Recent advances in capillary electrophoresis coupled to mass spectrometry for clinical proteomic applications

Body fluid multiomics in 3PM-guided ischemic stroke management: health risk assessment, targeted protection against health-to-disease transition, and cost-effective personalized approach are envisaged

Because of its rapid progression and frequently poor prognosis, stroke is the third major cause of death in Europe and the first one in China. Many independent studies demonstrated sufficient space for prevention interventions in the primary care of ischemic stroke defined as the most cost-effective protection of vulnerable subpopulations against health-to-disease transition. Although several studies identified molecular patterns specific for IS in body fluids, none of these approaches has yet been incorporated into IS treatment guidelines. The advantages and disadvantages of individual body fluids are thoroughly analyzed throughout the paper. For example, multiomics based on a minimally invasive approach utilizing blood and its components is recommended for real-time monitoring, due to the particularly high level of dynamics of the blood as a body system. On the other hand, tear fluid as a more stable system is recommended for a non-invasive and patient-friendly holistic approach appropriate for health risk assessment and innovative screening programs in cost-effective IS management. This article details aspects essential to promote the practical implementation of highlighted achievements in 3PM-guided IS management.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00376-2.

Multi-omics research strategies in ischemic stroke: A multidimensional perspective

Ischemic stroke (IS) is a multifactorial and heterogeneous neurological disorder with high rate of death and long-term impairment. Despite years of studies, there are still no stroke biomarkers for clinical practice, and the molecular mechanisms of stroke remain largely unclear. The high-throughput omics approach provides new avenues for discovering biomarkers of IS and explaining its pathological mechanisms. However, single-omics approaches only provide a limited understanding of the biological pathways of diseases. The integration of multiple omics data means the simultaneous analysis of thousands of genes, RNAs, proteins and metabolites, revealing networks of interactions between multiple molecular levels. Integrated analysis of multi-omics approaches will provide helpful insights into stroke pathogenesis, therapeutic target identification and biomarker discovery. Here, we consider advances in genomics, transcriptomics, proteomics and metabolomics and outline their use in discovering the biomarkers and pathological mechanisms of IS. We then delineate strategies for achieving integration at the multi-omics level and discuss how integrative omics and systems biology can contribute to our understanding and management of IS.

Urinary matrix Gla protein is associated with mortality risk in Flemish population: A prospective study

Background

Vascular calcification is strongly related to the risk of mortality and cardiovascular (CV) diseases. In vascular calcification, matrix Gla protein (MGP), a small vitamin K-dependent protein, is an important mineralization inhibitor. Recent studies showed that circulating MGP is associated with mortality risk. However, the longitudinal association between urinary excretion of MGP and all-cause mortality was not established.

Materials and methods

Urinary MGP was measured in 776 randomly recruited Flemish population (mean age: 51.2 years; 50.9% women) at baseline (during 2005–2010) using capillary electrophoresis coupled with mass spectrometry. Plasma inactive MGP [desphospho-uncarboxylated MGP (dp-ucMGP)] levels were quantified in 646 individuals by ELISA kits. Mortality status was ascertained through the Belgian Population Registry until 2016. The longitudinal association with mortality was determined by the multivariate-adjusted Cox proportional hazards regression models. The multivariate linear regression models were used to identify determinants of urinary MGP level.

Results

Over the 9.2 years, 47 (6.06%) participants died, including 15 CV deaths. For a doubling of urinary MGP, the hazard ratios (HRs) were 1.31 (95% CI: 1.01–1.69, P = 0.040) for all-cause mortality and 2.05 (95% CI: 1.11–3.79, P = 0.023) for CV mortality with adjustment for covariates, including estimated glomerular filtration rate and urine microalbumin. The addition of urinary MGP to the basic models improved the reclassification as suggested by the increased net reclassification improvement [64.01% (95% CI: 32.64–98.63)] and integrated discrimination improvement [2.33% (95% CI: 0.24–4.71)]. Circulating inactive MGP, total cholesterol, urine microalbumin, and smoking were significantly associated with urinary MGP levels (P ≤ 0.041), independent of sex and age.

Conclusion

Elevated urinary MGP was associated with an increased risk of all-cause mortality and CV mortality and improved the risk reclassification for all-cause mortality. These findings suggested that urinary MGP might be useful in mortality risk assessment in the general population. However, these observations need to be replicated in larger studies with a longer follow-up time.

Urinary Proteomic Profile of Arterial Stiffness Is Associated With Mortality and Cardiovascular Outcomes

Background

The underlying mechanisms of arterial stiffness remain not fully understood. This study aimed to identify a urinary proteomic profile to illuminate its pathogenesis and to determine the prognostic value of the profile for adverse outcomes.

Methods and Results

We measured aortic stiffness using pulse wave velocity (PWV) and analyzed urinary proteome using capillary electrophoresis coupled with mass spectrometry in 669 randomly recruited Flemish patients (mean age, 50.2 years; 51.1% women). We developed a PWV‐derived urinary proteomic score (PWV‐UP) by modeling PWV with proteomics data at baseline through orthogonal projections to latent structures. PWV‐UP that consisted of 2336 peptides explained the 65% variance of PWV, higher than 36% explained by clinical risk factors. PWV‐UP was significantly associated with PWV (adjusted β=0.73 [95% CI, 0.67–0.79]; P<0.0001). Over 9.2 years (median), 36 participants died, and 75 experienced cardiovascular events. The adjusted hazard ratios (+1 SD) were 1.46 (95% CI, 1.08–1.97) for all‐cause mortality, 2.04 (95% CI, 1.07–3.87) for cardiovascular mortality, and 1.39 (95% CI, 1.11–1.74) for cardiovascular events (P≤0.031). For PWV, the corresponding estimates were 1.25 (95% CI, 0.97–1.60), 1.35 (95% CI, 0.85–2.15), and 1.22 (95% CI, 1.02–1.47), respectively (P≥0.033). Pathway analysis revealed that the peptides in PWV‐UP mostly involved multiple pathways, including collagen turnover, cell adhesion, inflammation, and lipid metabolism.

Conclusions

PWV‐UP was highly associated with PWV and could be used as a biomarker of arterial stiffness. PWV‐UP, but not PWV, was associated with all‐cause mortality and cardiovascular mortality, implying that PWV‐UP–associated peptides may be multifaceted and involved in diverse pathological processes beyond arterial stiffness.

Engineered Nanoparticle-Protein Interactions Influence Protein Structural Integrity and Biological Significance

Engineered nanoparticles (ENPs) are artificially synthesized particles with unique physicochemical properties. ENPs are being extensively used in several consumer items, elevating the probability of ENP exposure to biological systems. ENPs interact with various biomolecules like lipids, proteins, nucleic acids, where proteins are most susceptible. The ENP-protein interactions are mostly studied for corona formation and its effect on the bio-reactivity of ENPs, however, an in-depth understanding of subsequent interactive effects on proteins, such as alterations in their structure, conformation, free energy, and folding is still required. The present review focuses on ENP-protein interactions and the subsequent effects on protein structure and function followed by the therapeutic potential of ENPs for protein misfolding diseases.

Reproducibility Evaluation of Urinary Peptide Detection Using CE-MS

In recent years, capillary electrophoresis coupled to mass spectrometry (CE-MS) has been increasingly applied in clinical research especially in the context of chronic and age-associated diseases, such as chronic kidney disease, heart failure and cancer. Biomarkers identified using this technique are already used for diagnosis, prognosis and monitoring of these complex diseases, as well as patient stratification in clinical trials. CE-MS allows for a comprehensive assessment of small molecular weight proteins and peptides (<20 kDa) through the combination of the high resolution and reproducibility of CE and the distinct sensitivity of MS, in a high-throughput system. In this study we assessed CE-MS analytical performance with regards to its inter- and intra-day reproducibility, variability and efficiency in peptide detection, along with a characterization of the urinary peptidome content. To this end, CE-MS performance was evaluated based on 72 measurements of a standard urine sample (60 for inter- and 12 for intra-day assessment) analyzed during the second quarter of 2021. Analysis was performed per run, per peptide, as well as at the level of biomarker panels. The obtained datasets showed high correlation between the different runs, low variation of the ten highest average individual log2 signal intensities (coefficient of variation, CV < 10%) and very low variation of biomarker panels applied (CV close to 1%). The findings of the study support the analytical performance of CE-MS, underlining its value for clinical application.

Evaluation of a nanoflow interface based on the triple-tube coaxial sheath-flow sprayer for capillary electrophoresis-mass spectrometry coupling in metabolomics

The performance of an original CE-MS interface that allows the in-axis positioning of the electrospray with respect to the MS inlet was evaluated. The variations in the geometrical alignment of this configuration in the absence of a nebulizing gas afforded a significant reduction in the sheath-liquid flow rate from 3 µL/min to as low as 300 nL/min. The sheath liquid and BGE were respectively composed of H₂O-iPrOHCH₃COOH 50:50:1 (v/v/v) and 10% acetic acid (pH 2.2). A significant gain in sensitivity was obtained, and it was correlated to the effective mobility of the analytes. Compounds with low mobility values showed a greater sensitivity gain. Special attention was paid to the detection of proteinogenic amino acids. Linear response functions were obtained from 15 ng/mL to 500 ng/mL. The limits of quantification, as low as 34.3 ng/mL, were improved by a factor of up to six compared to the conventional configuration. The in-axis setup was ultimately applied to the absolute quantification of four important amino acids, alanine, tyrosine, methionine and valine, in standard reference material (NIST plasma). The accuracies ranged from 78 to 113%, thus demonstrating the potential of this configuration for metabolomics.

Urinary peptidomic biomarkers of renal function in heart transplant recipients

Background

Chronic kidney disease (CKD) is common in patients after heart transplantation (HTx). We assessed whether in HTx recipients the proteomic urinary classifier CKD273 or sequenced urinary peptides revealing the parental proteins correlated with the estimated glomerular filtration rate (eGFR).

Methods

In 368 HTx patients, we measured the urinary peptidome and analysed CKD273 and 48 urinary peptides with a detectable signal in >95% of participants. After 9.1 months (median), eGFR and the urinary biomarkers were reassessed.

Results

In multivariable Bonferroni-corrected analyses of the baseline data, a 1-SD increase in CKD273 was associated with a 11.4 [95% confidence interval (CI) 7.25–15.5] mL/min/1.73 m² lower eGFR and an odds ratio of 2.63 (1.56–4.46) for having eGFR <60 mL/min/1.73 m². While relating eGFR category at follow-up to baseline urinary biomarkers, CKD273 had higher (P = 0.007) area under the curve (0.75; 95% CI 0.70–0.80) than 24-h proteinuria (0.64; 95% CI 0.58–0.69), but additional adjustment for baseline eGFR removed significance of both biomarkers. In partial least squares analysis, the strongest correlates of the multivariable-adjusted baseline eGFR were fragments of collagen I (positive) and the mucin-1 subunit α (inverse). Associations between the changes in eGFR and the urinary markers were inverse for CKD273 and mucin-1 and positive for urinary collagen I.

Conclusions

With the exception of baseline eGFR, CKD273 was more closer associated with imminent renal dysfunction than 24-h proteinuria. Fragments of collagen I and mucin-1—respectively, positively and inversely associated with eGFR and change in eGFR—are single-peptide markers associated with renal dysfunction.

Analytical strategies for the determination of amino acids: Past, present and future trends

This review describes the analytical methods that have been developed over the years to tackle the high polarity and non-chromophoric nature of amino acids (AAs). First, the historical methods are briefly presented, with a strong focus on the use of derivatization reagents to make AAs detectable with spectroscopic techniques (ultraviolet and fluorescence) and/or sufficiently retained in reversed phase liquid chromatography. Then, an overview of the current analytical strategies for achiral separation of AAs is provided, in which mass spectrometry (MS) becomes the most widely used detection mode in combination with innovative liquid chromatography or capillary electrophoresis conditions to detect AAs at very low concentration in complex matrixes. Finally, some future trends of AA analysis are provided in the last section of the review, including the use of supercritical fluid chromatography (SFC), multidimensional liquid chromatography and electrophoretic separations, hyphenation of ion exchange chromatography to mass spectrometry, and use of ion mobility spectrometry mass spectrometry (IM-MS). Various application examples will also be presented throughout the review to highlight the benefits and limitations of these different analytical approaches for AAs determination.

Clinical Proteomics in Kidney Disease: From Discovery to Clinical Application

Proteome analysis has been applied in multiple studies in the context of chronic kidney disease, aiming at improving our knowledge on the molecular pathophysiology of the disease. The approach is generally based on the hypothesis that proteins are key in maintaining kidney function, and disease is a clinical consequence of a significant change of the protein level. Knowledge on critical proteins and their alteration in disease should in turn enable identification of ideal biomarkers that could guide patient management. In addition, all drugs currently employed target proteins. Hence, proteome analysis also promises to enable identifying the best suited therapeutic target, and, in combination with biomarkers, could be used as the rationale basis for personalized intervention. To assess the current status of proteome analysis in the context of CKD, we present the results of a systematic review, of up-to-date scientific research, and give an outlook on the developments that can be expected in near future. Based on the current literature, proteome analysis has already seen implementation in the management of CKD patients, and it is expected that this approach, also supported by the positive results generated to date, will see advanced high-throughput application.

Corona Isolation Method Matters: Capillary Electrophoresis Mass Spectrometry Based Comparison of Protein Corona Compositions Following On-Particle versus In-Solution or In-Gel Digestion

Increased understanding of the role of the nanomaterial protein corona in driving nanomaterial uptake into, and impacts on, cells and organisms, and the consequent need for characterization of the corona, has led to a flourishing of methods for isolation and analysis of the constituent proteins over the past decade. However, despite over 700 corona studies to date, very little is understood in terms of which methods provide the most precise and comprehensive characterization of the corona. With the increasing importance of the modeling of corona formation and its correlation with biological impacts, it is timely to properly characterize and validate the isolation approaches used to determine the protein corona. The current work introduces Capillary Electrophoresis with Electro Spray Ionization Mass Spectrometry (CESI-MS) as a novel method for protein corona characterizations and develops an on-particle tryptic digestion method, comparing peptide solubilization solutions and characterizing the recovery of proteins from the nanomaterial surface. The CESI-MS was compared to the gold standard nano-LC-MS for corona analysis and maintained a high degree of reproducibility, while increasing throughput by >3-fold. The on-particle digestion is compared to an in-solution digestion and an in-gel digestion of the protein corona. Interestingly, a range of different protein classes were found to be recovered to greater or lesser extents among the different methods. Apolipoproteins were detected at lower concentrations when a surfactant was used to solubilize peptides, whereas immunoglobulins in general have a high affinity for nanomaterials, and thus show lower recovery using on-particle digestion. The optimized on-particle digestion was validated using 6 nanomaterials and proved capable of recovering in excess of 97% of the protein corona. These are important factors to consider when designing corona studies and modeling corona formation and impacts, highlighting the significance of a comprehensive validation of nanomaterial corona analysis methods.

Urinary proteome signature of Renal Cysts and Diabetes syndrome in children

Renal Cysts and Diabetes Syndrome (RCAD) is an autosomal dominant disorder caused by mutations in the HNF1B gene encoding for the transcriptional factor hepatocyte nuclear factor-1B. RCAD is characterized as a multi-organ disease, with a broad spectrum of symptoms including kidney abnormalities (renal cysts, renal hypodysplasia, single kidney, horseshoe kidneys, hydronephrosis), early-onset diabetes mellitus, abnormal liver function, pancreatic hypoplasia and genital tract malformations. In the present study, using capillary electrophoresis coupled to mass spectrometry (CE-MS), we investigated the urinary proteome of a pediatric cohort of RCAD patients and different controls to identify peptide biomarkers and obtain further insights into the pathophysiology of this disorder. As a result, 146 peptides were found to be associated with RCAD in 22 pediatric patients when compared to 22 healthy age-matched controls. A classifier based on these peptides was generated and further tested on an independent cohort, clearly discriminating RCAD patients from different groups of controls. This study demonstrates that the urinary proteome of pediatric RCAD patients differs from autosomal dominant polycystic kidney disease (PKD1, PKD2), congenital nephrotic syndrome (NPHS1, NPHS2, NPHS4, NPHS9) as well as from chronic kidney disease conditions, suggesting differences between the pathophysiology behind these disorders.

Early detection of organ involvement in Fabry disease by biomarker assessment in conjunction with LGE cardiac MRI: results from the SOPHIA study

BACKGROUND

Initiation of enzyme replacement therapy (ERT) early in the Fabry disease course may facilitate better outcomes than in patients with advanced disease. Early diagnosis is often hindered by the heterogeneous nature of signs and symptoms, and by the presentation of atypical phenotypes.

METHODS

The Sophisticated Assessment of Disease Burden in Patients with Fabry Disease study (SOPHIA; ClinicalTrials.gov, NCT01210196) evaluated clinical and diagnostic assessments for early detection of Fabry-related organ pathology in ERT-naïve patients with mild FD symptoms. Assessments included cardiac magnetic resonance imaging with late gadolinium enhancement (LGE-CMR), echocardiography, 24-h Holter electrocardiography, and biomarkers of FD and fibrosis.

RESULTS

35 patients with mean (SD) baseline age of 45.0 (10.2) years were included and assessed at baseline, 12 months, and (optionally) at 24 months. At baseline, LGE-CMR and elevated procollagen III N-terminal propeptide, sphingosine-1-phosphate, and globotriaosylsphingosine were the most prevalent indicators of early Fabry-related pathology. LGE was already present in 58.8% of patients with normal left ventricular mass index. 15.2% of patients showed grade 1 diastolic dysfunction. QRS duration increased from baseline to last observation, particularly in patients with severe baseline fibrosis. Fibrosis progressed from baseline to last observation, especially in patients with baseline LGE ≥ 2.50 mL (3.65 [1.14] mL vs 6.74 [1.10] mL). Statistically significant correlations were found between LGE volume and high-sensitivity troponin T, and between LGE volume and fragments of urinary collagen alpha-1 (I), (III), and (VII), and collagen alpha-3 (V).

CONCLUSIONS

Fibrosis may become apparent before left ventricular hypertrophy occurs. LGE-CMR imaging is superior to conventional echocardiography for detecting early cardiomyopathy in FD and, in conjunction with biomarker tests, may help detect early organ involvement in mild FD.

Urinary Proteomics as a Tool to Identify Kidney Responders to Dipeptidyl Peptidase-4 Inhibition: A Hypothesis-Generating Analysis from the MARLINA-T2D Trial

PURPOSE

Chronic kidney disease (CKD) is a serious complication of hyperglycemia and treatment options to slow its progression are scarce. Dipeptidyl peptidase-4 (DPP-4) inhibitors are common glucose-lowering drugs in type 2 diabetes (T2D). Among these, linagliptin has been suggested to exert kidney protective effects. It is investigated whether an effect of linagliptin on kidney function could be unmasked by characterizing the urinary proteome profile (UPP) in albuminuric T2D individuals.

EXPERIMENTAL DESIGN

Participants of the MARLINA-T2D trial (NCT01792518) are randomized 1:1 to receive either linagliptin 5 mg or placebo for 24 weeks. A previously developed proteome-based classifier, CKD273, is assessed.

RESULTS

Results confirm a significant correlation between CKD273 and clinical kidney parameters as well as with eGFR decline. Patient stratification using CKD273 at baseline, show a trend toward attenuation of renal function loss in high CKD-risk patients treated with linagliptin. Moreover, characterized are linagliptin affected peptides of which the majority contained a DPP-4 target sequence.

CONCLUSIONS AND CLINICAL RELEVANCE

CKD273 is a promising tool for identifying patients at high risk for CKD progression and may unmask a potential of linagliptin to slow progressive kidney function loss in high CKD-risk patients. UPP characterization reveals a significant impact of linagliptin on urinary peptides.

Proteomics biomarkers for solid tumors: Current status and future prospects

Cancer is a heterogeneous multifactorial disease, which continues to be one of the main causes of death worldwide. Despite the extensive efforts for establishing accurate diagnostic assays and efficient therapeutic schemes, disease prevalence is on the rise, in part, however, also due to improved early detection. For years, studies were focused on genomics and transcriptomics, aiming at the discovery of new tests with diagnostic or prognostic potential. However, cancer phenotypic characteristics seem most likely to be a direct reflection of changes in protein metabolism and function, which are also the targets of most drugs. Investigations at the protein level are therefore advantageous particularly in the case of in-depth characterization of tumor progression and invasiveness. Innovative high-throughput proteomic technologies are available to accurately evaluate cancer formation and progression and to investigate the functional role of key proteins in cancer. Employing these new highly sensitive proteomic technologies, cancer biomarkers may be detectable that contribute to diagnosis and guide curative treatment when still possible. In this review, the recent advances in proteomic biomarker research in cancer are outlined, with special emphasis placed on the identification of diagnostic and prognostic biomarkers for solid tumors. In view of the increasing number of screening programs and clinical trials investigating new treatment options, we discuss the molecular connections of the biomarkers as well as their potential as clinically useful tools for diagnosis, risk stratification and therapy monitoring of solid tumors.

Probing the endogenous peptidomes of cancer for biomarkers: A new endeavor

The life span of cancer patients can be prolonged with appropriate therapies if detected early. Mass screening for early detection of cancer, however, requires sensitive and specific biomarkers obtainable from body fluids such as blood or urine. To date, most biomarker discovery programs focus on the proteome rather than the endogenous peptidome. It has been long-established that tumor cells and stromal cells produce tumor resident proteases (TRPs) to remodel the surrounding tumor microenvironment in support of tumor progression. In fact, proteolytic products of TRPs have been shown to correlate with malignant behavior. Being of low molecular weight, these unique peptides can pass through the endothelial barrier of the vasculature into the bloodstream. As such, the cancer peptidome has increasingly become a focus for biomarker discovery. In this review, we discuss on the various aspects of the peptidome in cancer biomarker research.

Urinary proteomic biomarkers in oncology: ready for implementation?

Introduction: Biomarkers are expected to improve the management of cancer patients by enabling early detection and prediction of therapeutic response. Proteins reflect a molecular phenotype, have high potential as biomarkers, and also are key targets for intervention. Given the ease of collection and proximity to certain tumors, the urinary proteome is a rich source of biomarkers and several proteins have been already implemented. Areas covered: We examined the literature on urine proteins and proteome analysis in oncology from reports published during the last 5 years to generate an overview on the status of urine protein and peptide biomarkers, with emphasis on their actual clinical value. Expert commentary: A few studies report on biomarkers that are ready to be implemented in patient management, among others in bladder cancer and cholangiocarcinoma. These reports are based on multi-marker approaches. A high number of biomarkers, though, has been described in studies with low statistical power. In fact, several of them have been consistently reported across different studies. The latter should be the focus of attention and be tested in properly designed confirmatory and ultimately, prospective investigations. It is expected that multi-marker classifiers for a specific context-of-use, will be the preferred path toward clinical implementation.

Novel Urinary Biomarkers For Improved Prediction Of Progressive Egfr Loss In Early Chronic Kidney Disease Stages And In High Risk Individuals Without Chronic Kidney Disease

Chronic kidney disease is associated with increased risk of CKD progression and death. Therapeutic approaches to limit progression are limited. Developing tools for the early identification of those individuals most likely to progress will allow enriching clinical trials in high risk early CKD patients. The CKD273 classifier is a panel of 273 urinary peptides that enables early detection of CKD and prognosis of progression. We have generated urine capillary electrophoresis-mass spectrometry-based peptidomics CKD273 subclassifiers specific for CKD stages to allow the early identification of patients at high risk of CKD progression. In the validation cohort, the CKD273 subclassifiers outperformed albuminuria and CKD273 classifier for predicting rapid loss of eGFR in individuals with baseline eGFR > 60 ml/min/1.73 m². In individuals with eGFR > 60 ml/min/1.73 m² and albuminuria <30 mg/day, the CKD273 subclassifiers predicted rapid eGFR loss with AUC ranging from 0.797 (0.743-0.844) to 0.736 (0.689-0.780). The association between CKD273 subclassifiers and rapid progression remained significant after adjustment for age, sex, albuminuria, DM, baseline eGFR, and systolic blood pressure. Urinary peptidomics CKD273 subclassifiers outperformed albuminuria and CKD273 classifier for predicting the risk of rapid CKD progression in individuals with eGFR > 60 ml/min/1.73 m². These CKD273 subclassifiers represented the earliest evidence of rapidly progressive CKD in non-albuminuric individuals with preserved renal function.

Noninvasive diagnosis of chronic kidney diseases using urinary proteome analysis

Background

In spite of its invasive nature and risks, kidney biopsy is currently required for precise diagnosis of many chronic kidney diseases (CKDs). Here, we explored the hypothesis that analysis of the urinary proteome can discriminate different types of CKD irrespective of the underlying mechanism of disease.

Methods

We used data from the proteome analyses of 1180 urine samples from patients with different types of CKD, generated by capillary electrophoresis coupled to mass spectrometry. A set of 706 samples served as the discovery cohort, and 474 samples were used for independent validation. For each CKD type, peptide biomarkers were defined using statistical analysis adjusted for multiple testing. Potential biomarkers of statistical significance were combined in support vector machine (SVM)-based classifiers.

Results

For seven different types of CKD, several potential urinary biomarker peptides (ranging from 116 to 619 peptides) were defined and combined into SVM-based classifiers specific for each CKD. These classifiers were validated in an independent cohort and showed good to excellent accuracy for discrimination of one CKD type from the others (area under the receiver operating characteristic curve ranged from 0.77 to 0.95). Sequence analysis of the biomarkers provided further information that may clarify the underlying pathophysiology.

Conclusions

Our data indicate that urinary proteome analysis has the potential to identify various types of CKD defined by pathological assessment of renal biopsies and current clinical practice in general. Moreover, these approaches may provide information to model molecular changes per CKD.

A urinary proteome-based classifier for the early detection of decline in glomerular filtration

Background

Chronic kidney disease (CKD) progression is currently assessed by a decline in estimated glomerular filtration rate (eGFR) and/or an increase in urinary albumin excretion (UAE). However, these markers are considered either to be late-stage markers or to have low sensitivity or specificity. In this study, we investigated the performance of the urinary proteome-based classifier CKD273, compared with UAE, in a number of different narrow ranges of CKD severity, with each range separated by an eGFR of 10 mL/min/1.73 m 2 .

Methods

A total of 2672 patients with different CKD stages were included in the study. Of these, 394 individuals displayed a decline in eGFR of >5 mL/min/1.73 m 2 /year (progressors) and the remaining individuals were considered non-progressors. For all samples, UAE values and CKD273 classification scores were obtained. To assess UAE values and CKD273 scores at different disease stages, the cohort was divided according to baseline eGFRs of ≥80, 70-79, 60-69, 50-59, 40-49, 30-39 and <29 mL/min/1.73 m 2 . In addition, areas under the curve for CKD273 and UAE were calculated.

Results

In early stage CKD, the urinary proteome-based classifier performed significantly better than UAE in detecting progressors. In contrast, UAE performed better in patients with late-stage CKD. No significant difference in performance was found between CKD273 and UAE in patients with moderately reduced renal function.

Conclusions

These results suggest that urinary peptides, as combined in the CKD273 classifier, allow the detection of progressive CKD at early stages, a point where therapeutic intervention is more likely to be effective. However, late-stage disease, where irreversible damage of the kidney is already present, is better detected by UAE.

Enhanced Microchip Electrophoresis Separations Combined with Electrochemical Detection Utilizing a Capillary Embedded in Polystyrene

The ability to use microchip-based electrophoresis for fast, high-throughput separations provides researchers with a tool for close-to real time analysis of biological systems. While PDMS-based electrophoresis devices are popular, the separation efficiency is often an issue due to the hydrophobic nature of PDMS. In this study, a hybrid microfluidic capillary device was fabricated to utilize the positive features of PDMS along with the electrophoretic performance of fused silica. A capillary loop was embedded in a polystyrene base that can be coupled with PDMS microchannels at minimal dead volume interconnects. A method for cleaning out the capillaries after a wet-polishing step was devised through the use of 3D printed syringe attachment. By comparing the separation efficiency of fluorescein and CBI-glycine with both a PDMS-based serpentine device and the embedded capillary loop device, it was shown that the embedded capillary loop device maintained higher theoretical plates for both analytes. A Pd decoupler with a carbon or Pt detection electrode were embedded along with the loop allowing integration of the electrophoretic separation with electrochemical detection. A series of catecholamines were separated to show the ability to resolve similar analytes and detect redox active species. The release of dopamine and norepinephrine from PC 12 cells was also analyzed showing the compatibility of these improved microchip separations with high ionic cell buffers associated with cell culture.

Advances in mass spectrometry-based metabolomics for investigation of metabolites

Metabolomics is the systematic study of all the metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing over an extensive dynamic range in biological samples. Diverse analytical techniques are needed to achieve higher coverage of metabolites. The application of mass spectrometry (MS) in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques. Significant advances have also occurred in separation-based MS techniques (gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and ion mobility-mass spectrometry), as well as separation-free MS techniques (direct infusion-mass spectrometry, matrix-assisted laser desorption ionization-mass spectrometry, mass spectrometry imaging, and direct analysis in real time mass spectrometry) in the past decades. This review presents a brief overview of the recent advanced MS techniques and their latest applications in metabolomics. The software/websites for MS result analyses are also reviewed.

Metabolomics is the systematic study of all the metabolites present within a biological system, supply functional information and has received extensive attention in the field of life sciences.

Recent trends in capillary electrophoresis for complex samples analysis: A review

CE has been a continuously evolving analytical methodology since its first introduction in the 1980s of the last century. The development of new CE separation procedures, the coupling of these systems to more sensitive and versatile detection systems, and the advances in miniaturization technology have allowed the application of CE to the resolution of new and complex analytical problems, overcoming the traditional disadvantages associated with this method. In the present work, different recent trends in CE and their application to the determination of high complexity samples (as biological fluids, individual cells, etc.) will be reviewed: capillary modification by different types of coatings, microfluidic CE, and online microextraction CE. The main advantages and disadvantages of the different proposed approaches will be discussed with examples of most recent applications.

Prediction of Chronic Kidney Disease Stage 3 by CKD273, a Urinary Proteomic Biomarker

Introduction

CKD273 is a urinary biomarker, which in advanced chronic kidney disease predicts further deterioration. We investigated whether CKD273 can also predict a decline of estimated glomerular filtration rate (eGFR) to <60 ml/min per 1.73 m².

Methods

In analyses of 2087 individuals from 6 cohorts (46.4% women; 73.5% with diabetes; mean age, 46.1 years; eGFR ≥ 60 ml/min per 1.73 m², 100%; urinary albumin excretion rate [UAE] ≥20 μg/min, 6.2%), we accounted for cohort, sex, age, mean arterial pressure, diabetes, and eGFR at baseline and expressed associations per 1-SD increment in urinary biomarkers.

Results

Over 5 (median) follow-up visits, eGFR decreased more with higher baseline CKD273 than UAE (1.64 vs. 0.82 ml/min per 1.73 m²; P < 0.0001). Over 4.6 years (median), 390 participants experienced a first renal endpoint (eGFR decrease by ≥10 to <60 ml/min per 1.73 m²), and 172 experienced an endpoint sustained over follow-up. The risk of a first and sustained renal endpoint increased with UAE (hazard ratio ≥ 1.23; P ≤ 0.043) and CKD273 (≥ 1.20; P ≤ 0.031). UAE (≥20 μg/min) and CKD273 (≥0.154) thresholds yielded sensitivities of 30% and 33% and specificities of 82% and 83% (P ≤ 0.0001 for difference between UAE and CKD273 in proportion of correctly classified individuals). As continuous markers, CKD273 (P = 0.039), but not UAE (P = 0.065), increased the integrated discrimination improvement, while both UAE and CKD273 improved the net reclassification index (P ≤ 0.0003), except for UAE per threshold (P = 0.086).

Discussion

In conclusion, while accounting for baseline eGFR, albuminuria, and covariables, CKD273 adds to the prediction of stage 3 chronic kidney disease, at which point intervention remains an achievable therapeutic target.

The effect of sodium/glucose cotransporter 2 (SGLT2) inhibition on the urinary proteome

Treatment with empagliflozin, an inhibitor of the sodium/glucose cotransporter 2 (SGLT2), is associated with slower progression of diabetic kidney disease. In this analysis, we explored the hypothesis that empagliflozin may have an impact on urinary peptides associated with chronic kidney disease (CKD). In this post-hoc, exploratory analysis, we investigated urine samples obtained from 40 patients with uncomplicated type 1 diabetes (T1D) before and after treatment with empagliflozin for 8 weeks to for significant post-therapy changes in urinary peptides. We further assessed the association of these changes with CKD in an independent cohort, and with a previously established urinary proteomic panel, termed CKD273. 107 individual peptides significantly changed after treatment. The majority of the empagliflozin-induced changes were in the direction of “CKD absent” when compare to patients with CKD and controls. A classifier consisting of these 107 peptides scored significantly different in controls, in comparison to CKD patients. However, empagliflozin did not impact the CKD273 classifier. Our data indicate that empagliflozin induces multiple significant changes in the urinary proteomic markers such as mucin and clusterin. The relationship between empagliflozin-induced proteomic changes and clinical outcomes merits further investigation.

Novel Urinary Peptidomic Classifier Predicts Incident Heart Failure

BACKGROUND

Detection of preclinical cardiac dysfunction and prognosis of left ventricular heart failure (HF) would allow targeted intervention, and appears to be the most promising approach in its management. Novel biomarker panels may support this approach and provide new insights into the pathophysiology.

METHODS AND RESULTS

A retrospective comparison of urinary proteomic profiles generated by mass spectrometric analysis from 49 HF patients, 36 patients who progressed to HF within 2.6±1.6 years, and 192 sex- and age-matched controls who did not progress to HF enabled identification of 96 potentially HF-specific peptide biomarkers. Based on these 96 peptides, the classifier called Heart Failure Predictor (HFP) was established by support vector machine modeling. The incremental prognostic value of HFP was subsequently evaluated in urine samples from 175 individuals with asymptomatic diastolic dysfunction from an independent population cohort. Within 4.8 years, 17 of these individuals progressed to overt HF. The area under receiver-operating characteristic curve was 0.70 (95% CI, 0.56-0.82); P=0.0047 for HFP and 0.57 (0.42-0.72; P=0.62) for N-terminal pro b-type natriuretic peptide. Hazard ratios were 1.63 (CI, 1.04-2.55; P=0.032) per 1-SD increment in HFP and 0.70 (CI, 0.35-1.41; P=0.32) for a doubling of the logarithmically transformed N-terminal pro b-type natriuretic peptide.

CONCLUSIONS

HFP is a novel biomarker derived from the urinary proteome and might serve as a sensitive tool to improve risk stratification, patient management, and understanding of the pathophysiology of HF.

Urine peptidomic biomarkers for diagnosis of patients with systematic lupus erythematosus

Background Systematic lupus erythematosus (SLE) is characterized with various complications which can cause serious organ damage in the human body. Despite the significant improvements in disease management of SLE patients, the non-invasive diagnosis is entirely missing. In this study, we used urinary peptidomic biomarkers for early diagnosis of disease onset to improve patient risk stratification, vital for effective drug treatment. Methods Urine samples from patients with SLE, lupus nephritis (LN) and healthy controls (HCs) were analyzed using capillary electrophoresis coupled to mass spectrometry (CE-MS) for state-of-the-art biomarker discovery. Results A biomarker panel made up of 65 urinary peptides was developed that accurately discriminated SLE without renal involvement from HC patients. The performance of the SLE-specific panel was validated in a multicentric independent cohort consisting of patients without SLE but with different renal disease and LN. This resulted in an area under the receiver operating characteristic (ROC) curve (AUC) of 0.80 ( p < 0.0001, 95% confidence interval (CI) 0.65-0.90) corresponding to a sensitivity and a specificity of 83% and 73%, respectively. Based on the end terminal amino acid sequences of the biomarker peptides, an in silico methodology was used to identify the proteases that were up or down-regulated. This identified matrix metalloproteinases (MMPs) as being mainly responsible for the peptides fragmentation. Conclusions A laboratory-based urine test was successfully established for early diagnosis of SLE patients. Our approach determined the activity of several proteases and provided novel molecular information that could potentially influence treatment efficacy.

Urinary proteomics can define distinct diagnostic inflammatory arthritis subgroups

Current diagnostic tests applied to inflammatory arthritis lack the necessary specificity to appropriately categorise patients. There is a need for novel approaches to classify patients with these conditions. Herein we explored whether urinary proteomic biomarkers specific for different forms of arthritis (rheumatoid arthritis (RA), psoriatic arthritis (PsA), osteoarthritis (OA)) or chronic inflammatory conditions (inflammatory bowel disease (IBD)) can be identified. Fifty subjects per group with RA, PsA, OA or IBD and 50 healthy controls were included in the study. Two-thirds of these populations were randomly selected to serve as a training set, while the remaining one-third was reserved for validation. Sequential comparison of one group to the other four enabled identification of multiple urinary peptides significantly associated with discrete pathological conditions. Classifiers for the five groups were developed and subsequently tested blind in the validation test set. Upon unblinding, the classifiers demonstrated excellent performance, with an area under the curve between 0.90 and 0.97 per group. Identification of the peptide markers pointed to dysregulation of collagen synthesis and inflammation, but also novel inflammatory markers. We conclude that urinary peptide signatures can reliably differentiate between chronic arthropathies and inflammatory conditions with discrete pathogenesis.

Prediction of Proteases Involved in Peptide Generation

Clinical proteomics has led to the identification of a substantial number of disease-associated peptides and protein fragments in several conditions such as cancer, kidney, or cardiovascular diseases. In silico prediction tools that can facilitate linking of identified peptide biomarkers to predicted protease activity might therefore significantly contribute to the understanding of pathophysiological mechanisms of these diseases. Proteasix is an open-source, peptide-centric tool that can be used to predict in silico the proteases involved in naturally occurring peptide generation. From an input peptide list, Proteasix allows for automatic cleavage site reconstruction and protease associations.

Urinary Proteomics for Diagnosis and Monitoring of Diabetic Nephropathy

The last decade has seen a surge in publications describing novel biomarkers for early detection of diabetic nephropathy (DN), but as yet none have outperformed albuminuria in well-designed prospective studies. This is partially attributable to our incomplete understanding of the many complex interrelated mechanisms underlying DN development, a heterogeneous process unlikely to be captured by a single biomarker. Proteomics offers the advantage of simultaneously analysing the entire protein content of a biological sample, and the technique has gained attention as a potential tool for a more accurate diagnosis of disease at an earlier stage as well as a means by which to unravel the pathogenesis of complex diseases such as DN using an untargeted approach. This review will discuss the potential of proteomics as both a clinical and research tool, evaluating exploratory work in animal models as well as diagnostic potential in human subjects.

Identification of ageing-associated naturally occurring peptides in human urine

To assess normal and pathological peptidomic changes that may lead to an improved understanding of molecular mechanisms underlying ageing, urinarypeptidomes of 1227 healthy and 10333 diseased individuals between 20 and 86 years of age were investigated. The diseases thereby comprised diabetes mellitus, renal and cardiovascular diseases. Using age as a continuous variable, 116 peptides were identified that significantly (p < 0.05; |ρ|≥0.2) correlated with age in the healthy cohort. The same approach was applied to the diseased cohort. Upon comparison of the peptide patterns of the two cohorts 112 common age-correlated peptides were identified. These 112 peptides predominantly originated from collagen, uromodulin and fibrinogen. While most fibrillar and basement membrane collagen fragments showed a decreased age-related excretion, uromodulin, beta-2-microglobulin and fibrinogen fragments showed an increase. Peptide-based in silico protease analysis was performed and 32 proteases, including matrix metalloproteinases and cathepsins, were predicted to be involved in ageing. Identified peptides, predicted proteases and patient information were combined in a systems biology pathway analysis to identify molecular pathways associated with normal and/or pathological ageing. While perturbations in collagen homeostasis, trafficking of toll-like receptors and endosomal pathways were commonly identified, degradation of insulin-like growth factor-binding proteins was uniquely identified in pathological ageing.

Pro: urine proteomics as a liquid kidney biopsy: no more kidney punctures!

In this article, the benefits of urinary proteomics in comparison with kidney biopsy are discussed. The majority of urinary proteins are generated by the kidney, hence the urinary proteome holds substantial information on the kidney, and assessment of the urinary proteome could be considered a 'liquid biopsy'. The main question is how well the information contained in the urinary proteome can be assessed today, if it is ready to be routinely used, and what are the advantages and possible disadvantages in comparison with current standards. Since chronic kidney disease (CKD) is by far the largest area in nephrology based on the number of patients affected, the focus of this article is on CKD. Substantial progress was made in the last decade in urinary proteomics, and today we have comparable urinary proteome datasets of tens of thousands of subjects available. Clinical proteomics studies in CKD including close to, or even exceeding, 1000 subjects have recently been published, demonstrating a benefit over the current state-of-the-art in diagnosis and especially prognosis. The first large multicentric randomized controlled intervention trial aiming at preventing CKD by employing urinary proteomics-guided intervention has been initiated recently. These data provide ample evidence for the utility and value of urinary proteomics in nephrology. A further consideration is that the purpose of the biopsy, be it 'liquid' or 'solid', is to guide intervention. However, essentially all drug targets are proteins, not microscopic structures. Therefore, obtaining information on the proteome to guide intervention appears to be the most appropriate approach. Presenting more detailed evidence, I argue that urinary proteome analysis can, in most cases, be employed to guide therapeutic intervention, can be repeated multiple times as it is without any direct risk or discomfort and can be considered as a liquid biopsy.

Urine proteome analysis as a discovery tool in patients with deep vein thrombosis and pulmonary embolism

PURPOSE

Early and accurate detection of deep vein thrombosis (DVT) is an important clinical need. Based on the hypothesis that urinary peptides may hold information on DVT in conjunction with pulmonary embolism (PE), the study was aimed at identifying such peptide biomarkers using capillary electrophoresis coupled mass spectrometry.

EXPERIMENTAL DESIGN

Patients with symptoms of unprovoked/idiopathic DVT and/or PE were examined by doppler-sonography or angio-computed tomography. Urinary proteome analysis allowed for identification of respective peptide biomarkers. To confirm their biological relevance, we induced PE in mice and assessed human ex vivo thrombi.

RESULTS

We identified 62 urinary peptides as DVT-specific biomarkers, i.e. fragments of collagen type I and a fragment of fibrinogen β-chain. The presence of fibrinogen α/β in the acute thrombus, and collagen type I and osteopontin in the older, organized thrombus was demonstrated. The classifier DVT62 established through support vector machine (SVM) modeling based on the 62 identified peptides was validated in an independent cohort of 47 subjects (six cases and 41 controls) with a sensitivity of 100% and specificity of 83%.

CONCLUSIONS AND CLINICAL RELEVANCE

Urine proteome analysis enabled the detection of DVT-specific peptides, which were validated in human and mouse tissue. Furthermore, it allowed for the establishment of an urinary-proteome based classifier that is relatively specific for DVT. The data provide the basis for assessment of these biomarkers in a prospective clinical study.

Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy in TYpe 2 diabetic patients with normoalbuminuria (PRIORITY): essential study design and rationale of a randomised clinical multicentre trial

INTRODUCTION

Diabetes mellitus affects 9% of the European population and accounts for 15% of healthcare expenditure, in particular, due to excess costs related to complications. Clinical trials aiming for earlier prevention of diabetic nephropathy by renin angiotensin system blocking treatment in normoalbumuric patients have given mixed results. This might reflect that the large fraction of normoalbuminuric patients are not at risk of progression, thereby reducing power in previous studies. A specific risk classifier based on urinary proteomics (chronic kidney disease (CKD)273) has been shown to identify normoalbuminuric diabetic patients who later progressed to overt kidney disease, and may hold the potential for selection of high-risk patients for early intervention. Combining the ability of CKD273 to identify patients at highest risk of progression with prescription of preventive aldosterone blockade only to this high-risk population will increase power. We aim to confirm performance of CKD273 in a prospective multicentre clinical trial and test the ability of spironolactone to delay progression of early diabetic nephropathy.

METHODS AND ANALYSIS

Investigator-initiated, prospective multicentre clinical trial, with randomised double-masked placebo-controlled intervention and a prospective observational study. We aim to include 3280 type 2 diabetic participants with normoalbuminuria. The CKD273 classifier will be assessed in all participants. Participants with high-risk pattern are randomised to treatment with spironolactone 25 mg once daily, or placebo, whereas, those with low-risk pattern will be observed without intervention other than standard of care. Treatment or observational period is 3 years.The primary endpoint is development of confirmed microalbuminuria in 2 of 3 first morning voids urine samples.

ETHICS AND DISSEMINATION

The study will be conducted under International Conference on Harmonisation - Good clinical practice (ICH-GCP) requirements, ethical principles of Declaration of Helsinki and national laws. This first new biomarker-directed intervention trial aiming at primary prevention of diabetic nephropathy may pave the way for personalised medicine approaches in treatment of diabetes complications.

TRIAL REGISTRATION NUMBER

NCT02040441; Pre-results.

CE-ESI-MS for bottom-up proteomics: Advances in separation, interfacing and applications

With the development of more sensitive hyphenation strategies for capillary electrophoresis-electrospray-mass spectrometry the technique has reemerged as technique with high separation power combined with high sensitivity in the analysis of peptides and protein digests. This review will discuss the newly developed hyphenation strategies for CE-ESI-MS and their application in bottom-up proteomics as well as the applications in the same time span, 2009 to present, using co-axial sheathliquid. Subsequently all separate aspects in the development of a CE-ESI-MS method for bottom-up proteomics shall be discussed, highlighting certain applications and discussing pros and cons of the various choices. The separation of peptides in a capillary electrophoresis system is discussed including the great potential for modeling of this migration of peptides due to the simple electrophoretic separation process. Furthermore, the technical aspects of method development are discussed, namely; background electrolyte choice, coating of the separation capillary and chosen loading method. Finally, conclusions and an outlook on future developments in the field of bottom-up proteomics by CE-ESI-MS will be provided.

Implementation of CE-MS-identified proteome-based biomarker panels in drug development and patient management

The recent advancements in clinical proteomics enabled identification of biomarker panels for a large range of diseases. A number of CE-MS-identified biomarker panels were verified and implemented in clinical studies. Despite multiple challenges, accumulating evidence supports the value and the need for proteome-based biomarker panels. In this perspective, we provide an overview of clinical studies indicating the added value of CE-MS biomarker panels over traditional diagnostics and monitoring methods. We outline apparent advantages of applying novel proteomic biomarker panels for disease diagnosis, prognosis, staging, drug development and patient management. Facing the plethora of benefits associated with the use of CE-MS biomarker panels, we envision their implementation into the medical practice in the near future.

Separation of Peptides by Capillary Electrophoresis

Peptides are an important class of analytes in chemistry, biochemistry, food chemistry, as well as medical and pharmaceutical sciences including biomarker analysis in peptidomics and proteomics. As a high-resolution technique, capillary electrophoresis (CE) is well suited for the analysis of polar compounds such as peptides. In addition, CE is orthogonal to high-performance liquid chromatography (HPLC) as both techniques are based on different physicochemical separation principles. For the successful development of peptide separations by CE, operational parameters including puffer pH, buffer concentration and buffer type, applied voltage, capillary dimensions, as well as background electrolyte additives such as detergents, ion-pairing reagents, cyclodextrins, (poly)amines, and soluble polymers have to be considered and optimized.

Heat shock proteins and hormesis in the diagnosis and treatment of neurodegenerative diseases

Modulation of endogenous cellular defense mechanisms via the vitagene system represents an innovative approach to therapeutic intervention in diseases causing chronic tissue damage, such as in neurodegeneration. The possibility of high-throughoutput screening using proteomic techniques, particularly redox proteomics, provide more comprehensive overview of the interaction of proteins, as well as the interplay among processes involved in neuroprotection. Here by introducing the hormetic dose response concept, the mechanistic foundations and applications to the field of neuroprotection, we discuss the emerging role of heat shock protein as prominent member of vitagene network in neuroprotection and redox proteomics as a tool for investigating redox modulation of stress responsive vitagenes. Hormetic mechanisms are reviewed as possibility of targeted therapeutic manipulation in a cell-, tissue- and/or pathway-specific manner at appropriate points in the neurodegenerative disease process.