Urine protein biomarkers for detection of cardiovascular disease and their use for the clinic

Systematic scoping review evaluating the potential of wastewater-based epidemiology for monitoring cardiovascular disease and cancer

Cardiovascular disease (CVD) and cancer are collectively responsible for tens of millions of global deaths each year. These rates are projected to intensify as the COVID-19 pandemic has caused delays in individualized diagnostics, or exacerbated prevalence due to Post Acute Coronavirus (COVID-19) Syndrome. Wastewater-based epidemiology (WBE) has successfully been employed as a useful tool for generating population-level health assessments, and was examined here in this systematic scoping literature review to (i) identify endogenous human biomarkers reported to indicate CVD or cancer in clinical practice, (ii) assess specificity to the indicated diseases, (iii) evaluate the utility for estimating population-level disease prevalence in community wastewater, and (iv) contextualize the obtained information for monitoring CVD and cancer presence via WBE. A total of 48 peer-reviewed papers were critically examined identifying five urinary protein biomarkers: cardiac troponin I (cTnI) (heart attack/heart failure), cystatin C (atherosclerosis), normetanephrine (tumor presence), α-fetoprotein (prostate and liver cancer), and microtubule assisted serine/threonine kinase 4 (MAST4) (breast cancer). Next, urinary excretion information was utilized to predict biomarker concentrations extant in community wastewater, resulting in average healthy concentrations ranging from 0.02 to 1159 ng/L, and disease-indicating thresholds from 0.16 to 3041 ng/L. Finally, estimating prevalence-adjusted wastewater measurements was explored in order to assess community-level CVD and cancer presence utilizing U.S. reported prevalence rates. Results obtained suggest that WBE can serve as a viable tool in support of current methods for CVD and cancer assessment to reduce morbidities and mortalities worldwide.

Urinary Proteomics Identifying Novel Biomarkers for the Diagnosis and Phenotyping of Carotid Artery Stenosis

Background: Carotid artery stenosis (CAS) is caused by the formation of atherosclerotic plaques inside the arterial wall and accounts for 20–30% of all strokes. The development of an early, noninvasive diagnostic method and the identification of high-risk patients for ischemic stroke is essential to the management of CAS in clinical practice.

Methods: We used the data-independent acquisition (DIA) technique to conduct a urinary proteomic study in patients with CAS and healthy controls. We identified the potential diagnosis and risk stratification biomarkers of CAS. And Ingenuity pathway analysis was used for functional annotation of differentially expressed proteins (DEPs). Furthermore, receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic values of DEPs.

Results: A total of 194 DEPs were identified between CAS patients and healthy controls by DIA quantification. The bioinformatics analysis showed that these DEPs were correlated with the pathogenesis of CAS. We further identified 32 DEPs in symptomatic CAS compared to asymptomatic CAS, and biological function analysis revealed that these proteins are mainly related to immune/inflammatory pathways. Finally, a biomarker panel of six proteins (ACP2, PLD3, HLA-C, GGH, CALML3, and IL2RB) exhibited potential diagnostic value in CAS and good discriminative power for differentiating symptomatic and asymptomatic CAS with high sensitivity and specificity.

Conclusions: Our study identified novel potential urinary biomarkers for noninvasive early screening and risk stratification of CAS.

Review: Detection and quantification of proteins in human urine

Extensive medical research showed that patients, with high protein concentration in urine, have various kinds of kidney diseases, referred to as proteinuria. Urinary protein biomarkers are useful for diagnosis of many health conditions - kidney and cardio vascular diseases, cancers, diabetes, infections. This review focuses on the instrumental quantification (electrophoresis, chromatography, immunoassays, mass spectrometry, fluorescence spectroscopy, the infrared spectroscopy, and Raman spectroscopy) of proteins (the most of all albumin) in human urine matrix. Different techniques provide unique information on what constituents of the urine are. Due to complex nature of urine, a separation step by electrophoresis or chromatography are often used for proteomics study of urine. Mass spectrometry is a powerful tool for the discovery and the analysis of biomarkers in urine, however, costs of the analysis are high, especially for quantitative analysis. Immunoassays, which often come with fluorescence detection, are major qualitative and quantitative tools in clinical analysis. While Infrared and Raman spectroscopies do not give extensive information about urine, they could become important tools for the routine clinical diagnostics of kidney problems, due to rapidness and low-cost. Thus, it is important to review all the applicable techniques and methods related to urine analysis. In this review, a brief overview of each technique's principle is introduced. Where applicable, research papers about protein determination in urine are summarized with the main figures of merits, such as the limit of detection, the detectable range, recovery and accuracy, when available.

Plasma Proteome Profiling of Coronary Artery Disease Patients: Downregulation of Transthyretin-An Important Event

Coronary artery disease (CAD) is a prevalent chronic inflammatory cardiac disorder. An early diagnosis is likely to help in the prevention and proper management of this disease. As the study of proteomics provides the potential markers for detection of a disease, in the present investigation, attempt has been made to identify disease-associated differential proteins involved in CAD pathogenesis. For this study, a total of 200 selected CAD patients were considered, who were recruited for percutaneous coronary intervention (PCI) treatment. The proteomic analysis was performed using two-dimensional gel electrophoresis (2-DE) and MALDI-TOF MS/MS. Samples were also subjected to Western blot analysis, enzyme-linked immunosorbent assay (ELISA), peripheral blood mononuclear cells isolation immunofluorescence (IF) analysis, analytical screening by fluorescence-activated cell sorting (FACS), and in silico analysis. The representative data were shown as mean ± SD of at least three experiments. A total of 19 proteins were identified. Among them, the most abundant five proteins (serotransferrin, talin-1, alpha-2HS glycoprotein, transthyretin (TTR), fibrinogen-α chain) were found to have altered level in CAD. Serotransferrin, talin-1, alpha-2HS glycoprotein, and transthyretin (TTR) were found to have lower level, whereas fibrinogen-α chain was found to have higher level in CAD plasma compared to healthy, confirmed by Western blot analysis. TTR, an important acute phase transport protein, was validated low level in 200 CAD patients who confirmed to undergo PCI treatment. Further, in silico and in vitro studies of TTR indicated a downexpression of CAD in plasma as compared to the plasma of healthy individuals. Lower level of plasma TTR was determined to be an important risk marker in the atherosclerotic-approved CAD patients. We suggest that the TTR lower level predicts disease severity and hence may serve as an important marker tool for CAD screening. However, further large-scale studies are required to determine the clinical significance of TTR.

Identifying Synergistic Mechanisms of Multiple Ingredients in Shuangbai Tablets against Proteinuria by Virtual Screening and a Network Pharmacology Approach

Shuangbai Tablets (SBT), a traditional herbal mixture, has shown substantial clinical efficacy. However, a systematic mechanism of its active ingredients and pharmacological mechanisms of action against proteinuria continues being lacking. A network pharmacology approach was effectual in discovering the relationship of multiple ingredients and targets of the herbal mixture. This study aimed to identify key targets, major active ingredients, and pathways of SBT against proteinuria by network pharmacology approach combined with thin layer chromatography (TLC). Human phenotype (HP) disease analysis, gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and molecular docking were used in this study. To this end, a total of 48 candidate targets of 118 active ingredients of SBT were identified. Network analysis showed PTGS2, ESR1, and NOS2 to be the three key targets, and beta-sitosterol, quercetin, and berberine were the three major active ingredients; among them one of the major active ingredients, quercetin, was discriminated by TLC. These results of the functional enrichment analysis indicated that the most relevant disease including these 48 candidate proteins is proteinuria, SBT treated proteinuria by sympathetically regulating multiple biological pathways, such as the HIF-1, RAS, AGE-RAGE, and VEGF signaling pathways. Additionally, molecular docking validation suggested that major active ingredients of SBT were capable of binding to HIF-1A and VEGFA of the main pathways. Consequently, key targets, major active ingredients, and pathways based on data analysis of SBT against proteinuria were systematically identified confirming its utility and providing a new drug against proteinuria.

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.

Multi-Omics Approach: New Potential Key Mechanisms Implicated in Cardiorenal Syndromes

Cardiorenal syndromes (CRS) include a scenario of clinical interactions characterized by the heart and kidney dysfunction. The crosstalk between cardiac and renal systems is clearly evidenced but not completely understood. Multi-factorial mechanisms leading to CRS do not involve only hemodynamic parameters. In fact, in recent works on organ crosstalk endothelial injury, the alteration of normal immunologic balance, cell death, inflammatory cascades, cell adhesion molecules, cytokine and chemokine overexpression, neutrophil migration, leukocyte trafficking, caspase-mediated induction of apoptotic mechanisms and oxidative stress has been demonstrated to induce distant organ dysfunction. Furthermore, new alternative mechanisms using the multi-omics approach may be implicated in the pathogenesis of cardiorenal crosstalk. The study of “omics” modifications in the setting of cardiovascular and renal disease represents an emerging area of research. Over the last years, indeed, many studies have elucidated the exact mechanisms involved in gene expression and regulation, cellular communication and organ crosstalk. In this review, we analyze epigenetics, gene expression, small non-coding RNAs, extracellular vesicles, proteomics, and metabolomics in the setting of CRS.

Molecular Network Analysis of the Urinary Proteome of Alzheimer's Disease Patients

Background/Aims

The identification of predictive biomarkers for Alzheimer's disease (AD) from urine would aid in screening for the disease, but information about biological and pathophysiological changes in the urine of AD patients is limited. This study aimed to explore the comprehensive profile and molecular network relations of urinary proteins in AD patients.

Methods

Urine samples collected from 18 AD patients and 18 age- and sex-matched cognitively normal controls were analyzed by mass spectrometry and semiquantified with the normalized spectral index method. Bioinformatics analyses were performed on proteins which significantly increased by more than 2-fold or decreased by less than 0.5-fold compared to the control (p < 0.05) using DAVID bioinformatics resources and KeyMolnet software.

Results

The levels of 109 proteins significantly differed between AD patients and controls. Among these, annotation clusters related to lysosomes, complement activation, and gluconeogenesis were significantly enriched. The molecular relation networks derived from these proteins were mainly associated with pathways of lipoprotein metabolism, heat shock protein 90 signaling, matrix metalloproteinase signaling, and redox regulation by thioredoxin.

Conclusion

Our findings suggest that changes in the urinary proteome of AD patients reflect systemic changes related to AD pathophysiology.

Sample Treatment for Urine Proteomics

Urine is a biological fluid that can be collected noninvasively in relatively large quantities which can be used for the search of biomarkers of disease, both diseases of the urological tract and systemic diseases. One of the most important aspects in proteomic studies is sample treatment before further analysis. Methods of preparation of a urine sample depend on the techniques that will be used later for separation and identification of the proteins. Also, urine preparation should be as simple as possible to increase reproducibility. Normal urine has a much diluted protein concentration with a high-salt content, which interferes with proteomic analysis. Thus, an initial step in the handling of urine sample should be to concentrate and eliminate salts. As range of protein concentrations in urine spans several orders of magnitude, effective proteomic analyses require either removal of most abundant protein or enrichment of the less abundant ones. In this chapter, we discuss the aspects related to the collection and treatment of urine for proteomic studies.

Analysis of the mutations in exon 10 of MEFV gene in patients with premature coronary heart disease in west Azerbaijan province of Iran

Introduction: Premature coronary heart disease (PCHD) affects public health and leads to death. PCHD has several genetic and environmental risk factors. The aim of this study was to analysis of the mutations in exon 10 of MEFV gene in patients with PCHD in West Azerbaijan province of Iran.

Methods: Totally 41 PCHD patients who were admitted to the cardiology unit of Sayedoshohada hospital (Urmia, Iran) enrolled in the study. Selection of the patients was done based on the strict criteria, that is, who had a minimum of one angiographically documented coronary artery with the stenosis of 50%. Mutations in exon 10 of MEFV gene were found by direct sequencing.

Results: V726A, M680I, K695R, and A744S mutations with 2.44%, 1.22%, 1.22%, and 1.22%, allelic frequency were found, respectively. Five patients (12.2%) with PCHD carried at least one mutated MEFV allele. Heterozygote V726A was the most frequent mutation among tested cases (4.88%), followed by heterozygote M680I, heterozygote K695R, and heterozygote A744S.

Conclusion: The results of the present study imply that the frequency of the MEFV gene exon 10 is significantly high in PCHD patients. This is the first report in its own kind in clinically diagnosed PCHD pa­tients of Iranian Azeri Turkish population.