Search Results (1,808)

As people with cystic fibrosis (PwCF) live longer, kidney disease is emerging as a significant comorbidity that is increasingly linked to cardiovascular complications and progression to end-stage kidney disease. In our recent review, we proposed the unifying term CF-related kidney disease (CFKD) to encompass the spectrum of kidney dysfunction observed in this population. Early detection of kidney injury is critical for improving long-term outcomes, yet remains challenging due to the limited sensitivity of conventional laboratory tests, particularly in individuals with altered muscle mass and unique CF pathophysiology. Emerging approaches, including novel blood and urinary biomarkers, urinary extracellular vesicles, and genetic risk profiling, offer promising avenues for identifying subclinical kidney damage. When integrated with machine learning algorithms, these tools may enable the development of personalized risk stratification models and targeted therapeutic strategies. This precision medicine approach has the potential to transform kidney disease management in PwCF, shifting care from reactive treatment of late-stage disease to proactive monitoring and early intervention. Full article

Intravascular biosensors have become a crucial and novel class of devices in healthcare, enabling the constant real-time monitoring of essential physiological parameters directly within the circulatory system. Recent developments in micro- and nanotechnology have relevantly improved the sensitivity, miniaturization, and biocompatibility of these devices, thereby enabling their application in precision medicine. This review summarizes the latest advances in intravascular biosensor technologies, with a special focus on glucose and oxygen level monitoring, blood pressure and heart rate assessment, and early disease diagnostics, as well as modern approaches to drug therapy monitoring and delivery systems. Key challenges such as long-term biostability, signal accuracy, and regulatory approval processes are critical considerations. Innovative strategies, including biodegradable implants, nanomaterial-functionalized surfaces, and integration with artificial intelligence, are regarded as promising avenues to overcome current limitations. This review provides a comprehensive roadmap for upcoming research and the clinical translation of advanced intravascular biosensors with a strong emphasis on their transformative impact on personalized healthcare. Full article

Calcific aortic stenosis (CAS) is a newly emerging pandemic in elderly individuals due to the aging of the population in the world. Surgical Aortic Valve Replacement (SAVR) and Transcatheter Aortic Valve Replacement (TAVR) are the cornerstone of the management of severe aortic stenosis accompanied by one or more symptoms. Moreover, an appropriate interventional treatment of CAS, in elderly patients, is a very complex decision for heart teams, to avoid bad outcomes such as operative mortality, cardiovascular and all-cause death, hospitalization for heart failure, worsening of quality of life. In fact, CAS in the elderly is not only a focal valve disease, but a very complex clinical picture with different risk factors and etiologies, differing underlying pathophysiology, large phenotypic heterogeneity in a context of subjective biological, phenotypic and functional aging until frailty and disability. In this review, we analyzed separately and in a more integrated manner, the natural and prognostic histories of the progression of aortic stenosis, the phenotypes of myocardial damage and heart failure, within the metrics and aging trajectory. The aim is to suggest, during the clinical timing of valve disease, the best interval time for an appropriate and effective interventional treatment in each older patient, beyond subjective symptoms by integration of clinical, geriatric, chemical, and advanced imaging biomarkers. Full article

Blood-based biomarkers allow monitoring of an individual’s health status and provide insights into metabolic and inflammatory processes in conditions like obesity, cardiovascular, and liver diseases. However, selecting suitable biomarkers and optimizing analytical assays presents challenges, is time-consuming and laborious. Moreover, knowledge of potential sex differences remains incomplete as research is often carried out in men. This study aims at enabling researchers to make informed choices on the type of biomarkers, analytical assays, and dilutions being used. More specifically, we analyzed plasma concentrations of >90 biomarkers using commonly available ELISA or electrochemiluminescence-based multiplex methods, comparing normal weight (BMI < 25; n = 40) with obese (BMI > 30; n = 40) adult blood donors of comparable age. To help choose optimal biomarker sets, we grouped frequently employed biomarkers into biological categories (e.g., adipokines, acute-phase proteins, complement factors, cytokines, myokines, iron metabolism, vascular inflammation), first comparing normal-weight with obese persons, and thereafter exploratively comparing women and men within each BMI group. Many biomarkers linked to chronic inflammation and dysmetabolism were elevated in persons with obesity, including several adipokines, interleukins, chemokines, acute-phase proteins, complement factors, and oxidized LDL. Further exploration suggests sex disparities in biomarker levels within both normal-weight and obese groups. This comprehensive dataset of biomarkers across diverse biological domains constitutes a reference resource that may provide valuable guidance for researchers in selecting appropriate biomarkers and analytical assays for own studies. Moreover, the dataset highlights the importance of taking possible sex differences into account. Full article

Background: While epicardial adipose tissue (EAT) is a known predictor of adverse cardiovascular outcomes, lipomatous hypertrophy of the interatrial septum (LHIS) is composed of metabolically active fat such as brown adipose tissue, which may exert a different effect. This study investigates the coronary atherosclerosis profile in patients with LHIS using CTA, compared with a propensity score-matched control group. Methods: A total of 142 patients were included (n = 71 with LHIS and n = 71 controls) and propensity score-matched for age, gender, BMI, and the major CV risk factors (matching level, <0.05). CTA imaging parameters included HRP, coronary stenosis severity (CADRADS), and CAC score. Results: The mean age was 60.9 years +/− 10.6, there were nine (6.3%) women, and the mean BMI is 28.04 kg/m² +/− 4.99. HRP prevalence was significantly lower in LHIS patients vs. controls (21.1% vs. 40.8%; p < 0.011), while CAC (p = 0.827) and CADRADS (p = 0.329) were not different, and there was no difference in the obstructive disease rate. There was no difference in lipid panels (cholesterol, LDL, HDL, TG) and statin intake rate. Conclusions: HRP prevalence is lower in patients with LHIS than controls, while coronary stenosis severity and CAC score are not different. Clinical relevance: LHIS may serve as imaging biomarker for reversed CV risk. Full article

Growing interest in the future applications of nanotechnology in medicine has led to groundbreaking developments in nanosensors. Nanosensors are excellent platforms that provide reliable solutions for continuous monitoring and real-time detection of clinical targets. Nanosensors have attracted great attention due to their remarkable sensitivity, portability, selectivity, and automated data acquisition. The exceptional nanoscale properties of nanomaterials used in the nanosensors boost their sensing potential even at minimal concentrations of analytes present in a clinical sample. Along with applications in diverse sectors, the beneficial aspects of nanosensors have been exploited in healthcare systems to utilize their applications in diagnosing, treating, and preventing diseases. Hence, in this review, we have presented an overview of the disease-prognostic applications of nanosensors in chronic diseases through a detailed literature analysis. We focused on the advances in various nanosensors in the field of major diseases such as cancer, cardiovascular diseases, diabetes mellitus, and neurodegenerative diseases along with other prevalent diseases. This review demonstrates various categories of nanosensors with different nanoparticle compositions and detection methods suitable for specific diagnostic applications in clinical settings. The chemical properties of different nanoparticles provide unique characteristics to each nanosensors for their specific applications. This will aid the detection of potential biomarkers or pathological conditions that correlate with the early detection of various diseases. The potential challenges and possible recommendations of the applications of nanosensors for disease diagnosis are also discussed. The consolidated information present in the review will help to better understand the disease-prognostic potentials of nanosensors, which can be utilized to explore new avenues in improved therapeutic interventions and treatment modalities. Full article

Background: Statins exhibit pleiotropic anti-inflammatory, antioxidant, and immunomodulatory effects, suggesting their potential in non-cardiovascular conditions. However, evidence supporting their repurposing remains limited, and off-label prescribing policies vary globally. Objective: To systematically review evidence on statin repurposing in oncology and infectious diseases, and to assess Hungarian regulatory practices regarding off-label statin use. Methods: A systematic literature search (PubMed, Web of Science, Scopus, ScienceDirect; 2010–May 2025) was conducted using the terms “drug repositioning” OR “off-label prescription” AND “statin” NOT “cardiovascular,” following PRISMA guidelines. Hungarian off-label usage data from the NNGYK (2008–2025) were also analyzed. Results: Out of 205 publications, 12 met the inclusion criteria—75% were oncology-focused, and 25% focused on infectious diseases. Most were preclinical (58%); only 25% offered strong clinical evidence. Applications included hematologic malignancies, solid tumors, Cryptococcus neoformans, SARS-CoV-2, and dengue virus. Mechanisms involved mevalonate pathway inhibition and modulation of host immune responses. Hungarian data revealed five approved off-label statin uses—three dermatologic and two pediatric metabolic—supported by the literature and requiring post-treatment reporting. Conclusions: While preclinical findings are promising, clinical validation of off-label statin use remains limited. Statins should be continued in cancer patients with cardiovascular indications, but initiation for other purposes should be trial-based. Future directions include biomarker-based personalization, regulatory harmonization, and cost-effectiveness studies. Full article

Background: Metabolic syndrome (MetS) is a complex clinical condition characterized by the coexistence of interrelated metabolic abnormalities that significantly increase the risk of cardiovascular diseases and type 2 diabetes mellitus. Endocan—an endothelial cell-specific molecule—is considered a biomarker of endothelial dysfunction and inflammation. This study aimed to evaluate the relationship between serum endocan levels and the severity of MetS, assessed using the MetS-Z score. Methods: This study included 120 patients with MetS and 50 healthy controls. MetS was diagnosed according to the NCEP-ATP III criteria. MetS-Z scores were calculated using the MetS Severity Calculator. Serum levels of endocan, sICAM-1, and sVCAM-1 were measured using the ELISA method. Results: Serum levels of endocan, sICAM-1, and sVCAM-1 were significantly higher in the MetS group compared to the control group (all p < 0.001). When the MetS group was divided into tertiles based on MetS-Z scores, stepwise and statistically significant increases were observed in the levels of endocan and other endothelial markers from the lowest to highest tertile (p < 0.0001). Correlation analysis revealed a strong positive association between the MetS-Z score and serum endocan levels (r = 0.584, p < 0.0001). ROC curve analysis showed that endocan has high diagnostic accuracy for identifying MetS (AUC = 0.967, p = 0.0001), with a cutoff value of >88.0 ng/L. Conclusions: Circulating levels of endocan were significantly increased in MetS and were associated with the severity of MetS, suggesting that endocan may play a role in the cellular response to endothelial dysfunction-related injury in patients with MetS. Full article

Obstructive sleep apnea (OSA) is a prevalent disorder linked to metabolic complications such as diabetes and cardiovascular disease. By fragmenting normal sleep architecture, OSA perturbs the growth hormone/insulin-like growth factor (GH/IGF) axis and alters circulating levels of IGF-binding proteins (IGFBPs). A prior clinical observation of elevated IGFBP4 in OSA patients motivated the present investigation in a controlled animal model. Building on the previously reported protocol, OSA was induced in male C57BL/6 mice (9–12 weeks old) through intralingual injection of polytetrafluoroethylene (PTFE), producing tongue hypertrophy, intermittent airway obstruction, and hypoxemia. After 8–10 weeks, the study assessed (1) hypoxia biomarkers—including HIF-1α and VEGF expression—and (2) neurobehavioral outcomes in anxiety and cognition using the open-field and novel object recognition tests. PTFE-treated mice exhibited a significant increase in circulating IGFBP4 versus both baseline and control groups. Hepatic Igfbp4 mRNA was also upregulated. Behaviorally, PTFE mice displayed heightened anxiety-like behavior and impaired novel object recognition, paralleling cognitive deficits reported in human OSA. These findings validate the PTFE-induced model as a tool for studying OSA-related hypoxia and neurocognitive dysfunction, and they underscore IGFBP4 as a promising biomarker and potential mediator of OSA’s systemic effects. Full article

Diabetic nephropathy affects approximately 30–40% of individuals with diabetes mellitus (DM) and is a major contributor to end-stage renal disease (ESRD). While angiotensin II receptor blockers (ARBs) have long served as a standard treatment, sodium-glucose cotransporter-2 inhibitors (SGLT2i) have recently gained attention for their renal and cardiovascular benefits. However, comparative real-world data on their long-term renal effectiveness remain limited. We conducted a retrospective, longitudinal study over a 2-year period to compare the impact of ARB monotherapy versus SGLT2i and angiotensin-converting enzyme inhibitor (ACEi) combination therapy on the progression of chronic kidney disease (CKD) in patients with DM. A total of 126 patients were included and grouped based on treatment regimen. Renal biomarkers were analyzed using t-tests and ANOVA (p < 0.01). Albuminuria was qualitatively classified via urinalysis as negative, level 1 (+1), level 2 (+2), or level 3 (+3). The ARB group demonstrated higher estimated glomerular filtration rate (eGFR) and lower serum creatinine (sCr) levels than the combination therapy group, with glycated hemoglobin (HbA1c), potassium (K⁺), and blood pressure remaining within normal limits in both cohorts. Albuminuria remained stable over time, with 60.8% of ARB users and 73.1% of combination therapy users exhibiting persistently or on-average negative results. Despite the expected additive benefits of SGLT2i/ACEi therapy, ARB monotherapy was associated with slightly more favorable renal function markers and a lower incidence of severe albuminuria. These findings suggest a need for further controlled studies to clarify the comparative long-term renal effects of these treatment regimens. Full article

This review introduces a novel integrative framework linking gut dysbiosis, systemic inflammation, and cardiovascular risk in patients with inflammatory bowel disease (IBD). We highlight emerging biomarkers, including short-chain fatty acids (SCFAs), calprotectin, and zonulin, that reflect alterations in the gut microbiome and increased intestinal permeability, which contribute to cardiovascular pathology. Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, and recent evidence identifies IBD, encompassing ulcerative colitis (UC) and Crohn’s disease (CD), as a significant non-traditional risk factor for CVD. This review synthesizes current knowledge on how dysbiosis-driven inflammation in IBD patients exacerbates endothelial dysfunction, hypercoagulability, and atherosclerosis, even in the absence of traditional risk factors. Additionally, we discuss how commonly used IBD therapies may modulate cardiovascular risk. Understanding these multifactorial mechanisms and validating reliable biomarkers are essential for improving cardiovascular risk stratification and guiding targeted prevention strategies in this vulnerable population. Full article

Unhealthy dietary patterns are a major modifiable risk factor for atherosclerotic cardiovascular disease (ASCVD). International guidelines recommend reducing saturated fatty acid intake while increasing polyunsaturated and monounsaturated fatty acids (MUFAs) to mitigate cardiovascular risk. However, evidence regarding MUFAs and risk of ASCVD remains conflicting, with recent studies raising concern about a potential higher risk associated with MUFA intake. The aim of this narrative review is to provide an overview of current knowledge and gaps in the literature regarding MUFAs and the risk of ASCVD with a focus on intake, individual types, and content in adipose tissue as a biomarker of endogenous exposure. Main findings reveal that most studies have inappropriately combined all MUFAs together, despite individual MUFA types having different biological effects and showing varying correlations between dietary intake and adipose tissue content. Adipose tissue composition may serve as a biomarker of long-term MUFA exposure, reflecting cumulative intake over one to two years while minimizing biases inherent in dietary assessments. However, tissue levels reflect both dietary intake and endogenous synthesis, complicating interpretation. Importantly, the source of MUFAs appears critical, with plant-derived MUFAs potentially offering advantages over animal-derived sources. In conclusion, we suggest that future research should focus on individual MUFA types rather than treating them as a homogeneous group, investigate their specific dietary sources and associations with ASCVD risk, and use adipose tissue biomarkers to improve exposure assessment and clarify causal relationships while considering overall dietary patterns. Full article

Background and Objectives: Heart failure (HF) and chronic kidney disease (CKD) frequently coexist and are closely interrelated, significantly affecting clinical outcomes. Among CKD-related markers, albuminuria and estimated glomerular filtration rate (eGFR) have emerged as key prognostic indicators in HF. However, their specific predictive value across different HF phenotypes—namely HF with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF)—remains incompletely understood. This systematic review aims to evaluate the prognostic significance of albuminuria and eGFR in patients with HF and to compare their predictive roles in HFpEF versus HFrEF populations. Materials and Methods: We conducted a systematic search of major databases to identify clinical studies evaluating the association between albuminuria, eGFR, and adverse outcomes in HF patients. Inclusion criteria encompassed studies reporting on cardiovascular events, all-cause mortality, or HF-related hospitalizations, with subgroup analyses based on ejection fraction. Data extraction and quality assessment were performed independently by two reviewers. Results: Twenty-one studies met the inclusion criteria, including diverse HF populations and various biomarker assessment methods. Both albuminuria and reduced eGFR were consistently associated with increased risk of mortality and hospitalization. In HFrEF populations, reduced eGFR demonstrated stronger prognostic associations, whereas albuminuria was predictive across both HF phenotypes. Heterogeneity in study design and outcome definitions limited comparability. Conclusions: Albuminuria and eGFR are valuable prognostic biomarkers in HF and may enhance risk stratification and clinical decision-making, particularly when integrated into clinical assessment models. Differential prognostic implications in HFpEF versus HFrEF highlight the need for phenotype-specific approaches. Further research is warranted to validate these findings and clarify their role in guiding personalized therapeutic strategies in HF populations. Limitations: The current evidence base consists primarily of observational studies with variable methodological quality and inconsistent reporting of effect estimates. Full article

Background: This study presents an innovative approach to cardiovascular disease (CVD) risk prediction based on a comprehensive analysis of clinical, immunological and biochemical markers using mathematical modelling and machine learning methods. Baseline data include indices of humoral and cellular immunity (CD59, CD16, IL-10, CD14, CD19, CD8, CD4, etc.), cytokines and markers of cardiovascular disease, inflammatory markers (TNF, GM-CSF, CRP), growth and angiogenesis factors (VEGF, PGF), proteins involved in apoptosis and cytotoxicity (perforin, CD95), as well as indices of liver function, kidney function, oxidative stress and heart failure (albumin, cystatin C, N-terminal pro B-type natriuretic peptide (NT-proBNP), superoxide dismutase (SOD), C-reactive protein (CRP), cholinesterase (ChE), cholesterol, and glomerular filtration rate (GFR)). Clinical and behavioural risk factors were also considered: arterial hypertension (AH), previous myocardial infarction (PICS), aortocoronary bypass surgery (CABG) and/or stenting, coronary heart disease (CHD), atrial fibrillation (AF), atrioventricular block (AB block), and diabetes mellitus (DM), as well as lifestyle (smoking, alcohol consumption, physical activity level), education, and body mass index (BMI). Methods: The study included 52 patients aged 65 years and older. Based on the clinical, biochemical and immunological data obtained, a model for predicting the risk of premature cardiovascular aging was developed using mathematical modelling and machine learning methods. The aim of the study was to develop a predictive model allowing for the early detection of predisposition to the development of CVDs and their complications. Numerical methods of mathematical modelling, including Runge–Kutta, Adams–Bashforth and backward-directed Euler methods, were used to solve the prediction problem, which made it possible to describe the dynamics of changes in biomarkers and patients’ condition over time with high accuracy. Results: HLA-DR (50%), CD14 (41%) and CD16 (38%) showed the highest association with aging processes. BMI was correlated with placental growth factor (37%). The glomerular filtration rate was positively associated with physical activity (47%), whereas SOD activity was negatively correlated with it (48%), reflecting a decline in antioxidant defence. Conclusions: The obtained results allow for improving the accuracy of cardiovascular risk prediction, and form personalised recommendations for the prevention and correction of its development. Full article

Inflammatory biomarkers, including high-sensitivity C-reactive protein (hsCRP), serum amyloid A (SAA), and interleukin-6 (IL-6), have been associated with an increased risk of future cardiovascular events. While they provide valuable prognostic information, these associations do not necessarily imply a direct causal role. The combined prognostic utility of these markers, however, remains insufficiently studied. We analysed 3300 well-characterised participants of the Ludwigshafen Risk and Cardiovascular Health (LURIC) study, all of whom underwent coronary angiography. Participants were stratified based on their serum concentrations of hsCRP, SAA, and IL-6. Associations between biomarker combinations and mortality were assessed using multivariate Cox regression and ROC analysis. Individuals with elevated hsCRP and SAA or IL-6 showed higher prevalence rates of coronary artery disease, heart failure, and adverse metabolic traits. These “both high” groups had lower estimated glomerular filtration rate, higher NT-proBNP, and increased HbA1c. Combined elevations of hsCRP and SAA were significantly associated with higher all-cause and cardiovascular mortality in partially adjusted models. However, these associations weakened after adjusting for IL-6. IL-6 alone demonstrated the highest predictive power (AUC: 0.638) and improved risk discrimination when included in multi-marker models. The co-elevation of hsCRP, SAA, and IL-6 identifies a high-risk phenotype characterised by greater cardiometabolic burden and increased mortality. IL-6 may reflect upstream inflammatory activity and could serve as a therapeutic target. Multi-marker inflammatory profiling holds promise for refining cardiovascular risk prediction and advancing personalised prevention strategies. Full article