Biomarkers for prevention, early diagnosis, and prognosis of cardiovascular diseases

Extracellular vesicles (EVs) are diverse, membrane-bound vesicles released from cells into the extracellular environment. They originate from either endosomes or the cell membrane and typically include exosomes and microvesicles. These EVs serve as crucial mediators of intercellular communication, carrying a variety of contents such as nucleic acids, proteins, and lipids, which regulate the physiological and pathological processes of target cells. Moreover, the molecular cargo of EVs can reflect critical information about the originating cells, making them potential biomarkers for the diagnosis and prognosis of diseases. Over the past decade, the role of EVs as key communicators between cell types in cardiovascular physiology and pathology has gained increasing recognition. EVs from different cellular sources, or from the same source under different cellular conditions, can have distinct impacts on the management, diagnosis, and prognosis of cardiovascular diseases. Furthermore, it is essential to consider the influence of cardiovascular-derived EVs on the metabolism of peripheral organs. This review aims to summarize recent advancements in the field of cardiovascular research with respect to the roles and implications of EVs. Our goal is to provide new insights and directions for the early prevention and treatment of cardiovascular diseases, with an emphasis on the therapeutic potential and diagnostic value of EVs.

Cardiology and big data: a call for papers

Cardiovascular diseases (CVD) are the major causative factors for high mortality and morbidity in developing and developed nations. The biomarker detection plays a crucial role in the early diagnosis of several non-infectious and life-threatening diseases like CVD and many cancers, which in turn will help in more successful therapy, reducing the mortality rate. Biomarkers have diagnostic, prognostic and therapeutic significances. The search for novel biomarkers using proteomics, bio-sensing, micro-fluidics, and spectroscopic techniques with good sensitivity and specificity for CVD is progressing rapidly at present, in addition to the use of gold standard biomarkers like troponin. This review is dealing with the current progress and prospects in biomarker research for the diagnosis of cardiovascular diseases.Expert opinion.Fast diagnosis of cardiovascular diseases (CVDs) can help to provide rapid medical intervention, which can affect the patient’s short and long-term health. Identification and detection of proper biomarkers for early diagnosis are crucial for successful therapy and prognosis of CVDs. The present review discusses the analysis of clinical samples such as whole blood, blood serum, and other body fluids using techniques like high-performance liquid chromatography-LASER/LED-induced fluorescence, Raman spectroscopy, mainly, optical methods, combined with nanotechnology and micro-fluidic technologies, to probe patterns of multiple markers (marker signatures) as compared to conventional techniques.

Cardiovascular diseases are one of the most common causes of death in both developing and developed countries worldwide. Even though there have been improvements in primary prevention, the prevalence of cardiovascular diseases continues to increase in recent years. Hence, it is crucial to both investigate the molecular pathophysiology of cardiovascular diseases in-depth and find novel biomarkers regarding the early and proper prevention and diagnosis of these diseases. MicroRNAs, or miRNAs, are endogenous, conserved, single-stranded non-coding RNAs of 21-25 nucleotides in length. miRNAs have important roles in various cellular events such as embryogenesis, proliferation, vasculogenesis, apoptosis, cell growth, differentiation, and tumorigenesis. They also have potential roles in the cardiovascular system, including angiogenesis, cardiac cell contractility, control of lipid metabolism, plaque formation, the arrangement of cardiac rhythm, and cardiac cell growth. Circulating miRNAs are promising novel biomarkers for purposes of the diagnosis and prognosis of cardiovascular diseases. Cell or tissue specificity, stability in serum or plasma, resistance to degradative factors such as freeze-thaw cycles or enzymes in the blood, and fast-release kinetics, provide the potential for miRNAs to be surrogate markers for the early and accurate diagnosis of disease and for predicting middle- or long-term prognosis. Moreover, it may be a logical approach to combine miRNAs with traditional biomarkers to improve risk stratification and long-term prognosis. In addition to their efficacy in both diagnosis and prognosis, miRNA-based therapeutics may be beneficial for treating cardiovascular diseases using novel platforms and computational tools and in combination with traditional methods of analysis. microRNAs are promising, novel therapeutic agents, which can affect multiple genes using different signaling pathways. miRNAs therapeutic modulation techniques have been used in the settings of atherosclerosis, acute myocardial infarction, restenosis, vascular remodeling, arrhythmias, hypertrophy and fibrosis, angiogenesis and cardiogenesis, aortic aneurysm, pulmonary hypertension, and ischemic injury. This review presents detailed information about miRNAs regarding structure and biogenesis, stages of synthesis and functions, expression profiles in serum/plasma of living organisms, diagnostic and prognostic potential as novel biomarkers, and therapeutic applications in various diseases.

Recent studies in animal models and humans show that long non-coding RNAs (lncRNAs) are involved in the development of atherosclerosis, which contributes to the pathological foundation of coronary artery disease (CAD). LncRNAs in plasma and serum have been considered as promising novel biomarkers for diagnosis and prognosis of cardiovascular diseases, especially CAD. We here measured the circulating levels of 8 individual lncRNAs which are known to be relevant to atherosclerosis in the plasma samples from 300 patients with CAD and 180 control subjects by using quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) methods. We found that the plasma level of H19 and long intergenic non-coding RNA predicting cardiac remodeling (LIPCAR) were significantly increased in patients with CAD. The area under the receiver operating characteristic curve was 0.631 for H19 and 0.722 for LIPCAR. Multivariate logistic regression analyses indicated that plasma H19 and LIPCAR were independent predictors for CAD, even after adjustment for traditional cardiovascular risk factors. Further studies identified that plasma levels of H19 and LIPCAR were also increased in CAD patients with heart failure compared to those with normal cardiac function. Taken together, our results suggest that increased plasma levels of H19 and LIPCAR are associated with increased risk of CAD and may be considered as novel biomarkers for CAD.

Exosomes can reach distant tissues through blood circulation to communicate directly with target cells and rapidly regulate intracellular signals. Exosomes play an important role in cardiovascular pathophysiology. Different exosomes derived from different sources, and their cargos have different mechanisms of action. In addition to being biomarkers, exosomes also have a certain significance in the diagnosis, treatment, and even prevention of cardiovascular diseases. Here, we provide a review of the up-to-date applications of exosomes, derived from various sources, in the prognosis and diagnosis of cardiovascular diseases.

Electrocardiogram (ECG) plays a vital role in the prevention, diagnosis, and prognosis of cardiovascular diseases (CVDs). However, the lack of a user-friendly and accurate long-term dynamic electrocardiogram (DCG) device in motion has made it challenging to perform many daily cardiovascular risk screenings and assessments, such as sudden cardiac arrest, resulting in additional economic burdens on society. Here, we present a motion-unrestricted dynamic electrocardiogram (MU-DCG) system, which employs skin-conformal, imperceptible electronics for long-term, comfortable, and accurate 12-lead DCG monitoring. To facilitate assembly for use on the skin, the MU-DCG system features a pressure-activated flexible skin socket for stably soft-connecting the on-skin soft module and the off-skin stiff module during dynamic movements. Crucially, blinded cardiologist evaluations confirm minimal motion artifacts in MU-DCG-acquired ECG signals. Our results demonstrate that the MU-DCG system, with large-area, ultra-thin on-skin electrodes/leads, and an off-skin module, accomplishes anti-motion interference acquisition and in-situ analysis while retaining wearing imperceptibility.

The early diagnosis and real-time prognosis of cardiovascular diseases (CVDs) at the bedside are important. However, real-time detection of myocardial infarction involves the use of large-scale instrumentation and long test times. Herein, a simple, rapid and sensitive lateral flow immunochromatographic strip (LFIS) based on Yb/Er co-doped NaYF4 upconversion nanoparticles (UCNPs) was demonstrated for use in the detection of myocardial infarction. First, through heavy Yb/Er doping and an inert NaYF4 shell coating on the nanoparticles, the surface-related luminescence quenching effect of UCNPs was eliminated to enhance the upconversion luminescence. Second, through uniform coating of a SiO2 layer on the UCNPs, the biological affinity was improved to couple UCNPs and antibody proteins. Finally, through modification and activation with a specific antibody protein (serum amyloid A (SAA)), the UCNPs exhibited intense upconversion luminescence and high specificity when applied as a lateral flow immunochromatographic strip (LFIS). The developed UC-LFIS was highly sensitive (0.1 μg mL-1) and specific for detecting SAA in only 10 μL of serum. The UC-LFIS holds great potential for the early diagnosis and prognosis of CVDs.

The completion of the Human Genome Project has unleashed a wealth of human genomics information, but it remains unclear how best to implement this information for the benefit of patients. The standard approach of biomedical research, with researchers pursuing advances in knowledge in the laboratory and, separately, clinicians translating research findings into the clinic as much as decades later, will need to give way to new interdisciplinary models for research in genomic medicine. These models should include scientists and clinicians actively working as teams to study patients and populations recruited in clinical settings and communities to make genomics discoveries-through the combined efforts of data scientists, clinical researchers, epidemiologists, and basic scientists-and to rapidly apply these discoveries in the clinic for the prediction, prevention, diagnosis, prognosis, and treatment of cardiovascular diseases and stroke. The highly publicized US Precision Medicine Initiative, also known as All of Us, is a large-scale program funded by the US National Institutes of Health that will energize these efforts, but several ongoing studies such as the UK Biobank Initiative; the Million Veteran Program; the Electronic Medical Records and Genomics Network; the Kaiser Permanente Research Program on Genes, Environment and Health; and the DiscovEHR collaboration are already providing exemplary models of this kind of interdisciplinary work. In this statement, we outline the opportunities and challenges in broadly implementing new interdisciplinary models in academic medical centers and community settings and bringing the promise of genomics to fruition.

Metabolic and atherosclerotic cardiovascular diseases are a global problem for humanity due to high morbidity, disability, and mortality, despite the continuous improvement of methods of diagnosis and treatment. Objective. Based on the analysis of new literature data on the antioxidant, metabolic, immunosuppressive, and endocrine functions of bilirubin, to identify promising areas for their use in the prevention, diagnosis, and treatment of metabolic and atherosclerotic cardiovascular diseases. Material and methods. The search for Russian- and English-language publications was performed in the PubMed, Medscape, Cochrane Library databases, and the eLibrary scientific electronic library. The depth of article search was 2014—2023. The analysis includes 60publications that meet the selection criteria. Results. The data presented in the review are often controversial. However, most studies have found an adverse effect of low blood bilirubin on the course and prognosis of many metabolic and atherosclerotic cardiovascular diseases, and the use of promising strategies to increase the level of bilirubin in the blood improved the results of therapeutic and surgical treatment. Conclusion. The lack of effectiveness of currently available strategies for the prevention and treatment of metabolic and atherosclerotic cardiovascular diseases enables considering the level of blood bilirubin as a new promising target for improving the results of prevention, diagnosis, and treatment of these diseases.

The increasing incidence of cardiovascular disease (CVD) is a significant global health concern, affecting millions of individuals each year. Accurate diagnosis of acute CVD poses a formidable challenge, as misdiagnosis can significantly decrease patient survival rates. Traditional biomarkers have played a vital role in the diagnosis and prognosis of CVDs, but they can be influenced by various factors, such as age, sex, and renal function. Soluble ST2 (sST2) is a novel biomarker that is closely associated with different CVDs. Its low reference change value makes it suitable for continuous measurement, unaffected by age, kidney function, and other confounding factors, facilitating risk stratification of CVDs. Furthermore, the combination of sST2 with other biomarkers can enhance diagnostic accuracy and prognostic value. This review aims to provide a comprehensive overview of sST2, focusing on its diagnostic and prognostic value as a myocardial marker for different types of CVDs and discussing the current limitations of sST2.

Intracellular microRNAs (miRNAs) can be released into extracellular compartments, thus entering into body fluids such as blood circulation. Circulating miRNAs are highly stable and considered as novel biomarkers for the diagnosis and/or prognosis of cardiovascular diseases (CVDs). There is a growing body of evidence supporting circulating miRNAs as prognosis and/or diagnosis biomarkers for CVDs. Using the signatures of circulating miRNAs could improve sensitivity and specificity as biomarkers for CVDs, including unstable angina, myocardial infarction, in-stent restenosis after coronary drug-eluting stents implantation, atrial fibrillation, and heart failure. Circulating miRNAs are associated with other traditional CVD biomarkers such as cardiac-specific troponin, myoglobin and creatine kinase-MB, and other CVD risk factors such as diabetes mellitus and hyperlipidemia. The present review is different with other review articles in that we provide detailed information for individual miRNAs, including both clinical and basic science data. We have selected the 8 miRNAs (miR-1, miR-21, miR-126, miR-133, miR-145, miR-208, miR-223, and miR-499) that are most studied and have shown major clinical value as biomarkers for CADs. The purpose of this review is to provide a full-spectrum overview of these miRNAs and to help clinicians/researchers to understand the clinical value of major circulating miRNAs and help them to design or participate in further investigations of these miRNAs, developing new technologies to improve health care for patients with CVDs.

With the rapid development of artificial intelligence (AI) and machine learning (ML), as well as the arrival of the big data era, technological innovations have occurred in the field of cardiovascular medicine. First, the diagnosis of cardiovascular diseases (CVDs) is highly dependent on assistive examinations, the interpretation of which is time consuming and often limited by the knowledge level and clinical experience of doctors; however, AI could be used to automatically interpret the images obtained in auxiliary examinations. Second, some of the predictions of the incidence and prognosis of CVDs are limited in clinical practice by the use of traditional prediction models, but there may be occasions when AI-based prediction models perform well by using ML algorithms. Third, AI has been used to assist precise classification of CVDs by integrating a variety of medical data from patients, which helps better characterize the subgroups of heterogeneous diseases. To help clinicians better understand the applications of AI in CVDs, this review summarizes studies relating to AI-based diagnosis, prediction, and classification of CVDs. Finally, we discuss the challenges of applying AI to cardiovascular medicine.

Cardiovascular disease (CVD) is the leading cause of death in women. Clear gender differences exist in the incidence, prevalence, presentation, diagnosis, treatment, and prognosis of cardiovascular diseases. Over the past 15 years, robust efforts focused on the evidence-based prevention and treatment of CVD in women have resulted in a steeper decrease in cardiovascular (CV) mortality rates in women compared to men beginning in 2000. The prominent decline in female CV mortality rates is a new phenomenon, as decreases in male CV mortality rates outpaced those in women during the 1980s and 1990s. Historically, women have been underrepresented in clinical trials investigating cardiovascular diseases. Over the past decade, the representation of women in clinical trials has improved, and nuanced treatment approaches and prevention strategies have resulted from the dedicated study of gender differences. The traditional CV research focus has been on obstructive coronary disease and the development and complications of ischemic heart disease in men. Research has shown multiple layers of complexity in the etiology and pathophysiology of cardiovascular diseases in women differing from those predominating in men. Investigation has also shown a relationship between the hormonal fluctuations women experience throughout life and the development of ischemic heart disease and arrhythmias. Therefore, cardiovascular disease processes in women should not be equated to those traditionally encountered in the male population, and these differences should alter the physicians’ approach to the female patient.

The discovery of noncoding RNAs (ncRNAs) including short microRNAs, long ncRNAs and circular RNAs has broaden our knowledge about mammalian genomes and transcriptomes. A growing number of evidence on aberrantly regulated ncRNAs in cardiovascular diseases has indicated that ncRNAs are critical contributors to cardiovascular pathophysiology. Moreover, multiple recent studies have reported that ncRNAs can be detected in the bloodstream that differs between health subjects and diseased patients and some of them are remarkably stable. Although our knowledge about the origin and function of the circulating ncRNAs is still limited, these molecules have been regarded as promising noninvasive biomarker for risk stratification, diagnosis and prognosis of various cardiovascular diseases. In this chapter, we have described biological characteristics of circulating ncRNAs and discussed current trends and future prospects for the usage of circulating ncRNAs as biomarkers for common cardiovascular diseases.