for diagnosing different types of cancer, especially of the ovary, prostate, and bladder. Large-scale studies are needed to validate these molecules as cancer biomarkers.