Noncoding RNAs (ncRNAs) are pivotal for various pathological processes, impacting disease progression. The potential for leveraging ncRNAs to prevent or treat atherosclerosis and associated cardiovascular diseases is of great significance, especially given the increasing prevalence of atherosclerosis in an ageing and sedentary population. Together, these diseases impose a substantial socio-economic burden, demanding innovative therapeutic solutions. This review explores the potential of ncRNAs in atherosclerosis treatment. We commence by examining approaches for identifying and characterizing atherosclerosis-associated ncRNAs. We then delve into the functional aspects of ncRNAs in atherosclerosis development and progression. Additionally, we review current RNA and RNA-targeting molecules in development or under approval for clinical use, offering insights into their pharmacological potential. The importance of improved ncRNA delivery strategies is highlighted. Finally, we suggest avenues for advanced research to accelerate the use of ncRNAs in treating atherosclerosis and mitigating its societal impact.

Introduction: Hypertension is a major and modifiable risk factor for cardiovascular diseases. Essential, primary, or idiopathic hypertension accounts for 90–95% of all cases. Identifying novel biomarkers specific to essential hypertension may help in understanding pathophysiological pathways and developing personalized treatments. We tested whether the integration of circulating microRNAs (miRNAs) and clinical risk factors via machine learning modeling may provide useful information and novel tools for essential hypertension diagnosis and management. Materials and methods: In total, 174 participants were enrolled in the present observational case–control study, among which, there were 89 patients with essential hypertension and 85 controls. A discovery phase was conducted using small RNA sequencing in whole blood samples obtained from age- and sex-matched hypertension patients (n = 30) and controls (n = 30). A validation phase using RT-qPCR involved the remaining 114 participants. For machine learning, 170 participants with complete data were used to generate and evaluate the classification model. Results: Small RNA sequencing identified seven miRNAs downregulated in hypertensive patients as compared with controls in the discovery group, of which six were confirmed with RT-qPCR. In the validation group, miR-210-3p/361-3p/362-5p/378a-5p/501-5p were also downregulated in hypertensive patients. A machine learning support vector machine (SVM) model including clinical risk factors (sex, BMI, alcohol use, current smoker, and hypertension family history), miR-361-3p, and miR-501-5p was able to classify hypertension patients in a test dataset with an AUC of 0.90, a balanced accuracy of 0.87, a sensitivity of 0.83, and a specificity of 0.91. While five miRNAs exhibited substantial downregulation in hypertension patients, only miR-361-3p and miR-501-5p, alongside clinical risk factors, were consistently chosen in at least eight out of ten sub-training sets within the SVM model. Conclusions: This study highlights the potential significance of miRNA-based biomarkers in deepening our understanding of hypertension’s pathophysiology and in personalizing treatment strategies. The strong performance of the SVM model highlights its potential as a valuable asset for diagnosing and managing essential hypertension. The model remains to be extensively validated in independent patient cohorts before evaluating its added value in a clinical setting.

Aim of this paper was to determine the frequency of congenital anomalies in a sample of newborns of Tuzla Canton and as well as their distribution according to gender, mother’s age and marital distance category. Research was undertaken using the retrospective analysis on the Clinic for Gynecology and Obstetrics of University Clinical Center in Tuzla. By analyzing medical documentation of 17223 newborns, we determined the frequency of congenital anomalies of 5.24%. Highest frequency of congenital anomalies was found in the newborns whose mothers are older than 35. It was found that the frequency of congenital anomalies in the observed population is within the range of variation of this parameter with data from the literature.

Abstract The coronavirus disease 2019 (COVID-19) pandemic has been as unprecedented as unexpected, affecting more than 105 million people worldwide as of 8 February 2020 and causing more than 2.3 million deaths according to the World Health Organization (WHO). Not only affecting the lungs but also provoking acute respiratory distress, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is able to infect multiple cell types including cardiac and vascular cells. Hence a significant proportion of infected patients develop cardiac events, such as arrhythmias and heart failure. Patients with cardiovascular comorbidities are at highest risk of cardiac death. To face the pandemic and limit its burden, health authorities have launched several fast-track calls for research projects aiming to develop rapid strategies to combat the disease, as well as longer-term projects to prepare for the future. Biomarkers have the possibility to aid in clinical decision-making and tailoring healthcare in order to improve patient quality of life. The biomarker potential of circulating RNAs has been recognized in several disease conditions, including cardiovascular disease. RNA biomarkers may be useful in the current COVID-19 situation. The discovery, validation, and marketing of novel biomarkers, including RNA biomarkers, require multi-centre studies by large and interdisciplinary collaborative networks, involving both the academia and the industry. Here, members of the EU-CardioRNA COST Action CA17129 summarize the current knowledge about the strain that COVID-19 places on the cardiovascular system and discuss how RNA biomarkers can aid to limit this burden. They present the benefits and challenges of the discovery of novel RNA biomarkers, the need for networking efforts, and the added value of artificial intelligence to achieve reliable advances.

Cardiovascular disease (CVD) is the biggest cause of sickness and mortality worldwide in both males and females. Clinical statistics demonstrate clear sex differences in risk, prevalence, mortality rates, and response to treatment for different entities of CVD. The reason for this remains poorly understood. Non-coding RNAs (ncRNAs) are emerging as key mediators and biomarkers of CVD. Similarly, current knowledge on differential regulation, expression, and pathology-associated function of ncRNAs between sexes is minimal. Here, we provide a state-of-the-art overview of what is known on sex differences in ncRNA research in CVD as well as discussing the contributing biological factors to this sex dimorphism including genetic and epigenetic factors and sex hormone regulation of transcription. We then focus on the experimental models of CVD and their use in translational ncRNA research in the cardiovascular field. In particular, we want to highlight the importance of considering sex of the cellular and pre-clinical models in clinical studies in ncRNA research and to carefully consider the appropriate experimental models most applicable to human patient populations. Moreover, we aim to identify sex-specific targets for treatment and diagnosis for the biggest socioeconomic health problem globally.

BACKGROUND AND OBJECTIVE The SOX2OT lcnRNA has been recognized as positive regulator in transcription regulation of SOX2 gene. Recent studies have approved the dysregulation of SOX2OT lncRNA expression patterns in some common caner types including esophageal, lung, and breast cancer. The objective of present study was to investigate correlation between overexpression of SOX2OT lcnRNA and susceptibility to breast cancer. METHOD SOX2OT lncRNA expression profiling in 15 breast cancer and normal tumour-adjacent breast tissue samples was performed by using qRT-PCR. To evaluating the diagnostic potential of the SOX2OT lncRNA we performed ROC curve analyses. RESULTS The expression of SOX2OT lncRNA in patients suffering from breast cancer revealed a significant overexpression in comparison with the healthy group (P<0.001). Significantly, the elevated circulating SOX2OT lncRNA was found specific to breast cancer and could differentiate breast cancer from controls with 100% of both sensitivity of and specificity. Based on the Kaplan-Meier analysis, there were no significant correlation between SOX2OT lcnRNA expression and overall survival. CONCLUSION The results confirmed the association between breast cancer and higher SOX2OT lncRNA expression. According to the ROC curve results, SOX2OT lcnRNA could be a new measurable indicator of the breast cancer and a potential therapeutic target for breast cancer patients.

Analysis of 4G/5G polymorphisms of PAI-1 gene in interaction with other genetic and external risk factors that induce development of venous thromboembolism can be used for risk assessment for development of venous thromboembolism. Research was conducted on 202 examinees of both genders, older than 18, from north-eastern Bosnia. Experimental group included 100 examinees with diagnosed DVT and 101 examinees who until the sampling procedure did not have diagnosed DVT. In DVT group, following genotype frequencies were determined: 27% of examinees had a normal genotype 5G/5G, 68% are heterozygotes and 5% are mutated homozygotes 4G/4G. In the control group, frequencies of 4G/5G polymorphisms of PAI-1 gene were: 42.6% of examinees have 5G/5G genotype, 55.4% are heterozygotes 4G/5G and 2% are 4G/4G genotype. Obtained results support the hypothesis that PAI-1 in interaction with other genetic and external risk factors probably induces the development of venous thromboembolism.

Objective Recent data suggest that increased levels of the HOTAIR long non-coding RNA (lncRNA) are involved in the development of various types of malignancy, including breast cancer. The aim of present study was to investigate HOTAIR lncRNA expression profile in breast cancer (BC) patients and cell lines. Materials and Methods In this experimental study, expression level of HOTAIR lncRNA was evaluated in BC and normal tissues of 15 patients as well as MDA-MB-231, MCF-7 and MCF-10A cell lines, using quantitative reverse- transcription polymerase chain reaction (qRT-PCR). HOTAIR lncRNA expression levels were estimated using 2-ΔΔCt method. Further, receiver operating characteristic (ROC) curve analysis was done to evaluate the selected lncRNA diagnostic potential. The Cox’s proportional hazards regression model was performed to evaluate the predictive value of this lncRNA level in BC patients. Results The results of present study demonstrated no significant difference in the expression of HOTAIR lncRNA in MCF7 and MDA-MB-231 cancer cell lines compared to MCF-10A as normal cell line (P>0.05). However, we observed a significantly increase in the expression of HOTAIR in BC patients compared to normal tissues (P<0.001). Significant associations were found between gene expression and tumour size and margin. We found 91.1% sensitivity and 95.7% specificity of circulating HOTAIR with an area under the ROC curve of 0.969. The Kaplan-Meier analysis indicated significant correlation between HOTAIR expression and overall survival. Conclusion This study demonstrated that expression of HOTAIR is increased in BC and might be associated with its progression. According to these findings, HOTAIR expression could be proposed as biomarkers for BC early diagnosis and prognosis.

High blood pressure or hypertension is an outstanding public health problem affecting nearly 40% of the World’s adult population. Prevalence of hypertension has a strong socioeconomic impact and health burden. Recently, hypertension has reached epidemic proportions, and it is estimated that ≈25% of adult individuals will be hypertensive in the World by 2025. Untreated hypertension can result in various health complications, such as stroke, myocardial infarction, vascular disease, and chronic kidney diseases. Generally, hypertension is categorized as either primary or secondary according to its cause. However, there are several types of hypertension that are more or less common such as essential hypertension (EHT), pulmonary hypertension (PHT), pulmonary arterial hypertension (PAHT), white coat hypertension, and nocturnal hypertension. This article focuses on the 3 first types for which a significant amount of information on the role of noncoding RNAs (ncRNAs) is available. Essential, primary, or idiopathic hypertension refers to elevated blood pressure in which secondary causes such as renovascular disease, renal failure, pheochromocytoma, aldosteronism, or other causes of secondary hypertension, or Mendelian forms are not present. EHT is the most frequent type of hypertension, which accounts for 95% of all cases. PHT refers to an elevation of the pulmonary arterial pressure above 25 mm Hg at rest as assessed by right heart catheterization. This elevation can be caused by different underlying diseases, such as liver disease, thromboembolic disease, rheumatic disorders, lung conditions, including tumors, chronic obstructive pulmonary disease, pulmonary fibrosis, or cardiovascular diseases, including aortic valve disease, heart failure, and congenital heart disease. According to the latest World Health Organization classification, PHT is classified depending on its cause into 5 groups: PAHT, PHT caused by left heart disease, PHT caused by lung disease, PHT caused by chronic blood clots, and PHT associated with other unclear conditions. PAHT is defined as pulmonary vasculopathy and progressive pulmonary vasculature remodeling that cause the rise of pulmonary arterial pressure. Although PAHT is classified as a specific subgroup of PHT, in the literature, PHT is often used instead of PAHT. Thus, while PHT refers to an elevation of pressure in the lung arteries caused by a side disease, PAHT is caused by remodeling of pulmonary blood vessels. Owing to the fact that blood pressure is regulated by multiple physiological pathways, it is difficult to decipher a single causative agent of hypertension. Recent studies have shown that complex multifactorial cause of hypertension results from a dynamic interplay of genetic and environmental factors. Polygenic nature of hypertension involves many genes each with mild cumulative effects reacting to environmental factors that contribute to hypertension. Population-based studies have demonstrated that Mendelian forms of hypertension can be found in about 20% of families and reach 60% in twins. Integration of data from genome-wide linkage and association studies and system genetics approaches allowed the identification of >100 single nucleotide polymorphisms implicated in high blood pressure. Studies aiming to decipher the molecular pathways of high blood pressure have identified genes involved in the renin-angiotensin-aldosterone system (RAAS), signaling through G protein-coupled receptors, vascular inflammation, remodeling, and in the structure and regulation of vascular senescence and developmental programming. Although significant progress has been achieved in elucidating the molecular pathways involved in the pathophysiology of hypertension, the regulatory function of these pathways remains to be fully elucidated. Recent advances in epigenetics may provide at least some of the missing pieces of the hereditary puzzle that can explain the fact that a same genome can provide distinct phenotypes, without alterations in primary DNA structure. The key factor in figuring out the complex multifactorial nature of hypertension might well hence be the dark matter of the human genome. Indeed, while it used to be commonly accepted that each of human genes would encode proteins, it has more recently been discovered that the majority (>95%) of these genes are unable to produce proteins. These genes are transcribed into ncRNA molecules and they play multiple important roles in regulating protein-coding genes. The ubiquitous expression of ncRNAs allows them to regulate many physiological and pathological processes, in virtually all cell types. Because their discovery, ncRNAs have attracted an exponential interest by the biomedical research community, notably in the area of cardiovascular diseases and their major risk factor, hypertension. NcRNAs have been arbitrarily classified into short and long ncRNAs with a threshold of 200 nucleotides. In addition, ncRNAs have been classified according to their cellular localization (nuclear versus cytoplasmic), mechanism of action and