Inside human aortic stenosis: a proteomic analysis of plasma

Circulating Plasma Proteins in Aortic Stenosis: Associations With Severity, Myocardial Response, and Clinical Outcomes

BACKGROUND

Echocardiographic indexes of aortic stenosis may not comprehensively reflect disease morbidity. Plasma proteomic profiling may add prognostic value in these patients.

METHODS AND RESULTS

Proximity extension assays (Olink) of 183 circulating cardiovascular and inflammatory proteins were performed in a prospective follow-up study of 122 asymptomatic/minimally symptomatic patients (mean±SD age, 69.1±10.9 years; 61% men) with moderate to severe aortic stenosis and preserved left ventricular ejection fraction. Protein signatures of higher-risk echocardiographic subgroups were determined. Associations of proteins with the primary composite outcome (heart failure hospitalization, progression to New York Heart Association class III-IV, or all-cause mortality) were evaluated using competing risk analyses, with aortic valve replacement being the competing risk. Network analysis unveiled mutually exclusive communities of proteins and echocardiographic parameters, connected only through NT-proBNP (N-terminal pro-B-type natriuretic peptide). Members of the tumor necrosis factor receptor superfamily (TNFRSF1A, TNFRSF1B, and TNFRSF14), and trefoil factor-3 were major hub proteins among the circulating biomarkers. Left ventricular global longitudinal strain >-15% was associated with higher levels of proteins, primarily of inflammation and immune regulation, whereas aortic valve area <1 cm2, E/e' >15, and left atrial reservoir strain <20% were associated with higher levels of NT-proBNP. Of 14 proteins associated with the primary end point, phospholipase-C, C-X-C motif chemokine-9, and interleukin-10 receptor subunit β demonstrated the highest hazard ratios after adjusting for clinical factors (q<0.05).

CONCLUSIONS

Plasma proteins involved in inflammation and immune regulation were differentially expressed in patients with aortic stenosis with reduced left ventricular global longitudinal strain, and associated with adverse clinical outcomes. Their incorporation into aortic stenosis risk stratification warrants further assessment.

Diabetes mellitus and aortic stenosis head to head: toward personalized medicine in patients with both pathologies

Diabetes mellitus (DM) and calcific aortic stenosis (CAS) are common morbidities in the elderly, which are both chronic, progressive and often concomitant diseases. Several studies revealed that DM increases the risk of developing severe CAS, yet clear information about the relationship between both these diseases and the influence of DM on the progression of CAS is currently lacking. To evaluate the effect of DM on aortic valves and on the process of calcification, and to achieve better patient management in daily clinical practice, we analysed calcified and noncalcified valve tissue from patients with severe CAS, with or without DM. A proteomic strategy using isobaric tags was adopted and the plasma concentrations of nine proteins were studied using 3 orthogonal methods and in a separate cell model. The differentially expressed proteins identified are implicated in biological processes like endopeptidase activity, lipid metabolism, coagulation, and fibrinolysis. The results obtained provide evidence that DM provokes changes in the proteome of aortic valves, affecting valve calcification. This finding may help enhance our understanding of the pathogenesis of CAS and how DM affects the evolution of this condition, an important step in identifying targets to personalize the treatment of these patients.

Multi-omics of in vitro aortic valve calcification

Heart valve calcification is an active cellular and molecular process that partly remains unknown. Osteogenic differentiation of valve interstitial cells (VIC) is a central mechanism in calcific aortic valve disease (CAVD). Studying mechanisms in CAVD progression is clearly needed. In this study, we compared molecular mechanisms of osteogenic differentiation of human VIC isolated from healthy donors or patients with CAVD by RNA-seq transcriptomics in early timepoint (48 h) and by shotgun proteomics at later timepoint (10th day). Bioinformatic analysis revealed genes and pathways involved in the regulation of VIC osteogenic differentiation. We found a high amount of stage-specific differentially expressed genes and good accordance between transcriptomic and proteomic data. Functional annotation of differentially expressed proteins revealed that osteogenic differentiation of VIC involved many signaling cascades such as: PI3K-Akt, MAPK, Ras, TNF signaling pathways. Wnt, FoxO, and HIF-1 signaling pathways were modulated only at the early timepoint and thus probably involved in the commitment of VIC to osteogenic differentiation. We also observed a significant shift of some metabolic pathways in the early stage of VIC osteogenic differentiation. Lentiviral overexpression of one of the most upregulated genes (ZBTB16, PLZF) increased calcification of VIC after osteogenic stimulation. Analysis with qPCR and shotgun proteomics suggested a proosteogenic role of ZBTB16 in the early stages of osteogenic differentiation.

Models and Techniques to Study Aortic Valve Calcification in Vitro, ex Vivo and in Vivo. An Overview

Aortic valve stenosis secondary to aortic valve calcification is the most common valve disease in the Western world. Calcification is a result of pathological proliferation and osteogenic differentiation of resident valve interstitial cells. To develop non-surgical treatments, the molecular and cellular mechanisms of pathological calcification must be revealed. In the current overview, we present methods for evaluation of calcification in different ex vivo, in vitro and in vivo situations including imaging in patients. The latter include echocardiography, scanning with computed tomography and magnetic resonance imaging. Particular emphasis is on translational studies of calcific aortic valve stenosis with a special focus on cell culture using human primary cell cultures. Such models are widely used and suitable for screening of drugs against calcification. Animal models are presented, but there is no animal model that faithfully mimics human calcific aortic valve disease. A model of experimentally induced calcification in whole porcine aortic valve leaflets ex vivo is also included. Finally, miscellaneous methods and aspects of aortic valve calcification, such as, for instance, biomarkers are presented.

Prioritization of Candidate Biomarkers for Degenerative Aortic Stenosis through a Systems Biology-Based In-Silico Approach

Degenerative aortic stenosis is the most common valve disease in the elderly and is usually confirmed at an advanced stage when the only treatment is surgery. This work is focused on the study of previously defined biomarkers through systems biology and artificial neuronal networks to understand their potential role within aortic stenosis. The goal was generating a molecular panel of biomarkers to ensure an accurate diagnosis, risk stratification, and follow-up of aortic stenosis patients. We used in silico studies to combine and re-analyze the results of our previous studies and, with information from multiple databases, established a mathematical model. After this, we prioritized two proteins related to endoplasmic reticulum stress, thrombospondin-1 and endoplasmin, which have not been previously validated as markers for aortic stenosis, and analyzed them in a cell model and in plasma from human subjects. Large-scale bioinformatics tools allow us to extract the most significant results after using high throughput analytical techniques. Our results could help to prevent the development of aortic stenosis and open the possibility of a future strategy based on more specific therapies.

Lipoprotein Proteomics and Aortic Valve Transcriptomics Identify Biological Pathways Linking Lipoprotein(a) Levels to Aortic Stenosis

Lipoprotein(a) (Lp(a)) is one of the most important risk factors for the development of calcific aortic valve stenosis (CAVS). However, the mechanisms through which Lp(a) causes CAVS are currently unknown. Our objectives were to characterize the Lp(a) proteome and to identify proteins that may be differentially associated with Lp(a) in patients with versus without CAVS. Our second objective was to identify genes that may be differentially regulated by exposure to high versus low Lp(a) levels in explanted aortic valves from patients with CAVS. We isolated Lp(a) from the blood of 21 patients with CAVS and 22 volunteers and performed untargeted label-free analysis of the Lp(a) proteome. We also investigated the transcriptomic signature of calcified aortic valves from patients who underwent aortic valve replacement with high versus low Lp(a) levels (n = 118). Proteins involved in the protein activation cascade, platelet degranulation, leukocyte migration, and response to wounding may be associated with Lp(a) depending on CAVS status. The transcriptomic analysis identified genes involved in cardiac aging, chondrocyte development, and inflammation as potentially influenced by Lp(a). Our multi-omic analyses identified biological pathways through which Lp(a) may cause CAVS, as well as key molecular events that could be triggered by Lp(a) in CAVS development.

Integrated Strategy for Discovery and Validation of Glycated Candidate Biomarkers for Hemodialysis Patients with Cardiovascular Complications

Glycation plays a pathogenic role in many age-related degenerative pathological conditions, such as diabetes, end-stage renal diseases, and cardiovascular diseases. Mass spectrometry-based qualitative and quantitative analysis methods have been greatly developed and contribute to our understanding of protein glycation. However, it is still challenging to sensitively and accurately quantify endogenous glycated proteome in biological samples. Herein, we proposed an integrated and robust quantitative strategy for comprehensive profiling of early-stage glycated proteome. In this strategy, a filter-assisted sample preparation method was applied to reduce sample loss and improve reproducibility of sample preparation, contributing to high-throughput analysis and accurate quantification of endogenous glycated proteins with low abundance. Standard glycated peptides were spiked and performed the subsequent process together with complex samples both in label-free quantification and multiple reaction monitoring (MRM) analysis, contributing to the improvement of quantitative accuracy. In parallel, a novel approach was developed for the synthesis of heavy isotope-labeled glycated peptides used in MRM analysis. By this way, a total of 1128 endogenous glycated peptides corresponding to 203 serum proteins were identified from 60 runs of 10 pairs of hemodialysis patients with and without cardiovascular complications, and 234 glycated peptides corresponding to 63 proteins existed in >70% runs, among which 17 peptides were discovered to be differentially glycated (P < 0.05, fold-change > 1.5 or <0.67). Furthermore, we validated the glycation difference of four target peptides in 46 serum samples using MRM analysis, which were consistent with our results of label-free quantification.

Integrative Multi-Omics Analysis in Calcific Aortic Valve Disease Reveals a Link to the Formation of Amyloid-Like Deposits

Calcific aortic valve disease (CAVD) is the most prevalent valvular heart disease in the developed world, yet no pharmacological therapy exists. Here, we hypothesize that the integration of multiple omic data represents an approach towards unveiling novel molecular networks in CAVD. Databases were searched for CAVD omic studies. Differentially expressed molecules from calcified and control samples were retrieved, identifying 32 micro RNAs (miRNA), 596 mRNAs and 80 proteins. Over-representation pathway analysis revealed platelet degranulation and complement/coagulation cascade as dysregulated pathways. Multi-omics integration of overlapping proteome/transcriptome molecules, with the miRNAs, identified a CAVD protein–protein interaction network containing seven seed genes (apolipoprotein A1 (APOA1), hemoglobin subunit β (HBB), transferrin (TF), α-2-macroglobulin (A2M), transforming growth factor β-induced protein (TGFBI), serpin family A member 1 (SERPINA1), lipopolysaccharide binding protein (LBP), inter-α-trypsin inhibitor heavy chain 3 (ITIH3) and immunoglobulin κ constant (IGKC)), four input miRNAs (miR-335-5p, miR-3663-3p, miR-21-5p, miR-93-5p) and two connector genes (amyloid beta precursor protein (APP) and transthyretin (TTR)). In a metabolite–gene–disease network, Alzheimer’s disease exhibited the highest degree of betweenness. To further strengthen the associations based on the multi-omics approach, we validated the presence of APP and TTR in calcified valves from CAVD patients by immunohistochemistry. Our study suggests a novel molecular CAVD network potentially linked to the formation of amyloid-like structures. Further investigations on the associated mechanisms and therapeutic potential of targeting amyloid-like deposits in CAVD may offer significant health benefits.

Patient Management in Aortic Stenosis: Towards Precision Medicine Through Protein Analysis, Imaging and Diagnostic Tests

Aortic stenosis is the most frequent valvular disease in developed countries. It progresses from mild fibrocalcific leaflet changes to a more severe leaflet calcification at the end stages of the disease. Unfortunately, symptoms of aortic stenosis are unspecific and only appear when it is too late, complicating patients' management. The global impact of aortic stenosis is increasing due to the growing elderly population. The disease supposes a great challenge because of the multiple comorbidities of these patients. Nowadays, the only effective treatment is valve replacement, which has a high cost in both social and economic terms. For that reason, it is crucial to find potential diagnostic, prognostic and therapeutic indicators that could help us to detect this disease in its earliest stages. In this article, we comprehensively review several key observations and translational studies related to protein markers that are promising for being implemented in the clinical field as well as a discussion about the role of precision medicine in aortic stenosis.

CD34+ circulating cells display signs of immune activation in patients with acute coronary syndrome

Bone marrow-derived endothelial progenitor cells (EPC) are released into the peripheral blood in situations of vascular repair/angiogenesis. Regulation of vascular repair and angiogenesis by EPC depends not only on the number of circulating EPC but also on their functionality. As endothelial cells can act as antigen-presenting cells in coronary artery disease (CAD), we postulated that EPC can be immune activated here as well. CD34⁺-EPC were isolated from peripheral blood of patients with ST-elevation myocardial infarction (STEMI, n = 12), non-STEMI/unstable angina (UA, n = 15), and stable CAD (SA, n = 18). Expression of HLA-DR, adhesion and costimulatory molecules by isolated CD34⁺-EPC were compared with levels in healthy controls (n = 18). There were no significant differences in VCAM-1 and CD80 expression by peripheral circulating CD34⁺-EPC between the four groups, yet expression of CD86 was highest in UA (p < 0.05). ICAM-1 expression was lowest in SA (p < 0.01). CD34⁺-EPC constitutively expressed HLA-DR across all groups. Of note, patients pretreated with HMG-CoA reductase inhibitors exhibited lower expression of VCAM-1 by CD34⁺-EPC throughout all patient groups; furthermore, statins significantly limited ex vivo-induced upregulation of ICAM-1 by TNF-alpha. To the best of our knowledge, this is the first study to examine the expression of immune markers in peripheral circulating CD34⁺-EPC ex vivo. We demonstrate that CD34⁺-EPC display different patterns of adhesion and costimulatory molecules in various states of CAD. Expression levels were affected by pretreatment with statins. Hence, immune activity of peripheral circulating CD34⁺ cells might play a pathophysiologic role in evolution of CAD.

A comprehensive study of calcific aortic stenosis: from rabbit to human samples

The global incidence of calcific aortic stenosis (CAS) is increasing owing, in part, to a growing elderly population. The condition poses a great challenge to public health, because of the multiple comorbidities of these older patients. Using a rabbit model of CAS, we sought to characterize protein alterations associated with calcified valve tissue that can be ultimately measured in plasma as non-invasive biomarkers of CAS. Aortic valves from healthy and mild stenotic rabbits were analyzed by two-dimensional difference gel electrophoresis, and selected reaction monitoring was used to directly measure the differentially expressed proteins in plasma from the same rabbits to corroborate their potential as diagnostic indicators. Similar analyses were performed in plasma from human subjects, to examine the suitability of these diagnostic indicators for transfer to the clinical setting. Eight proteins were found to be differentially expressed in CAS tissue, but only three were also altered in plasma samples from rabbits and humans: transitional endoplasmic reticulum ATPase, tropomyosin α-1 chain and L-lactate dehydrogenase B chain. Results of receiver operating characteristic curves showed the discriminative power of the scores, which increased when the three proteins were analyzed as a panel. Our study shows that a molecular panel comprising three proteins related to osteoblastic differentiation could have utility as a serum CAS indicator and/or therapeutic target.

Summary: Using a rabbit model of calcific aortic stenosis, we have defined a molecular panel of three proteins related to osteoblastic differentiation. Additionally, this panel has been confirmed in human samples.

How to use and integrate bioinformatics tools to compare proteomic data from distinct conditions? A tutorial using the pathological similarities between Aortic Valve Stenosis and Coronary Artery Disease as a case-study

Nowadays we are surrounded by a plethora of bioinformatics tools, powerful enough to deal with the large amounts of data arising from proteomic studies, but whose application is sometimes hard to find. Therefore, we used a specific clinical problem - to discriminate pathophysiology and potential biomarkers between two similar cardiovascular diseases, aortic valve stenosis (AVS) and coronary artery disease (CAD) - to make a step-by-step guide through four bioinformatics tools: STRING, DisGeNET, Cytoscape and ClueGO. Proteome data was collected from articles available on PubMed centered on proteomic studies enrolling subjects with AVS or CAD. Through the analysis of gene ontology provided by STRING and ClueGO we could find specific biological phenomena associated with AVS, such as down-regulation of elastic fiber assembly, and with CAD, such as up-regulation of plasminogen activation. Moreover, through Cytoscape and DisGeNET we could pinpoint surrogate markers either for AVS (e.g. popeye domain containing protein 2 and 28S ribosomal protein S36, mitochondrial) or for CAD (e.g. ankyrin repeat and SOCS box protein 7) which deserve future validation. Data recycling and integration as well as research orientation are among the main advantages of resorting to bioinformatics analysis, hence these tutorials can be of great convenience for proteomics investigators.

BIOLOGICAL SIGNIFICANCE

As we saw for aortic valve stenosis and coronary artery disease, it can be of great relevance to perform preliminary bioinformatics analysis with already published proteomics data. It not only saves us time in the lab (avoiding work duplication) as it points out new hypothesis to explain the phenotypical presentation of the diseases as well as new surrogate markers with clinical relevance, deserving future scrutiny. These essential steps can be easily overcome if one follows the steps proposed in our tutorial for STRING, DisGeNET, Cytoscape and ClueGO utilization.

Patients with calcific aortic stenosis exhibit systemic molecular evidence of ischemia, enhanced coagulation, oxidative stress and impaired cholesterol transport

BACKGROUND

The most common valve diseases are calcific aortic stenosis (AS) and aortic regurgitation (AR). The former is characterized by thickening of valve leaflets followed by progressive calcification, which produces progressive aortic valve (AV) narrowing, increased pressure afterload on the left ventricle (LV) and subsequent LV hypertrophy. On the other hand, AR is due to malcoaptation of the valve leaflets with resultant diastolic reflux of blood from aorta back to the LV producing volume and pressure overload and progressive LV dilatation. In order to isolate the molecular mechanisms taking place during AS, we have used an integrated "-omic" approach to compare plasma samples from AS and from AR patients used as controls. The final purpose of this work is to find molecular changes in response to the calcification of the AV, diminishing the effects of the AV dysfunction.

METHODS AND RESULTS

Using two-dimensional difference gel electrophoresis (2D-DIGE) and gas chromatography coupled to mass spectrometry (GC-MS) in a cohort of 6 subjects, we have found differences in 24 protein spots and 19 metabolites, respectively. Among them, 7 proteins and 3 metabolites have been verificated by orthogonal techniques (SRM or turbidimetry): fibrinogen beta and gamma chain, vitronectin, apolipoprotein C-II, antithrombin III, haptoglobin, succinic acid, pyroglutamic acid and alanine. Classification according to their main function showed alterations related to coagulation, inflammation, oxidative stress, response to ischemia and lipid metabolism, defining 4 different molecular panels that characterize AS with high specificity and sensitivity.

CONCLUSION

These results may facilitate management of these patients by making faster diagnostics of the disease and better understand these pathways for regulating its progression.

Proteomic identification of putative biomarkers for early detection of sudden cardiac death in a family with a LMNA gene mutation causing dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a severe heart disease characterized by progressive ventricular dilation and impaired systolic function of the left ventricle. We recently identified a novel pathogenic mutation in the LMNA gene in a family affected by DCM showing sudden death background. We now aimed to identify potential biomarkers of disease status, as well as sudden death predictors, in members of this family. We analysed plasma samples from 14 family members carrying the mutation, four of which (with relevant clinical symptoms) were chosen for the proteomic analysis. Plasma samples from these four patients and from four sex- and age-matched healthy controls were processed for their enrichment in low- and medium-abundance proteins (ProteoMiner™) prior to proteomic analysis by 2D-DIGE and MS. 111 spots were found to be differentially regulated between mutation carriers and control groups, 83 of which were successfully identified by MS, corresponding to 41 different ORFs. Some proteins of interest were validated either by turbidimetry or western blot in family members and healthy controls. Actin, alpha-1-antytripsin, clusterin, vitamin-D binding protein and antithrombin-III showed increased levels in plasma from the diseased group. We suggest following these proteins as putative biomarkers for the evaluation of DCM status in LMNA mutation carriers.

BIOLOGICAL SIGNIFICANCE

We developed a proteomic analysis of plasma samples from a family showing history of dilated cardiomyopathy caused by a LMNA mutation, which may lead to premature death or cardiac transplant. We identified a number of proteins augmented in mutation carriers that could be followed as potential biomarkers for dilated cardiomyopathy on these patients.

Contributions of immunoaffinity chromatography to deep proteome profiling of human biofluids

Human biofluids, especially blood plasma or serum, hold great potential as the sources of candidate biomarkers for various diseases; however, the enormous dynamic range of protein concentrations in biofluids represents a significant analytical challenge for detecting promising low-abundance proteins. Over the last decade, various immunoaffinity chromatographic methods have been developed and routinely applied for separating low-abundance proteins from the high- and moderate-abundance proteins, thus enabling much more effective detection of low-abundance proteins. Herein, we review the advances of immunoaffinity separation methods and their contributions to the proteomic applications in human biofluids. The limitations and future perspectives of immunoaffinity separation methods are also discussed.

Implementation strategies of Systems Medicine in clinical research and home care for cardiovascular disease patients

Insights from the "-omics" science have recently emphasized the need to implement an overall strategy in medical research. Here, the development of Systems Medicine has been indicated as a potential tool for clinical translation of basic research discoveries. Systems Medicine also gives the opportunity of improving different steps in medical practice, from diagnosis to healthcare management, including clinical research. The development of Systems Medicine is still hampered however by several challenges, the main one being the development of computational tools adequate to record, analyze and share a large amount of disparate data. In addition, available informatics tools appear not yet fully suitable for the challenge because they are not standardized, not universally available, or with ethical/legal concerns. Cardiovascular diseases (CVD) are a very promising area for translating Systems Medicine into clinical practice. By developing clinically applied technologies, the collection and analysis of data may improve CV risk stratification and prediction. Standardized models for data recording and analysis can also greatly broaden data exchange, thus promoting a uniform management of CVD patients also useful for clinical research. This advance however requires a great organizational effort by both physicians and health institutions, as well as the overcoming of ethical problems. This narrative review aims at providing an update on the state-of-art knowledge in the area of Systems Medicine as applied to CVD, focusing on current critical issues, providing a road map for its practical implementation.

The plasma proteomic signature as a strategic tool for early diagnosis of acute coronary syndrome

BACKGROUND

Acute coronary syndrome is the major cause of death in developed countries. Despite its high prevalence, there is still a strong need for new biomarkers which permit faster and more accurate diagnostics and new therapeutic drugs. The basis for this challenge lay in improving our understanding of the whole atherosclerotic process from atherogenesis to atherothrombosis. In this study, we conducted two different proteomic analyses of peripheral blood plasma from non-ST elevation acute coronary syndrome and ST elevation acute coronary syndrome patients vs healthy controls.

RESULTS

Two-dimensional Fluorescence Difference in Gel Electrophoresis and mass spectrometry permitted the identification of 31 proteins with statistical differences (p < 0.05) between experimental groups. Additionally, validation by Western blot and Selected Reaction Monitoring permitted us to confirm the identification of a different and characteristic plasma proteomic signature for NSTEACS and STEACS patients.

CONCLUSIONS

We purpose the severity of hypoxia as the cornerstone for explaining the differences observed between both groups.

Proteomic analysis of human plasma in chronic rheumatic mitral stenosis reveals proteins involved in the complement and coagulation cascade

BACKGROUND

Rheumatic fever in childhood is the most common cause of Mitral Stenosis in developing countries. The disease is characterized by damaged and deformed mitral valves predisposing them to scarring and narrowing (stenosis) that results in left atrial hypertrophy followed by heart failure. Presently, echocardiography is the main imaging technique used to diagnose Mitral Stenosis. Despite the high prevalence and increased morbidity, no biochemical indicators are available for prediction, diagnosis and management of the disease. Adopting a proteomic approach to study Rheumatic Mitral Stenosis may therefore throw some light in this direction. In our study, we undertook plasma proteomics of human subjects suffering from Rheumatic Mitral Stenosis (n = 6) and Control subjects (n = 6). Six plasma samples, three each from the control and patient groups were pooled and subjected to low abundance protein enrichment. Pooled plasma samples (crude and equalized) were then subjected to in-solution trypsin digestion separately. Digests were analyzed using nano LC-MS(E). Data was acquired with the Protein Lynx Global Server v2.5.2 software and searches made against reviewed Homo sapiens database (UniProtKB) for protein identification. Label-free protein quantification was performed in crude plasma only.

RESULTS

A total of 130 proteins spanning 9-192 kDa were identified. Of these 83 proteins were common to both groups and 34 were differentially regulated. Functional annotation of overlapping and differential proteins revealed that more than 50% proteins are involved in inflammation and immune response. This was corroborated by findings from pathway analysis and histopathological studies on excised tissue sections of stenotic mitral valves. Verification of selected protein candidates by immunotechniques in crude plasma corroborated our findings from label-free protein quantification.

CONCLUSIONS

We propose that this protein profile of blood plasma, or any of the individual proteins, could serve as a focal point for future mechanistic studies on Mitral Stenosis. In addition, some of the proteins associated with this disorder may be candidate biomarkers for disease diagnosis and prognosis. Our findings might help to enrich existing knowledge on the molecular mechanisms involved in Mitral Stenosis and improve the current diagnostic tools in the long run.

Identification of altered plasma proteins by proteomic study in valvular heart diseases and the potential clinical significance

BACKGROUND

Little is known about genetic basis and proteomics in valvular heart disease (VHD) including rheumatic (RVD) and degenerative (DVD) valvular disease. The present proteomic study examined the hypothesis that certain proteins may be associated with the pathological changes in the plasma of VHD patients.

METHODS AND RESULTS

Differential protein analysis in the plasma identified 18 differentially expressed protein spots and 14 corresponding proteins or polypeptides by two-dimensional electrophoresis and mass spectrometry in 120 subjects. Two up-regulated (complement C4A and carbonic anhydrase 1) and three down-regulated proteins (serotransferrin, alpha-1-antichymotrypsin, and vitronectin) were validated by ELISA in enlarging samples. The plasma levels (n = 40 for each) of complement C4A in RVD (715.8±35.6 vs. 594.7±28.2 ng/ml, P = 0.009) and carbonic anhydrase 1 (237.70±15.7 vs. 184.7±10.8 U/L, P = 0.007) in DVD patients were significantly higher and that of serotransferrin (2.36±0.20 vs. 2.93±0.16 mg/ml, P = 0.025) and alpha-1-antichymotrypsin (370.0±13.7 vs. 413.0±11.6 µg/ml, P = 0.019) in RVD patients were significantly lower than those in controls. The plasma vitronectin level in both RVD (281.3±11.0 vs. 323.2±10.0 µg/ml, P = 0.006) and DVD (283.6±11.4 vs. 323.2±10.0 µg/ml, P = 0.011) was significantly lower than those in normal controls.

CONCLUSIONS

We have for the first time identified alterations of 14 differential proteins or polypeptides in the plasma of patients with various VHD. The elevation of plasma complement C4A in RVD and carbonic anhydrase 1 in DVD and the decrease of serotransferrin and alpha-1-antichymotrypsin in RVD patients may be useful biomarkers for these valvular diseases. The decreased plasma level of vitronectin - a protein related to the formation of valvular structure - in both RVD and DVD patients might indicate the possible genetic deficiency in these patients.

Aortic stenosis: a general overview of clinical, pathophysiological and therapeutic aspects

Aortic stenosis is the most prevalent valve pathology and calcific aortic valve disease (CAVD) is its most frequent etiology in developed countries. There is extensive evidence that CAVD represents an active disease process similar to that of atherosclerosis with similar classical cardiovascular risk factors and pathological mechanisms. Given that in the vast majority of situations the only treatment available is valve replacement there is a need to develop pharmacological therapies that retard the disease progression. Lipid-lowering therapies have been the focus of research, however, so far with negative results. Future studies, including animal models, shall provide an opportunity to further evaluate the disease mechanisms of CAVD and to discover potential disease biomarkers and pharmacological interventions that can reduce the need for valve replacement.

Can proteomics yield insight into aging aorta?

The aging aorta exhibits structural and physiological changes that are reflected in the proteome of its component cells types. The advance in proteomic technologies has made it possible to analyze the quantity of proteins associated with the natural history of aortic aging. These alterations reflect the molecular and cellular mechanisms of aging and could provide an opportunity to predict vascular health. This paper focuses on whether discoveries stemming from the application of proteomic approaches of the intact aging aorta or vascular smooth muscle cells can provide useful insights. Although there have been limited studies to date, a number of interesting proteins have been identified that are closely associated with aging in the rat aorta. Such proteins, including milk fat globule-EGF factor 8, matrix metalloproteinase type-2, and vitronectin, could be used as indicators of vascular health, or even explored as therapeutic targets for aging-related vascular diseases.

Modification of the secretion pattern of proteases, inflammatory mediators, and extracellular matrix proteins by human aortic valve is key in severe aortic stenosis

One of the major challenges in cardiovascular medicine is to identify candidate biomarker proteins. Secretome analysis is particularly relevant in this search as it focuses on a subset of proteins released by a cell or tissue under certain conditions. The sample can be considered as a plasma subproteome and it provides a more direct approximation to the in vivo situation. Degenerative aortic stenosis is the most common worldwide cause of valve replacement. Using a proteomic analysis of the secretome from aortic stenosis valves we could identify candidate markers related to this pathology, which may facilitate early diagnosis and treatment. For this purpose, we have designed a method to validate the origin of secreted proteins, demonstrating their synthesis and release by the tissue and ruling out blood origin. The nLC-MS/MS analysis showed the labeling of 61 proteins, 82% of which incorporated the label in only one group. Western blot and selective reaction monitoring differential analysis, revealed a notable role of the extracellular matrix. Variation in particular proteins such as PEDF, cystatin and clusterin emphasizes the link between aortic stenosis and atherosclerosis. In particular, certain proteins variation in secretome levels correlates well, not only with label incorporation trend (only labeled in aortic stenosis group) but, more importantly, with alterations found in plasma from an independent cohort of samples, pointing to specific candidate markers to follow up in diagnosis, prognosis, and therapeutic intervention.

Secretome of human aortic valves

One of the major challenges in cardiovascular medicine is to identify candidate biomarker proteins. Between different proteomics studies, the secretome is a valuable tool in the search for biomarkers locally released by a studied tissue and remains particularly important while working with vascular tissues, since the secreted proteins would be probably shed to the blood. In this chapter, we described a method to validate the origin of secreted proteins in human aortic valves, demonstrating their synthesis and release by the tissue and ruling out blood origin.

Multiple reaction monitoring (MRM) of plasma proteins in cardiovascular proteomics

Different methodologies have been used through years to discover new potential biomarkers related with cardiovascular risk. The conventional proteomic strategy involves a discovery phase that requires the use of mass spectrometry (MS) and a validation phase, usually on an alternative platform such as immunoassays that can be further implemented in clinical practice. This approach is suitable for a single biomarker, but when large panels of biomarkers must be validated, the process becomes inefficient and costly. Therefore, it is essential to find an alternative methodology to perform the biomarker discovery, validation, and -quantification. The skills provided by quantitative MS turn it into an extremely attractive alternative to antibody-based technologies. Although it has been traditionally used for quantification of small molecules in clinical chemistry, MRM is now emerging as an alternative to traditional immunoassays for candidate protein biomarker validation.

A comparative study of immunodepletion and equalization methods for aortic stenosis human plasma

Calcified aortic valve disease is a slowly progressive disorder that ranges from mild valve thickening with no obstruction of blood flow, known as aortic sclerosis, to severe calcification with impaired leaflet motion or aortic stenosis. Until now, aortic stenosis (AS) was thought to result from aging and "wear and tear" of the aortic valve, but nowadays, it is known that it presents the same risk factors as atherosclerosis and cardiovascular diseases.A proteomic analysis of plasma could permit to identify the changes in protein expression induced by AS in this biological sample. However, the characterization of human plasma proteome is a very complicated task, due to the wide dynamic range of concentration that separates the most abundant proteins and the less common ones (10-12 orders of magnitude). For this reason, plasma analysis requires pre-fractionation methods, and several such techniques are currently used to deplete albumin and other abundant plasma proteins.In this work we describe two different and optimized protocols to decrease the plasma proteome complexity for proteomic analysis. With this, comprehensive and systematic characterization of the plasma proteome in the healthy and diseased aortic stenosis (AS) state will greatly facilitate the development of "useful" biomarkers for early disease detection, clinical diagnosis, and therapy.