Recent advances in proteomic technologies applied to cardiovascular disease

Searching for Atherosclerosis Biomarkers by Proteomics: A Focus on Lesion Pathogenesis and Vulnerability

Plaque rupture and thrombosis are the most important clinical complications in the pathogenesis of stroke, coronary arteries, and peripheral vascular diseases. The identification of early biomarkers of plaque presence and susceptibility to ulceration could be of primary importance in preventing such life-threatening events. With the improvement of proteomic tools, large-scale technologies have been proven valuable in attempting to unravel pathways of atherosclerotic degeneration and identifying new circulating markers to be utilized either as early diagnostic traits or as targets for new drug therapies. To address these issues, different matrices of human origin, such as vascular cells, arterial tissues, plasma, and urine, have been investigated. Besides, proteomics was also applied to experimental atherosclerosis in order to unveil significant insights into the mechanisms influencing atherogenesis. This narrative review provides an overview of the last twenty years of omics applications to the study of atherogenesis and lesion vulnerability, with particular emphasis on lipoproteomics and vascular tissue proteomics. Major issues of tissue analyses, such as plaque complexity, sampling, availability, choice of proper controls, and lipoproteins purification, will be raised, and future directions will be addressed.

Clinical Phenotypes of Cardiovascular and Heart Failure Diseases Can Be Reversed? The Holistic Principle of Systems Biology in Multifaceted Heart Diseases

Recent advances in cardiology and biological sciences have improved quality of life in patients with complex cardiovascular diseases (CVDs) or heart failure (HF). Regardless of medical progress, complex cardiac diseases continue to have a prolonged clinical course with high morbidity and mortality. Interventional coronary techniques together with drug therapy improve quality and future prospects of life, but do not reverse the course of the atherosclerotic process that remains relentlessly progressive. The probability of CVDs and HF phenotypes to reverse can be supported by the advances made on the medical holistic principle of systems biology (SB) and on artificial intelligence (AI). Studies on clinical phenotypes reversal should be based on the research performed in large populations of patients following gathering and analyzing large amounts of relative data that embrace the concept of complexity. To decipher the complexity conundrum, a multiomics approach is needed with network analysis of the biological data. Only by understanding the complexity of chronic heart diseases and explaining the interrelationship between different interconnected biological networks can the probability for clinical phenotypes reversal be increased.

Fluid-based assays and precision medicine of cardiovascular diseases: the ‘hope’ for Pandora’s box?

Progresses in liquid-based assays may provide novel useful non-invasive indicators of cardiovascular (CV) diseases. By analysing circulating cells or their products in blood, saliva and urine samples, we can investigate molecular changes present at specific time points in each patient allowing sequential monitoring of disease evolution. For example, an increased number of circulating endothelial cells may be a diagnostic biomarker for diabetic nephropathy and heart failure with preserved ejection fraction. The assessment of circulating cell-free DNA (cfDNA) levels may be useful to predict severity of acute myocardial infarction, as well as diagnose heart graft rejection. Remarkably, circulating epigenetic biomarkers, including DNA methylation, histone modifications and non-coding RNAs are key pathogenic determinants of CV diseases representing putative useful biomarkers and drug targets. For example, the unmethylated FAM101A gene may specifically trace cfDNA derived from cardiomyocyte death providing a powerful diagnostic biomarker of apoptosis during ischaemia. Moreover, changes in plasma levels of circulating miR-92 may predict acute coronary syndrome onset in patients with diabetes. Now, network medicine provides a framework to analyse a huge amount of big data by describing a CV disease as a result of a chain of molecular perturbations rather than a single defect (reductionism). We outline advantages and challenges of liquid biopsy with respect to traditional tissue biopsy and summarise the main completed and ongoing clinical trials in CV diseases. Furthermore, we discuss the importance of combining fluid-based assays, big data and network medicine to improve precision medicine and personalised therapy in this field.

Differential expression of NPM, GSTA3, and GNMT in mouse liver following long-term in vivo irradiation by means of uranium tailings

Uranium tailings (UT) are formed as a byproduct of uranium mining and are of potential risk to living organisms. In the present study, we sought to identify potential biomarkers associated with chronic exposure to low dose rate γ radiation originating from UT. We exposed C57BL/6J mice to 30, 100, or 250 μGy/h of gamma radiation originating from UT samples. Nine animals were included in each treatment group. We observed that the liver central vein was significantly enlarged in mice exposed to dose rates of 100 and 250 μGy/h, when compared with nonirradiated controls. Using proteomic techniques, we identified 18 proteins that were differentially expressed (by a factor of at least 2.5-fold) in exposed animals, when compared with controls. We chose glycine N-methyltransferase (GNMT), glutathione S-transferase A3 (GSTA3), and nucleophosmin (NPM) for further investigations. Our data showed that GNMT (at 100 and 250 μGy/h) and NPM (at 250 μGy/h) were up-regulated, and GSTA3 was down-regulated in all of the irradiated groups, indicating that their expression is modulated by chronic gamma radiation exposure. GNMT, GSTA3, and NPM may therefore prove useful as biomarkers of gamma radiation exposure associated with UT. The mechanisms underlying those changes need to be further studied.

Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins

Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule.

Biomarkers in cardiovascular disease: Statistical assessment and section on key novel heart failure biomarkers

Cardiovascular disease (CVD) is a leading cause of death worldwide and continues to increase in prevalence compared to previous decades, in part because of the aging of the world population. Atherosclerotic CVD starts at a very young age and progresses over time allowing sufficient time for screening and early detection of the condition. Advances in biomarker research and developments related to CVD over the past 30 years have led to more sensitive screening methods, a greater emphasis on its early detection and diagnosis, and improved treatments resulting in more favorable clinical outcomes in the community. However, the use of biomarkers for different purposes in CVD remains an important area of research that has been explored by scientists over the years and many new developments are still underway. Therefore, a detailed description of all CVD biomarkers that are currently been used or investigated for future use in the field of cardiovascular medicine is out of scope for any review article. In the present review, we do not intend to replicate the information from previous exhaustive review on biomarkers, but highlight key statistical and clinical issues with an emphasis on methods to evaluate the incremental yield of biomarkers, including their clinical utility, a prerequisite before any putative novel biomarker is utilized in clinical practice. In addition, we will summarize information regarding recent novel heart failure biomarkers in current practice, which are undergoing scrutiny before they can be available for clinical use, and their impact on clinical outcomes.

Identifying new Risk Markers and Potential Targets: The Value of the Proteome

Several protein biomarkers, including cardiac troponin T, cardiac troponin I, B-type natriuretic peptide, C-reactive protein and apolipoprotein A-I, are widely employed in the evaluation of cardiovascular disease. Several of such potential biomarkers, or their multiscores, have been assessed over the last years for the prediction of cardiovascular risk but only a few of them have been validated for clinical use. Substantial improvement in the cardiovascular risk prediction and reclassification relative to traditional models therefore remains a difficult task presently unresolved. Hence, a potential importance of alternative approaches which may rely on novel proteomic biomarkers among others. Plasma or serum concentrations of numerous proteins were measured using proteomic approaches to establish their relationships with cardiovascular disease; none of them was however evaluated for cardiovascular risk prediction and subject stratification in rigorous large-scale studies. Thus, further research is needed to identify novel candidates that can improve cardiovascular risk prediction, subject stratification and standard care. Proteomics will undoubtedly remain a key approach to address this major clinical and scientific challenge.

Nutrigenomics, the Microbiome, and Gene-Environment Interactions: New Directions in Cardiovascular Disease Research, Prevention, and Treatment: A Scientific Statement From the American Heart Association

Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention.

Transition from identity to bioactivity-guided proteomics for biomarker discovery with focus on the PF2D platform

Proteomic strategies provide a valuable tool kit to identify proteins involved in diseases. With recent progress in MS technology, high throughput proteomics has accelerated protein identification for potential biomarkers. Numerous biomarker candidates have been identified in several diseases, and many are common among pathologies. An overall strategy that could complement and strengthen the search for biomarkers is combining protein identity with biological outcomes. This review describes an emerging framework of bridging bioactivity to protein identity, exploring the possibility that some biomarkers will have a mechanistic role in the disease process. A review of pulmonary, cardiovascular, and CNS biomarkers will be discussed to demonstrate the utility of combining bioactivity with identification as a means to not only find meaningful biomarkers, but also to uncover functional mediators of disease.

Recent developments in proteomic methods and disease biomarkers

Proteomic methodologies for identification and analysis of biomarkers have gained more attention during recent years and have evolved rapidly. Identification and detection of disease biomarkers are important to foresee outbreaks of certain diseases thereby avoiding surgery and other invasive and expensive medical treatments for patients. Thus, more research into discovering new biomarkers and new methods for faster and more accurate detection is needed. It is often difficult to detect and measure biomarkers because of their low concentrations and the complexity of their respective matrices. Therefore it is hard to find and validate methods for accurate screening methods suitable for clinical use. The most recent developments during the last three years and also some historical considerations of proteomic methodologies for identification and validation of disease biomarkers are presented in this review.

Urinary protein biomarker database: a useful tool for biomarker discovery

An open-access biomarker database offers a convenient tool for researchers to acquire existing knowledge about proteins and diseases by simply querying its Web site. Biologists can use the biomarker database to assess the confidence and disease specificity of their own research results by cross-study comparison, and bioinformaticians can use it to discover new relationships between diseases and proteins by reanalyzing data via new strategies. This chapter introduces the urinary protein biomarker database, a manually curated database that aim to collect all studies of urinary protein biomarkers from published literature. In the current stage, this database includes very few disease-specific biomarker candidates that have been reported by multiple studies, reflecting current status in the field of urinary biomarker discovery. We believe that this situation will be improved with the development of technologies and accumulation of data, and a more complete and precise biomarker database will play more important role in future studies.

The selected reaction monitoring/multiple reaction monitoring-based mass spectrometry approach for the accurate quantitation of proteins: clinical applications in the cardiovascular diseases

Selected reaction monitoring, also known as multiple reaction monitoring, is a powerful targeted mass spectrometry approach for a confident quantitation of proteins/peptides in complex biological samples. In recent years, its optimization and application have become pivotal and of great interest in clinical research to derive useful outcomes for patient care. Thus, selected reaction monitoring/multiple reaction monitoring is now used as a highly sensitive and selective method for the evaluation of protein abundances and biomarker verification with potential applications in medical screening. This review describes technical aspects for the development of a robust multiplex assay and discussing its recent applications in cardiovascular proteomics: verification of promising disease candidates to select only the highest quality peptides/proteins for a preclinical validation, as well as quantitation of protein isoforms and post-translational modifications.

Development and analytical comparison of microflow and nanoflow liquid chromatography/mass spectrometry procedures for quantification of cardiac troponin T in mouse hearts

Three procedures for the quantification of cardiac troponin T (cTnT) based on liquid chromatography/mass spectrometry (LC/MS) were developed, validated and compared. The procedures were applied to estimate the cTnT content in the hearts of wild type mice C57BL/6J (WT) and double knock-outs for apolipoprotein E and receptor for LDL (AL KO). Three variants of the procedure proposed include microflow, direct injection nanoflow and preconcentration nanoflow LC/MS. Troponin T tryptic peptide YEINVLR and its analog (internal standard) were monitored in a multiple reaction monitoring mode using triple quadrupole mass detector with electrospray (ESI) ion sources. The preconcentration nanoflow LC/MS method offered the best sensitivity with a lower limit of quantification (LLOQ) of 0.25 fg µL(-1) and a minimal matrix effect. The LLOQ value was 8 times better, compared with that in direct injection nanoflow LC/MS and 200 times better than in microflow LC/MS. The accuracy or precision for all three methods were not different. Separation time in the direct injection nanoflow (8 min) was equivalent to the microflow method (6 min). The cTnT contents in the mice hearts measured by the methods developed by the present authors were not different between the WT and AL KO. We conclude that nanoflow LC/MS based quantitative proteomics offers fundamentally better sensitivities while maintaining analytical quality and separation times equivalent to microflow procedures.

Cardiac biomarkers for infarct diagnosis and early exclusion of acute coronary syndrome

The acute coronary syndrome (ACS) represents a diagnostic challenge: on the one hand patients need to be quickly identified to initiate treatment and on the other hand early exclusion of patients without ACS is important to relieve patient stress as well as overcrowded emergency departments. A growing number of biomarkers are becoming available to aid physicians with this task. This review gives an overview of the current research concerning early exclusion with an emphasis on the clinically most important biomarker: cardiac troponin.