Biomarkers for the diagnosis and management of heart failure

Emerging methods and techniques for cancer biomarker discovery

Modern cancer research depends heavily on the identification and validation of biomarkers because they provide important information about the diagnosis, prognosis, and response to treatment of the cancer. This review will provide a comprehensive overview of cancer biomarkers, including their development phases and recent breakthroughs in transcriptomics and computational techniques for detecting these biomarkers. Blood-based biomarkers have great potential for non-invasive tumor dynamics and treatment response monitoring. These include circulating tumor DNA, exosomes, and microRNAs. Comprehensive molecular profiles are provided by multi-omic technologies, which combine proteomics, metabolomics, and genomes to support the identification of biomarkers and the targeting of therapeutic interventions. Genetic changes are detected by next-generation sequencing, and patterns of protein expression are found by protein arrays and mass spectrometry. Tumor heterogeneity and clonal evolution can be understood using metabolic profiling and single-cell studies. It is projected that the use of several biomarkers-genetic, protein, mRNA, microRNA, and DNA profiles, among others-will rise, enabling multi-biomarker analysis and improving individualised treatment plans. Biomarker identification and patient outcome prediction are further improved by developments in AI algorithms and imaging techniques. Robust biomarker validation and reproducibility require cooperation between industry, academia, and doctors. Biomarkers can provide individualized care, meet unmet clinical needs, and enhance patient outcomes despite some obstacles. Precision medicine will continue to take shape as scientific research advances and the integration of biomarkers with cutting-edge technologies continues to offer a more promising future for personalized cancer care.

Impaired HDL antioxidant and anti-inflammatory functions are linked to increased mortality in acute heart failure patients

AIMS

Acute heart failure (AHF) is typified by inflammatory and oxidative stress responses, which are associated with unfavorable patient outcomes. Given the anti-inflammatory and antioxidant properties of high-density lipoprotein (HDL), this study sought to examine the relationship between impaired HDL function and mortality in AHF patients. The complex interplay between various HDL-related biomarkers and clinical outcomes remains poorly understood.

METHODS

HDL subclass distribution was quantified by nuclear magnetic resonance spectroscopy. Lecithin-cholesterol acyltransferase (LCAT) activity, cholesterol ester transfer protein (CETP) activity, and paraoxonase (PON-1) activity were assessed using fluorometric assays. HDL-cholesterol efflux capacity (CEC) was assessed in a validated assay using [3H]-cholesterol-labeled J774 macrophages.

RESULTS

Among the study participants, 74 (23.5 %) out of 315 died within three months after hospitalization due to AHF. These patients exhibited lower activities of the anti-oxidant enzymes PON1 and LCAT, impaired CEC, and lower concentration of small HDL subclasses, which remained significant after accounting for potential confounding factors. Smaller HDL particles, particularly HDL3 and HDL4, exhibited a strong association with CEC, PON1 activity, and LCAT activity.

CONCLUSIONS

In patients with AHF, impaired HDL CEC, HDL antioxidant and anti-inflammatory function, and impaired HDL metabolism are associated with increased mortality. Assessment of HDL function and subclass distribution could provide valuable clinical information and help identify patients at high risk.

Effects and mechanisms of Salvia miltiorrhiza Bunge extract on myocardial cell apoptosis in rat heart failure model

PURPOSE

This work aimed to investigate the effects of Tanshinone IIA (Tan IIA) on myocardial cell (MC) apoptosis in a rat model of heart failure (HF).

METHODS

Tan IIA was extracted from Salvia miltiorrhiza Bunge (SMB) using an ethanol reflux method. Fifty rats were randomly divided into five groups: sham (no treatment), mod (HF model establishment), low dose (LD: 0.1 mL/kg Tan IIA), medium dose (MD: 0.3 mL/kg Tan IIA), and high dose (HD: 0.5 mL/kg Tan IIA), with 10 rats in each group. The effects of different doses of Tan IIA on cardiac function, MC apoptosis, and the levels of proteins associated with the PI3K/Akt/mTOR signaling pathway were compared.

RESULTS

Mod group showed a significant decrease in systolic arterial pressure, mean arterial pressure, heart rate, left ventricular systolic pressure, left ventricular ejection fraction, left ventricular fractional shortening, and the levels of p-PI3K, p-Akt, and p-mTOR proteins versus sham group (p < 0.05). Additionally, the left ventricular end-diastolic diameter (LVIDd), end-systolic diameter, diastolic pressure, and MC apoptosis were significantly increased (p < 0.05). LD, MD, and HD groups exhibited significant improvements across various indicators of cardiac function and MC apoptosis versus mod group (p < 0.05).

CONCLUSIONS

Tan IIA may improve cardiac function and inhibit MC apoptosis in rats with HF by modulating the PI3K/Akt/mTOR signaling pathway.

Natriuretic peptides and soluble ST2 improves echocardiographic diagnosis of elevated left ventricular filling pressures

Elevated filling pressure of the left ventricle (LV) defines diastolic dysfunction. The gold standard for diagnosis is represented by the measurement of LV end-diastolic pressure (LVEDP) during cardiac catheterization, but it has the disadvantage of being an invasive procedure. This study aimed to investigate the correlation between LVEDP and cardiac serum biomarkers such as natriuretic peptides (mid-regional pro-atrial natriuretic peptide [MR-proANP], B-type natriuretic peptide [BNP], and N-terminal prohormone BNP [NT-proBNP]), soluble ST2 (sST2), galectin-3 and mid-regional pro-adrenomedullin (MR-proAMD). Consecutive patients hospitalized in a tertiary center and undergoing left cardiac catheterization were included in the study. Diastolic dysfunction was considered present if the end-expiratory LVEDP was ≥ 15 mmHg. Cardiac biomarkers were determined from pre-procedural peripheral venous blood samples. A total of 110 patients were included, of whom 76 (69.0%) were males, with a median age of 65 (55-71) years. Median LVEDP was 13.5 (8-19) mmHg and diastolic dysfunction was present in 50 (45.4%) of the patients. LVEDP correlated with BNP (p < 0.0001, r = 0.39 [0.20-0.53]), NT-proBNP (p < 0.0001, r = 0.40 [0.22-0.55]), MR-proANP (p = 0.001, r = 0.30 [0.11-0.46]), sST2 (p < 0.0001, r = 0.47 [0.30-0.60]), but not with MR-proAMD (p = 0.77) or galectin-3 (p = 0.76). In the final stepwise multivariable binary logistic regression model, diastolic dysfunction was predicted by NT-proBNP, mitral average E/e', sST2, atrial fibrillation, and left atrium reservoir strain. BNP, NT-proBNP, MR-proANP, and sST2 had predictive value for diastolic dysfunction. In contrast, galectin-3 and MR-proAMD were not associated with increased filling pressures. Furthermore, NT-proBNP and sST2 significantly improved diastolic dysfunction prediction in the final multivariable model.

Association between cardiometabolic index and congestive heart failure among US adults: a cross-sectional study

Background

The risk of congestive heart failure (CHF) is significantly affected by obesity. However, data on the association between visceral obesity and the risk of CHF remain limited. We explored the relationship between CHF and cardiometabolic index (CMI).

Methods

Drawing from the National Health and Nutrition Examination Survey (NHANES) for 2011-2018, we enrolled 9,008 participants in a cross-sectional study. We calculated the CMI as triglyceride (TG)/high density lipid-cholesterol (HDL-C) × weight-to-height ratio (WHtR), and CMI-age as CMI × age. Then, we analyzed CMI and CMI-age as categorical and continuous variables to assess its correlation with CHF. To assess the relationships of CMI and CMI-age with CHF, we used multiple logistic regression models and performed subgroup analysis. To examine the predictive ability of CMI and CMI-age on patients with CHF, we used receiver operating characteristic (ROC) curves.

Results

The overall prevalence of CHF was 3.31%. The results revealed significant differences in demographic data, comorbidities, lifestyle variables, standing height, BMI, WC, WHtR, TG, and HDL-C among the four groups classified by CMI quartile and CMI-age quartile. When indicators were analyzed as continuous variables, CMI and CMI-age showed positive correlations with CHF in both the crude and adjusted models (all P < 0.05). When indicators were analyzed as categorical variables, it was found that in all four models, the ORs of group Q4 was significantly different compared to Q1 (all P < 0.05), suggesting the risk of CHF is significantly increased with higher CMI, and CMI-age. The associations of CMI and CMI-age with CHF were similar in all stratified populations (P for interaction > 0.05). The areas under the ROC curve (AUCs) of CMI and CMI-age in predicting CHF were 0.610 (95% CI, 0.578-0.642) and 0.697 (95% CI, 0.668-0.725) separately, suggesting that CMI-age was significantly better than the CMI in predicting CHF (P < 0.001).

Conclusions

Both CMI and CMI-age were independently correlated with the risk for CHF. These results suggested that the CMI-age, which provides new insights into the prevention and management of CHF. CMI-age could serve as effective tools to identify CHF during primary care examinations and in medically resource-limited areas.

The multidimensional value of natriuretic peptides in heart failure, integrating laboratory and clinical aspects

Natriuretic peptides (NP) play an essential role in heart failure (HF) regulation, and their measurement has improved diagnostic and prognostic accuracy. Clinical symptoms and objective measurements, such as NP levels, should be included in the HF definition to render it more reliable and consistent among observers, hospitals, and healthcare systems. BNP and NT-proBNP are reasonable surrogates for cardiac disease, and their measurement is critical to early diagnosis and risk stratification of HF patients. NPs should be measured in all patients presenting with dyspnea or other symptoms suggestive of HF to facilitate early diagnosis and risk stratification. Both BNP and NT-proBNP are currently used for guided HF management and display comparable diagnostic and prognostic accuracy. Standardized cutoffs for each NP assay are essential for data comparison. The value of NP testing is recognized at various levels, including patient empowerment and education, analytical and operational issues, clinical HF management, and cost-effectiveness.

S100B Serum Levels in Chronic Heart Failure Patients: A Multifaceted Biomarker Linking Cardiac and Cognitive Dysfunction

S100 calcium-binding protein B (S100B) is a protein primarily known as a biomarker for central nervous system (CNS) injuries, reflecting blood-brain barrier (BBB) permeability and dysfunction. Recently, S100B has also been implicated in cardiovascular diseases, including heart failure (HF). Thus, we investigated serum levels of S100B in 146 chronic HF patients from the Cognition.Matters-HF study and their association with cardiac and cognitive dysfunction. The median S100B level was 33 pg/mL (IQR: 22-47 pg/mL). Higher S100B levels were linked to longer HF duration (p = 0.014) and increased left atrial volume index (p = 0.041), but also with a higher prevalence of mild cognitive impairment (p = 0.023) and lower visual/verbal memory scores (p = 0.006). In a multivariable model, NT-proBNP levels independently predicted S100B (T-value = 2.27, p = 0.026). S100B did not impact mortality (univariable HR (95% CI) 1.00 (0.99-1.01); p = 0.517; multivariable HR (95% CI) 1.01 (1.00-1.03); p = 0.142), likely due to its reflection of acute injury rather than long-term outcomes and the mild HF phenotype in our cohort. These findings underscore S100B's value in comprehensive disease assessment, reflecting both cardiac dysfunction and potentially related BBB disruption.

Lipidomic analyses reveal potential biomarkers for predicting death and heart failure after acute myocardial infarction

Background Acute myocardial infarction (AMI) and postmyocardial infarction heart failure (pMIHF) have high mortality rates worldwide. This study aimed to explore lipidomic profiles and identify potential biomarkers for the prediction of death and heart failure (HF) after AMI. Methods All serum samples were collected at Xuanwu Hospital, Capital Medical University, and their clinical characteristics and lipidomic profiles were analyzed in different groups. LC-MS/MS was used for lipidomic analyses, and underlying biomarkers were screened by receiver operating characteristic (ROC) curve analysis. Results Lipidomic analyses of the survival and nonsurvival groups revealed that the decrease of the content of SM (d18:1/22:0), PE (P-20:1/18:0), PC (18:2), LPE (18:2), PE (P-20:0/18:0), LPC (18:0) and PC (20:0/20:3) while increase of the content of PG (18:1/18:1) could increase the risk of death after AMI. In parallel, the lipidomic analysis of the HF and non-HF groups revealed that the decrease of the content of PC (20:3/20:4), LPC (20:3), LPC (18:0), LPC (18:2), LPC (20:0), LPC (18:3), LPE (16:1) and PC (18:2/20:3) could increase the risk of HF after AMI. Conclusion Several lipids could be potential biomarkers for the prediction of death and HF after AMI.

Trajectory of Irisin as a Predictor of Kidney-Related Outcomes in Patients with Asymptomatic Heart Failure

The purpose of the study is to elucidate whether irisin is a promising predictive biomarker for kidney-related events in patients with T2DM and concomitant asymptomatic HF. We prospectively enrolled 146 T2DM patients who had either evidence of structural cardiac abnormality or elevated levels of N-terminal brain natriuretic pro-peptide (NT-proBNP) > 125 pmol/mL and followed them for 52 weeks. Structural cardiac abnormalities were used as the minimum from the following criteria: abnormal left ventricular (LV) global longitudinal strain (GLS) < -16%, LV hypertrophy, left atrial volume index > 34 mL/m2, abnormal ratio of early transmitral diastolic filling velocity/early mitral annular velocity ≥ 13 units. All the patients underwent echocardiographic and Doppler examinations by two blinded, highly experienced echocardiographers. NT-proBNP, irisin, TNF-alpha, and hs-CRP were quantified in the serum at baseline, at 26 weeks, and at the end of the study. The kidney-related outcomes consisted of an eGFR reduction by 40% from baseline, or end-stage kidney disease, or kidney replacement therapy. We found that levels of irisin at baseline < 4.15 ng/mL and/or its decrease > 20% from baseline in T2DM patients predicted kidney-related events better than baseline levels/dynamic NT-proBNP and the use of SGLT2 inhibitors. In conclusion, we established that a low baseline level of irisin and its 20% decrease correlated with newly kidney-related events in T2DM patients with asymptomatic HFpEF/HFmrEF.

The Role and Underlying Mechanisms of Exercise in Heart Failure

Heart failure is a prevalent and life-threatening syndrome characterized by structural and/or functional abnormalities of the heart. As a global burden with high rates of morbidity and mortality, there is growing recognition of the beneficial effects of exercise on physical fitness and cardiovascular health. A substantial body of evidence supports the notion that exercise can play a protective role in the development and progression of heart failure and improve cardiac function through various mechanisms, such as attenuating cardiac fibrosis, reducing inflammation, and regulating mitochondrial metabolism. Further investigation into the role and underlying mechanisms of exercise in heart failure may uncover novel therapeutic targets for the prevention and treatment of heart failure.

Proteomic Characterisation of Heart Failure Reveals a Unique Molecular Phenotype for Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a disease, which is difficult to diagnose at an early stage and for which there is a pressing need for more effective treatment options. The purpose of this study was to compare the molecular profile of HCM to that of ischaemic cardiomyopathy (ISCM) and dilated cardiomyopathy (DCM) for identification of protein and pathway targets that could support the development of better diagnostic and treatment options for HCM. A high-throughput mass spectrometry workflow was applied to achieve deep quantitative coverage of left ventricular tissue from HCM, DCM, ISCM and non-heart-failure control patients. HCM had a diverse proteomic profile compared to that of DCM and ISCM. Differentially expressed proteins unique to HCM were identified based on an observed fold change of ≥1.5 or ≤0.67 and q-value ≤ 0.05. Candidate proteins of interest were found to be significantly associated with clinical features of HCM. The significant association between these proteins and HCM was validated in an independent dataset. This represents one of the largest and deepest proteomic datasets for myocardial tissue reported to date. The dataset highlights the diverse proteomic profile of HCM, relative to other cardiomyopathies, and reveals disease-relevant pathways and promising biomarker candidates that are uniquely associated with HCM.

Early Detection of Heart Failure with Autonomous AI-Based Model Using Chest Radiographs: A Multicenter Study

The opportunistic use of radiological examinations for disease detection can potentially enable timely management. We assessed if an index created by an AI software to quantify chest radiography (CXR) findings associated with heart failure (HF) could distinguish between patients who would develop HF or not within a year of the examination. Our multicenter retrospective study included patients who underwent CXR without an HF diagnosis. We included 1117 patients (age 67.6 ± 13 years; m:f 487:630) that underwent CXR. A total of 413 patients had the CXR image taken within one year of their HF diagnosis. The rest (n = 704) were patients without an HF diagnosis after the examination date. All CXR images were processed with the model (qXR-HF, Qure.AI) to obtain information on cardiac silhouette, pleural effusion, and the index. We calculated the accuracy, sensitivity, specificity, and area under the curve (AUC) of the index to distinguish patients who developed HF within a year of the CXR and those who did not. We report an AUC of 0.798 (95%CI 0.77-0.82), accuracy of 0.73, sensitivity of 0.81, and specificity of 0.68 for the overall AI performance. AI AUCs by lead time to diagnosis (<3 months: 0.85; 4-6 months: 0.82; 7-9 months: 0.75; 10-12 months: 0.71), accuracy (0.68-0.72), and specificity (0.68) remained stable. Our results support the ongoing investigation efforts for opportunistic screening in radiology.

Risk Assessment and Personalized Treatment Options in Inherited Dilated Cardiomyopathies: A Narrative Review

Considering the worldwide impact of heart failure, it is crucial to develop approaches that can help us comprehend its root cause and make accurate predictions about its outcome. This is essential for lowering the suffering and death rates connected with this widespread illness. Cardiomyopathies frequently result from genetic factors, and the study of heart failure genetics is advancing quickly. Dilated cardiomyopathy (DCM) is the most prevalent kind of cardiomyopathy, encompassing both genetic and nongenetic abnormalities. It is distinguished by the enlargement of the left ventricle or both ventricles, accompanied by reduced contractility. The discovery of the molecular origins and subsequent awareness of the molecular mechanism is broadening our knowledge of DCM development. Additionally, it emphasizes the complicated nature of DCM and the necessity to formulate several different strategies to address the diverse underlying factors contributing to this disease. Genetic variants that can be transmitted from one generation to another can be a significant contributor to causing family or sporadic hereditary DCM. Genetic variants also play a significant role in determining susceptibility for acquired triggers for DCM. The genetic causes of DCM can have a large range of phenotypic expressions. It is crucial to select patients who are most probable to gain advantages from genetic testing. The purpose of this research is to emphasize the significance of identifying genetic DCM, the relationships between genotype and phenotype, risk assessment, and personalized therapy for both those affected and their relatives. This approach is expected to gain importance once treatment is guided by genotype-specific advice and disease-modifying medications.

Higher systemic inflammation response index is associated with increased risk of heart failure in adults: An observational study

Inflammation has been established to play a crucial role in the onset of heart failure (HF) for many years, and the systemic inflammation response index (SIRI) is a new and comprehensive indicator reflecting the inflammation status in human body. The aim of this investigation was to determine the potential relationship between HF and SIRI in adults. For this investigation, we used cross-sectional data from the National Health and Nutrition Examination Survey (NHANES), which was conducted from 2009 to 2018. The study utilized multivariable linear regression models to examine the potential independent relationship between HF and SIRI. Additionally, a subgroup analysis and interaction test were carried out. To illustrate the nonlinear relationship, threshold effect analysis and fitted smoothing curves were also used. 26,303 eligible subjects aged ≥ 20 years were enrolled as the final samples. HF participants exhibited significant higher SIRI compared with non-HF participants [1.89 ± 1.33 vs 1.25 ± 0.95 (1000 cells/μL), P < .0001]. Multivariate logistic regression showed that those in the highest SIRI quartile had a significantly greater risk of HF by 130% (OR = 2.30, 95% CI 1.41-3.76; P < .0001). In addition, nonlinear relationship between HF and SIRI with the inflection point of 2.2 (1000 cells/μL) was observed. According to our research, adult HF prevalence and SIRI are positively correlated. This implies that SIRI could be a valuable biomarker for determining HF risk in the clinic.

Advances in heart failure monitoring: Biosensors targeting molecular markers in peripheral bio-fluids

Cardiovascular diseases (CVDs), especially chronic heart failure, threaten many patients' lives worldwide. Because of its slow course and complex causes, its clinical screening, diagnosis, and prognosis are essential challenges. Clinical biomarkers and biosensor technologies can rapidly screen and diagnose. Multiple types of biomarkers are employed for screening purposes, precise diagnosis, and treatment follow-up. This article provides an up-to-date overview of the biomarkers associated with the six main heart failure etiology pathways. Plasma natriuretic peptides (BNP and NT-proBNP) and cardiac troponins (cTnT, cTnl) are still analyzed as gold-standard markers for heart failure. Other complementary biomarkers include growth differentiation factor 15 (GDF-15), circulating Galactose Lectin 3 (Gal-3), soluble interleukin (sST2), C-reactive protein (CRP), and tumor necrosis factor-alpha (TNF-α). For these biomarkers, the electrochemical biosensors have exhibited sufficient sensitivity, detection limit, and specificity. This review systematically summarizes the latest molecular biomarkers and sensors for heart failure, which will provide comprehensive and cutting-edge authoritative scientific information for biomedical and electronic-sensing researchers in the field of heart failure, as well as patients. In addition, our proposed future outlook may provide new research ideas for researchers.

Proteomics of the heart

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

Clinical Use of Biomarkers in Cardiac Amyloidosis

Amyloidosis is a systemic condition characterized by multiple organs involvement. A multidisciplinary and multimodal approach in assessing patients is pivotal and recommended by the international scientific societies. Biomarkers represent an essential noninvasive tool to increase the suspicion of disease and orient further workup and clinical management of patients. This review provides an updated contemporary focus on the clinical use of biomarkers in cardiac amyloidosis, emphasizing their role in both the diagnostic and prognostic setting and discussing future perspective of emerging biomarkers.

Integrated biomarker profiling for enhanced heart failure management: a comprehensive study on the application of chemiluminescence detection of GDF-15 and multi-index models

BACKGROUND

Growth differentiation factor 15 (GDF-15) holds promise as a novel marker for heart failure. However, current detection methods fall short of meeting essential clinical requirements.

OBJECTIVES

The aim of this investigation was to assess the clinical significance of serum GDF-15 detection through the chemiluminescence method and to enhance its clinical application for predicting and evaluating heart failure in patients.

METHODS

A total of 122 patients were included in the study. Serum GDF-15 levels were assessed using the chemiluminescence method and compared with results for NT-proBNP, N-terminal pro-brain natriuretic peptide (NT-proBNP), growth stimulation expressed gene 2 (ST2), high-sensitivity C-reactive protein (hs-CRP), and left ventricular ejection fraction (LVEF). Additionally, we conducted an analysis to evaluate the correlation between these indicators and heart failure events.

RESULTS

LVEF, ST2, NT-proBNP, and GDF-15 exhibited significant associations with heart failure. In the multivariate proportional hazard analysis, subsequent to adjusting for the effects of other markers, however, only LVEF and GDF-15 retained their associations with heart failure events. Notably, GDF-15 emerged as the exclusive marker suitable for diagnosing heart failure with preserved ejection fraction.

CONCLUSION

The chemiluminescence method proved efficient in the rapid and sensitive detection of GDF-15 in patients with heart failure. Additionally, GDF-15 combined with other markers created a robust multi-index model. This model is valuable for heart failure diagnosis, treatment, and monitoring, with broad clinical applicability.

The Role of High-Sensitivity Troponin T Regarding Prognosis and Cardiovascular Outcome across Heart Failure Spectrum

Background: Cardiac troponin release is related to the cardiomyocyte loss occurring in heart failure (HF). The prognostic role of high-sensitivity cardiac troponin T (hs-cTnT) in several settings of HF is under investigation. The aim of the study is to assess the prognostic role of intrahospital hs-cTnT in patients admitted due to HF. Methods: In this observational, single center, prospective study, patients hospitalized due to HF have been enrolled. Admission, in-hospital peak, and discharge hs-cTnT have been assessed. Patients were followed up for 6 months. Cardiovascular (CV) death, HF hospitalization (HFH), and worsening HF (WHF) (i.e., urgent ambulatory visit/loop diuretics escalation) events have been assessed at 6-month follow up. Results: 253 consecutive patients have been enrolled in the study. The hs-cTnT median values at admission and discharge were 0.031 ng/mL (IQR 0.02-0.078) and 0.031 ng/mL (IQR 0.02-0.077), respectively. The risk of CV death/HFH was higher in patients with admission hs-cTnT values above the median (p = 0.02) and in patients who had an increase in hs-cTnT during hospitalization (p = 0.03). Multivariate Cox regression analysis confirmed that hs-cTnT above the median (OR: 2.06; 95% CI: 1.02-4.1; p = 0.04) and increase in hs-cTnT during hospitalization (OR:1.95; 95%CI: 1.006-3.769; p = 0.04) were predictors of CV death/HFH. In a subgroup analysis of patients with chronic HF, hs-cTnT above the median was associated with increased risk of CV death/HFH (p = 0.03), while in the subgroup of patients with HFmrEF/HFpEF, hs-cTnT above the median was associated with outpatient WHF events (p = 0.03). Conclusions: Inpatient hs-cTnT levels predict CV death/HFH in patients with HF. In particular, in the subgroup of chronic HF patients, hs-cTnT is predictive of CV death/HFH; while in patients with HFmrEF/HFpEF, hs-cTnT predicts WHF events.

Butyrate attenuates sympathetic activation in rats with chronic heart failure by inhibiting microglial inflammation in the paraventricular nucleus

Sympathetic activation is a hallmark of heart failure and the underlying mechanism remains elusive. Butyrate is generated by gut microbiota and influences numerous physiological and pathological processes in the host. The present study aims to investigate whether the intestinal metabolite butyrate reduces sympathetic activation in rats with heart failure (HF) and the underlying mechanisms involved. Sprague-Dawley rats (220‒250 g) are anaesthetized with isoflurane, and the left anterior descending artery is ligated to model HF. Then, the rats are treated with or without butyrate sodium (NaB, a donor of butyrate, 10 g/L in water) for 8 weeks. Blood pressure and renal sympathetic nerve activity (RSNA) are recorded to assess sympathetic outflow. Cardiac function is improved (mean ejection fraction, 22.6%±4.8% vs 38.3%±5.3%; P<0.05), and sympathetic activation is decreased (RSNA, 36.3%±7.9% vs 23.9%±7.6%; P<0.05) in HF rats treated with NaB compared with untreated HF rats. The plasma and cerebrospinal fluid levels of norepinephrine are decreased in HF rats treated with NaB. The infusion of N-methyl-D-aspartic acid (NMDA) into the paraventricular nucleus (PVN) of the hypothalamus of HF model rats increases sympathetic nervous activity by upregulating the NMDA receptor. Microglia polarized to the M2 phenotype and inflammation are markedly attenuated in the PVN of HF model rats after NaB administration. In addition, HF model rats treated with NaB exhibit enhanced intestinal barrier function and increased levels of GPR109A, zona occludens-1 and occludin, but decreased levels of lipopolysaccharide-binding protein and zonulin. In conclusion, butyrate attenuates sympathetic activation and improves cardiac function in rats with HF. The improvements in intestinal barrier function, reductions in microglia-mediated inflammation and decreases in NMDA receptor 1 expression in the PVN are all due to the protective effects of NaB.

Newborn Screening for High-Risk Congenital Heart Disease by Dried Blood Spot Biomarker Analysis

Importance

Congenital heart disease (CHD) is the most common human organ malformation, affecting approximately 1 of 125 newborns globally.

Objectives

Assessing the performance of 2 diagnostic tests using minimal amounts of dried blood spots (DBS) to identify high-risk CHD compared with controls in a Swedish cohort of neonates.

Design, Setting, and Participants

This diagnostic study took place in Sweden between 2019 and 2023 and enrolled full-term babies born between 2005 and 2023. All cases were identified through centralized pediatric cardiothoracic surgical services in Lund and Gothenburg, Sweden. Controls were followed up for 1 year to ensure no late presentations of high-risk CHD occurred. Cases were verified through surgical records and echocardiography.

Exposure

High-risk CHD, defined as cases requiring cardiac surgical management during infancy due to evolving signs of heart failure or types in which the postnatal circulation depends on patency of the arterial duct. Using 3-μL DBS samples, automated quantitative tests for NT-proBNP and interleukin 1 receptor-like 1 (IL-1 RL1; formerly known as soluble ST2) were compared against established CHD screening methods.

Main Outcomes and Measures

Performance of DBS tests to detect high-risk CHD using receiver operating characteristic curves; Bland-Altman and Pearson correlation analyses to compare IL-1 RL1 DBS with plasma blood levels.

Results

A total of 313 newborns were included (mean [SD] gestational age, 39.4 [1.3] weeks; 181 [57.8%] male). Mean (SD) birthweight was 3495 (483) grams. Analyzed DBS samples included 217 CHD cases and 96 controls. Among the CHD cases, 188 participants (89.3%) were high-risk types, of which 73 (38.8%) were suspected prenatally. Of the 188 high-risk cases, 94 (50.0%) passed pulse oximetry screening and 36 (19.1%) were initially discharged after birth without diagnoses. Combining NT-proBNP and IL-1 RL1 tests performed well in comparison with existing screening methods and enabled additional identification of asymptomatic babies with receiver operating characteristic area under the curve 0.95 (95% CI, 0.93-0.98).

Conclusions and relevance

In this diagnostic study, NT-proBNP and IL-1 RL1 DBS assays identified high-risk CHD in a timely manner, including in asymptomatic newborns, and improved overall screening performance in this cohort from Sweden. Prospective evaluation of this novel approach is warranted.

Evaluating Biomarkers as Tools for Early Detection and Prognosis of Heart Failure: A Comprehensive Review

There is a high prevalence of heart failure (HF) worldwide, which has significant consequences for healthcare costs, patient death and quality of life. Therefore, there has been much focus on finding and using biomarkers for early diagnosis, prognostication and therapy of HF. This overview of the research presents a thorough examination of the current state of HF biomarkers and their many uses. Their function in diagnosing HF, gauging its severity and monitoring its response to therapy are all discussed. Particularly promising in HF diagnosis and risk stratification are the cardiac-specific biomarkers, B-type natriuretic peptide and N-terminal pro-B-type natriuretic peptide. Markers of oxidative stress, extracellular matrix, renal function, inflammation and cardiac peptides have shown promise in evaluating HF severity and prognosis. MicroRNAs and insulin-like growth factor are two emerging biomarkers that have shown potential in helping with HF diagnosis and prognosis.

Real-World Outcomes of a Rhythm Control Strategy for Atrial Fibrillation Patients with Reduced Left Ventricular Ejection Fraction (<50%)

Background/Objectives: The effectiveness of a rhythm control strategy in patients with atrial fibrillation (AF) and reduced left ventricular ejection fraction (LVEF < 50%) in real-world practice remains uncertain. Our objective was to evaluate the real-world outcomes of a rhythm control strategy in patients with AF and reduced LVEF, focusing on changes in LV systolic function and brain natriuretic peptide (BNP) levels. Methods: The study retrospectively reviewed the medical records of 80 patients with concurrent AF and reduced LVEF who underwent rhythm control therapy between March 2015 and December 2021. Results: The patients had an average age of 63.6 years and an initial LVEF of 34.3%. Sinus rhythm was restored using anti-arrhythmic drugs (38, 47.5%) or electrical cardioversion (42, 52.5%). Over a follow-up period of 53.0 months, AF recurred in 65% of patients, with 57.7% undergoing catheter ablation. Significant improvements were noted in LVEF (from 34.3% to 55.1%, p < 0.001) and BNP levels (from 752 pg/mL to 72 pg/mL, p < 0.001) at the last follow-up. Nearly all patients (97.5%) continued with the rhythm control strategy during the follow-up period. Conclusions: In real-world settings, a rhythm control strategy proves to be feasible and effective for improving LVEF and reducing BNP levels in AF patients with reduced LVEF.

m6A reader YTHDF1 promotes cardiac fibrosis by enhancing AXL translation

Cardiac fibrosis caused by ventricular remodeling and dysfunction such as post-myocardial infarction (MI) can lead to heart failure. RNA N6-methyladenosine (m6A) methylation has been shown to play a pivotal role in the occurrence and development of many illnesses. In investigating the biological function of the m6A reader YTHDF1 in cardiac fibrosis, adeno-associated virus 9 was used to knock down or overexpress the YTHDF1 gene in mouse hearts, and MI surgery in vivo and transforming growth factor-β (TGF-β)-activated cardiac fibroblasts in vitro were performed to establish fibrosis models. Our results demonstrated that silencing YTHDF1 in mouse hearts can significantly restore impaired cardiac function and attenuate myocardial fibrosis, whereas YTHDF1 overexpression could further enhance cardiac dysfunction and aggravate the occurrence of ventricular pathological remodeling and fibrotic development. Mechanistically, zinc finger BED-type containing 6 mediated the transcriptional function of the YTHDF1 gene promoter. YTHDF1 augmented AXL translation and activated the TGF-β-Smad2/3 signaling pathway, thereby aggravating the occurrence and development of cardiac dysfunction and myocardial fibrosis. Consistently, our data indicated that YTHDF1 was involved in activation, proliferation, and migration to participate in cardiac fibrosis in vitro. Our results revealed that YTHDF1 could serve as a potential therapeutic target for myocardial fibrosis.

Heart Failure With Improved Ejection Fraction: Prevalence, Predictors, and Guideline-Directed Medical Therapy

Recently, a new category of heart failure with improved ejection fraction (HFimpEF) has emerged in the classification system. This is defined as the subgroup of patients with heart failure with reduced ejection fraction (HFrEF) whose left ventricular ejection fraction has recovered partially or completely, with no specific cut-off values established yet in the guidelines. In our review, we aim to provide an overview of prevalence, predictors, mechanism of remodeling, and management strategies regarding HFimpEF. These patients constitute a sizeable cohort among patients with reduced ejection fraction. Certain patient characteristics including younger age and female gender, absence of comorbid conditions, low levels of biomarkers, and non-ischemic etiology were identified as positive predictors. The heart undergoes significant maladaptive changes post failure leading to adverse remodeling influenced etiology and duration. Goal-directed medical therapy including beta-blockers, angiotensin-converting enzyme inhibitors (ACEIs), and angiotensin II receptor blockers (ARBs) have notably improved cardiac function by inducing reverse remodeling. Despite a more favorable prognosis compared to HFrEF, patients with improved ejection fraction (EF) still face clinical events and reduced quality of life, and remain at risk of adverse outcomes. Although the evidence is scarce, it is advisable to continue treatment modalities despite improvement in EF, including device therapies, to prevent relapse and clinical deterioration. It is imperative to conduct further research to understand the mechanism leading to EF amelioration and establish guidelines to identify and direct management strategies.

Mapping the interplay of immunoproteasome and autophagy in different heart failure phenotypes

Proper protein degradation is required for cellular protein homeostasis and organ function. Particularly, in post-mitotic cells, such as cardiomyocytes, unbalanced proteolysis due to inflammatory stimuli and oxidative stress contributes to organ dysfunction. To ensure appropriate protein turnover, eukaryotic cells exert two main degradation systems, the ubiquitin-proteasome-system and the autophagy-lysosome-pathway. It has been shown that proteasome activity affects the development of cardiac dysfunction differently, depending on the type of heart failure. Studies analyzing the inducible subtype of the proteasome, the immunoproteasome (i20S), demonstrated that the i20S plays a double role in diseased hearts. While i20S subunits are increased in cardiac hypertrophy, atrial fibrillation and partly in myocarditis, the opposite applies to diabetic cardiomyopathy and ischemia/reperfusion injury. In addition, the i20S appears to play a role in autophagy modulation depending on heart failure phenotype. This review summarizes the current literature on the i20S in different heart failure phenotypes, emphasizing the two faces of i20S in injured hearts. A selection of established i20S inhibitors is introduced and signaling pathways linking the i20S to autophagy are highlighted. Mapping the interplay of the i20S and autophagy in different types of heart failure offers potential approaches for developing treatment strategies against heart failure.

Early-pregnancy N-terminal pro-brain natriuretic peptide level is inversely associated with hypertensive disorders of pregnancy diagnosed after 35 weeks of gestation

Hypertensive disorders of pregnancy (HDP) are among the major causes of high maternal and fetal/neonatal morbidity and mortality rates. Patients with HDP have significantly elevated N-terminal pro-brain natriuretic peptide (NT-proBNP) levels at diagnosis; however, the NT-proBNP levels during early pregnancy are largely unknown. This study aimed to validate the association between HDP and NT-proBNP levels. This retrospective study evaluated 103 pregnant women who developed HDP diagnosed after 35 weeks of gestation and 667 who did not. The HDP group had significantly lower early-pregnancy NT-proBNP levels than the without HDP group. However, the two groups did not significantly differ in terms of the late-pregnancy NT-proBNP levels. After adjusting for confounding factors such as age, body mass index, parity, and blood pressure levels, high early-pregnancy NT-proBNP levels were associated with a lower HDP risk. Early-pregnancy NT-proBNP levels ≥ 60.5 pg/mL had a negative predictive value of 97.0% for ruling out HDP, with a sensitivity of 87.4% and specificity of 62.5%. In conclusion, elevated early-pregnancy NT-proBNP levels were associated with a lower HDP risk. Moreover, a cutoff point of ≥ 60.5 pg/mL for early-pregnancy NT-proBNP levels had a high negative predictive value and sensitivity for ruling out HDP. These findings can provide new clinical implications.

The Role of Oxidative Stress and Inflammatory Parameters in Heart Failure

Heart failure (HF) remains a major medical and social problem. The NT-pro-brain natriuretic peptide (NT-proBNP) and its active form, brain-type natriuretic peptide (BNP), in a simple blood test are the gold-standard biomarkers for HF diagnosis. However, even good biomarkers such as natriuretic peptides fail to predict all the risks associated with HF due to the diversity of the mechanisms involved. The pathophysiology of HF is determined by numerous factors, including oxidative stress, inflammation, neuroendocrine activation, pathological angiogenesis, changes in apoptotic pathways, fibrosis and vascular remodeling. High readmission and mortality rates prompt a search for new markers for the diagnosis, prognosis and treatment of HF. Oxidative-stress-mediated inflammation plays a crucial role in the development of subsequent changes in the failing heart and provides a new insight into this complex mechanism. Oxidative stress and inflammatory biomarkers appear to be a promising diagnostic and prognostic tool in patients with HF. This systematic review provides an overview of the current knowledge about oxidative stress and inflammation parameters as markers of HF.

The use of peptides for immunodiagnosis of human Chagas disease

Chagas disease, caused by the protozoa Trypanosoma cruzi, continues to be a serious public health problem in Latin America, worsened by the limitations in its detection. Given the importance of developing new diagnostic methods for this disease, the present review aimed to verify the number of publications dedicated to research on peptides that demonstrate their usefulness in serodiagnosis. To this end, a bibliographic survey was conducted on the PubMed platform using the keyword "peptide" or "epitope" combined with "Chagas disease" or "Trypanosoma cruzi"; "diagno*" or "serodiagnosis" or "immunodiagnosis", without period restriction. An increasing number of publications on studies employing peptides in ELISA and rapid tests assays was verified, which confirms the expansion of research in this field. It is possible to observe that many of the peptides tested so far originate from proteins widely used in the diagnosis of Chagas, and many of them are part of commercial tests developed. In this sense, as expected, promising results were obtained for several peptides when tested in ELISA, as many of them exhibited sensitivity and specificity values above 90%. Furthermore, some peptides have been tested in several studies, confirming their diagnostic potential. Despite the promising results observed, it is possible to emphasize the need for extensive testing of peptides, using different serological panels, in order to confirm their potential. The importance of producing an effective assay capable of detecting the clinical stages of the disease, as well as new immunogenic antigens that enable new serological diagnostic tools for Chagas disease, is evident.

Emerging Biomarkers in the Laboratory and in Practice: A Novel Approach to Diagnosing Heart Failure in Diabetes

The Biomarkers for the Diagnosis of Heart Failure in Diabetes webinar was hosted by Diabetes Technology Society on September 20, 2023, with the objective to review current evidence and management practices of biomarker screening for heart failure in people with diabetes. The webinar discussed (1) the four stages of heart failure, (2) diabetes and heart failure, (3) natriuretic peptide and troponin for diagnosing heart failure in diabetes, (4) emerging composite and investigational biomarkers for diagnosing heart failure, and (5) prevention of heart failure progression. Experts in heart failure from the fields of clinical chemistry, cardiology, and diabetology presented data about the importance of screening for heart failure as an often-unnoticed complication of people with type 1 and type 2 diabetes.

Plasma SMOC2 Predicts Prognosis in Patients with Heart Failure: A Prospective Cohort

Background

Heart failure (HF) is a chronic disease with a poor prognosis, making it extremely important to assess the prognosis of patients with HF for accurate treatment. Secreted modular calcium-binding protein 2 (SMOC2) is a cysteine-rich acidic secreted protein that plays a pathophysiological role in many diseases, including regulation of vascular growth factor activity. It has previously been found that SMOC2 plays an essential role in cardiac fibrosis in our previous preclinical study, but whether it can be used as a clinical marker in heart failure patients remains unclear. The purpose of this research was to evaluate the correlation between plasma levels of SMOC2 and the prognosis for individuals with HF.

Methods

HF patients diagnosed with ischemic cardiomyopathy were enrolled from January to December 2021. Baseline plasma levels of SMOC2 were measured after demographic and clinical features were collected. Linear and nonlinear multivariate Cox regression models were used to determine the association between plasma SMOC2 and patient outcomes during follow-up. All analysis was performed using SPSS, EmpowerStats, and R software.

Results

The study included 188 patients, and the average follow-up time was 489.5±88.3 days. The plasma SMOC2 concentrations were positively correlated with N-terminal pro-B-type Natriuretic Peptide (NT-proBNP), left ventricular end-diastolic diameter (LVEDd), and length of hospital stay and were negatively correlated with left ventricular ejection fraction (LVEF) at baseline. A total of 53 patients (28.2%) were rehospitalized due to cardiac deterioration, 14 (7.4%) died, and 37 (19.7%) developed malignant arrhythmias. A fully adjusted multivariate COX regression model showed that SMOC2 is associated with readmission (HR = 1.02, 95% CI:1.012-1.655). A significant increase in rehospitalization risk was observed in group Q2 (HR =1.064, 95% CI: 1.037, 3.662, p=0.005) and group Q3 (HR =1.085, 95% CI:1.086, 3.792, p=0.009) in comparison with group Q1. The p for trend also shows a linear correlation across the three models (P < 0.001). SMOC2 was associated with the severity of HF in patients, but not with all-cause deaths and arrhythmias during follow-up.

Conclusion

Plasma SMOC2 is associated with the severity of HF and readmission rate, and is a good predictor of the risk of readmission in patients.

The Congestion "Pandemic" in Acute Heart Failure Patients

Congestion not only represents a cardinal sign of heart failure (HF) but is also now recognized as the primary cause of hospital admissions, rehospitalization, and mortality among patients with acute heart failure (AHF). Congestion can manifest through various HF phenotypes in acute settings: volume overload, volume redistribution, or both. Recognizing the congestion phenotype is paramount, as it implies different therapeutic strategies for decongestion. Among patients with AHF, achieving complete decongestion is challenging, as more than half still experience residual congestion at discharge. Residual congestion is one of the strongest predictors of future cardiovascular events and poor outcomes. Through this review, we try to provide a better understanding of the congestion phenomenon among patients with AHF by highlighting insights into the pathophysiological mechanisms behind congestion and new diagnostic and management tools to achieve and maintain efficient decongestion.

Oxidative Stress and Antioxidant Status in Adult Patients with Transfusion-Dependent Thalassemia: Correlation with Demographic, Laboratory, and Clinical Biomarkers

Iron overload in beta transfusion-dependent thalassemia (β-TDT) may provoke oxidative stress and reduction of the antioxidant defenses, with serious consequences for the disease course and complications. The present study evaluated the oxidant/antioxidant status of β-TDT patients and its correlation with demographic, clinical, laboratory, and instrumental biomarkers. The OXY-adsorbent assay and the d-ROMs (Diacron, Grosseto, Italy) were evaluated in 58 β-TDT patients (mean age: 37.55 ± 7.83 years, 28 females) enrolled in the Extension-Myocardial Iron Overload in Thalassemia Network. Iron overload was quantified with R2* magnetic resonance imaging. Mean OXY was 323.75 ± 113.19 μmol HClO/mL and 39 (67.2%) patients showed a decreased OXY-Adsorbent level (<350 μmol HClO/mL), of whom 22 (37.9%) showed severely reduced levels. Mean d-ROMs was 305.12 ± 62.19 UA; 12 (20.7%) patients showed oxidative stress, and 4 (6.9%) elevated oxidative stress. OXY showed a significant negative correlation with global and segmental cardiac iron levels. D-ROMs levels significantly correlated with markers of cardiovascular risk (aging, glycemia, and N-terminal pro-B-type natriuretic peptide). Antioxidant depletion is frequent in β-TDT patients, where OXY might serve as additive biomarker to assess heart iron status, whereas the d-ROMs might be helpful to assess the cardiovascular risk burden.

Immune patterns of cuproptosis in ischemic heart failure: A transcriptome analysis

Cuproptosis is a recently discovered programmed cell death pattern that affects the tricarboxylic acid (TCA) cycle by disrupting the lipoylation of pyruvate dehydrogenase (PDH) complex components. However, the role of cuproptosis in the progression of ischemic heart failure (IHF) has not been investigated. In this study, we investigated the expression of 10 cuproptosis-related genes in samples from both healthy individuals and those with IHF. Utilizing these differential gene expressions, we developed a risk prediction model that effectively distinguished healthy and IHF samples. Furthermore, we conducted a comprehensive evaluation of the association between cuproptosis and the immune microenvironment in IHF, encompassing infiltrated immunocytes, immune reaction gene-sets and human leukocyte antigen (HLA) genes. Moreover, we identified two different cuproptosis-mediated expression patterns in IHF and explored the immune characteristics associated with each pattern. In conclusion, this study elucidates the significant influence of cuproptosis on the immune microenvironment in ischemic heart failure (IHF), providing valuable insights for future mechanistic research exploring the association between cuproptosis and IHF.

Pharmacodynamics and Mechanism of Astragali Radix and Anemarrhenae Rhizoma in Treating Chronic Heart Failure by Inhibiting Complement Activation

Astragali radix (AR) and anemarrhenae rhizoma (AAR) are used clinically in Chinese medicine for the treatment of chronic heart failure (CHF), but the exact therapeutic mechanism is unclear. In this study, a total of 60 male C57BL/6 mice were divided into 5 groups, namely sham, model, AR, AAR, and AR-AAR. In the sham group, the chest was opened without ligation. In the other groups, the chest was opened and the transverse aorta was ligated to construct the transverse aortic constriction model. After 8 weeks of feeding, mice were given medicines by gavage for 4 weeks. Left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS) were detected by echocardiography. Heart weight index (HWI) and wheat germ agglutinin staining were used to evaluate cardiac hypertrophy. Hematoxylin-eosin staining was used to observe the pathological morphology of myocardial tissue. Masson staining was used to evaluate myocardial fibrosis. The content of serum brain natriuretic peptide (BNP) was detected by enzyme-linked immunosorbent assay kit. The content of serum immunoglobulin G (IgG) was detected by immunoturbidimetry. The mechanism of AR-AAR in the treatment of CHF was explored by proteomics. Western blot was used to detect the protein expressions of complement component 1s (C1s), complement component 9 (C9), and terminal complement complex 5b-9 (C5b-9). The results show that AR-AAR inhibits the expression of complement proteins C1s, C9, and C5b-9 by inhibiting the production of IgG antibodies from B cell activation, which further inhibits the complement activation, attenuates myocardial fibrosis, reduces HWI and cardiomyocyte cross-sectional area, improves cardiomyocyte injury, reduces serum BNP release, elevates LVEF and LVFS, improves cardiac function, and exerts myocardial protection.

Quantitative assessment of left ventricular myocardial work in patients with different types of atrial fibrillation by non-invasive pressure-strain loop technique

OBJECTIVE

This study aimed to analyze myocardial work in patients with atrial fibrillation (AF) using a noninvasive pressure strain loop (PSL) technique to provide a basis for the quantitative assessment of left ventricular (LV) systolic function.

METHODS

LV myocardial work of 107 AF patients (56 with paroxysmal atrial fibrillation and 51 with persistent atrial fibrillation) and 55 healthy individuals were assessed by the noninvasive PSL and then compared.

RESULTS

Global longitudinal strain (GLS) in absolute values, global work index (GWI), global constructive work (GCW), and global work efficiency (GWE) were significantly lower in the AF group than control group, whereas peak strain dispersion (PSD) and global wasted work (GWW) were significantly higher (P < .05). Further subdivision according to the AF type revealed that, compared with the controls, GLS in absolute values and GWE decreased significantly; PSD and GWW increased significantly in the paroxysmal AF group (P < .05). Nevertheless, GWI and GCW were not significantly different between paroxysmal AF and control groups (P > .05). Compared to paroxysmal AF, persistent AF induced a further decrease in absolute GLS and GWE and a further increase in GWW (P < .05), but PSD did not increase further (P > .05). Multiple linear regression analysis showed that GWI and GCW were independently associated with systolic blood pressure. GWW was associated with types of AF and left atrial volume index (LAVI). GWE was correlated with age, types of AF, disease duration, and LAVI. Receiver operating characteristic curve analysis showed that the area under the curve predicting myocardial injury was higher for GWE and GWW than for GLS (area under the curve:  .880,  .846, and  .821, respectively).

CONCLUSIONS

Non-invasive PSL can quantitatively assess LV systolic function in patients with different kinds of AF and detect early subclinical myocardial injury in patients with paroxysmal AF. GWE and GWW outperform GLS and LV ejection fraction when assessing myocardial injury. Systolic blood pressure, type of AF, LVAI, disease duration, and age may be associated with myocardial injury in patients with AF.

Soluble ST2 as a possible biomarker for inflammation in patients with acute heart failure

AIM

The aim of this study was to explore the relationship between peripheral circulating serum soluble suppression of tumorigenicity-2 (sST2) levels and inflammatory biomarkers in patients with acute heart failure (AHF).

METHODS

One hundred and eleven consecutive AHF patients with NYHA class II-IV were enrolled, and peripheral blood was collected within 24 h of admission for the detection of NT-ProBNP, sST2, hypersensitive troponin I, cytokines, precalcitoninogen, C-reactive protein, in addition to routine standard of care blood tests.

RESULTS

The median sST2 of 111 patients was 47.50 ng/ml (24.25-86.15 IQR), of whom 43 patients (38.7%) had sST2 35 ng/ml or less; linear correlation analysis showed that serum sST2 correlated with NT-ProBNP ( r2  = 0.32), NEU% ( r2  = 0.41), NLR ( r2  = 0.36), CRP ( r2  = 0.50), IL-18 ( r2  = 0.43) ( P  < 0.001), and correlated with Hs-cTnI ( r2  = 0.19), NUE ( r2  = 0.25), LYM ( r2  = -0.23), IL-2RA ( r2  = 0.29) ( P  < 0.05). Multiple linear regression analysis depicted that CRP (β = 0.318), IL-18 (β = 0.368), NEU% (β = 0.346), NLR (β = -0.304), and NT-ProBNP (β = 0.324) significantly correlated with sST2 values, respectively ( P  < 0.05). ST2 levels have a linear association with length of hospitalization.

CONCLUSION

Peripheral blood inflammatory markers (CRP, IL-18, NEU%, NLR) in patients with AHF had a close relationship with sST2 levels, and the mechanism of action of sST2 may be related to the inflammatory response.

Pathophysiological insights into machine learning-based subphenotypes of acute heart failure with preserved ejection fraction

OBJECTIVE

The heterogeneous pathophysiology of the diverse heart failure with preserved ejection fraction (HFpEF) phenotypes needs to be examined. We aim to assess differences in the biomarkers among the phenotypes of HFpEF and investigate its multifactorial pathophysiology.

METHODS

This study is a retrospective analysis of the PURSUIT-HFpEF Study (N=1231), an ongoing, prospective, multicentre observational study of acute decompensated HFpEF. In this registry, there is a predefined subcohort in which we perform multibiomarker tests (N=212). We applied the previously established machine learning-based clustering model to the subcohort with biomarker measurements to classify them into four phenotypes: phenotype 1 (n=69), phenotype 2 (n=49), phenotype 3 (n=41) and phenotype 4 (n=53). Biomarker characteristics in each phenotype were evaluated.

RESULTS

Phenotype 1 presented the lowest value of N-terminal pro-brain natriuretic peptide (NT-proBNP), high-sensitive C reactive protein, tumour necrosis factor-α, growth differentiation factor (GDF)-15, troponin T and cystatin C, whereas phenotype 2, which is characterised by hypertension and cardiac hypertrophy, showed the highest value of these markers. Phenotype 3 showed the second highest value of GDF-15 and cystatin C. Phenotype 4 presented a low NT-proBNP value and a relatively high GDF-15.

CONCLUSIONS

Distinctive characteristics of biomarkers in HFpEF phenotypes would indicate differential underlying mechanisms to be elucidated. The contribution of inflammation to the pathogenesis varied considerably among different HFpEF phenotypes. Systemic inflammation substantially contributes to the pathophysiology of the classic HFpEF phenotype with cardiac hypertrophy.

TRIAL REGISTRATION NUMBER

UMIN-CTR ID: UMIN000021831.

Evaluation of the A2B Score for Prediction of Survival in Patients With Heart Failure in a Nationwide Cohort in Japan

BACKGROUND

Although a tool for sharing patient prognosis among all medical staff is desirable in heart failure (HF) cases, only a few simple HF prognostic scores are available. We previously presented the A2B score, a simple user-friendly HF risk score, and validated it in a small single-center cohort. In the present study, we validated it in a larger nationwide cohort.

METHODS AND RESULTS

We examined the 2-year mortality in relation to the A2B scores in 3483 patients from a Japanese nationwide cohort and attempted to stratify their prognoses according to the scores. The A2B score was determined by assigning points for age, anemia, and brain natriuretic peptide (BNP) level at discharge: age (<65 years, 0; 65-74 years, 1; ≥75 years, 2), anemia (hemoglobin ≥12 g/dL, 0; 10-11.9 g/dL, 1; <10 g/dL, 2), and BNP (<200 pg/mL, 0; 200-499 pg/mL, 1; ≥500 pg/mL, 2). Hemoglobin and BNP levels were applied to the data at discharge. The 2-year survival rates for A2B scores 1, 2, 3, 4, 5, and 6 were 94.1%, 83.2%, 74.1%, 63.5%, 51.6%, and 41.5%, respectively; the mortality rate increased by ≈10% for each point increase (c-index, 0.702). The A2B score was applicable in HF cases with reduced or preserved ejection fraction and remained useful when BNP was substituted with N-terminal proBNP (c-index, 0.749, 0.676, and 0.682, respectively).

CONCLUSIONS

The A2B score showed a good prognostic value for HF in a large population even when BNP was replaced with N-terminal proBNP.

N-Acetylcysteine Alleviates Phenylephrine-Induced Cardiomyocyte Dysfunction via Engaging PI3K/AKT Signaling Pathway

BACKGROUND

Increased reactive oxygen species (ROS) and oxidative stress response lead to cardiomyocyte hypertrophy and apoptosis, which play crucial roles in the pathogenesis of heart failure. The purpose of current research was to explore the role of antioxidant N-acetylcysteine (NAC) on cardiomyocyte dysfunction and the underlying molecular mechanisms.

METHODS AND RESULTS

Compared with control group without NAC treatment, NAC dramatically inhibited the cell size of primary cultured neonatal rat cardiomyocytes (NRCMs) tested by immunofluorescence staining and reduced the expression of representative markers associated with hypertrophic, fibrosis and apoptosis subjected to phenylephrine administration examined by reverse transcription-polymerase chain reaction (RT-PCR) and western blot. Moreover, enhanced ROS expression was attenuated, whereas activities of makers related to oxidative stress response examined by individual assay Kits, including total antioxidation capacity (T-AOC), glutathione peroxidase (GSH-Px), and primary antioxidant enzyme Superoxide dismutase (SOD) were induced by NAC treatment in NRCMs previously treated with phenylephrine. Mechanistically, we noticed that the protein expression levels of phosphorylated phosphatidylinositol 3-kinase (PI3K) and AKT were increased by NAC stimulation. More importantly, we identified that the negative regulation of NAC in cardiomyocyte dysfunction was contributed by PI3K/AKT signaling pathway through further utilization of PI3K/AKT inhibitor (LY294002) or agonist (SC79).

CONCLUSIONS

Collected, NAC could attenuate cardiomyocyte dysfunction subjected to phenylephrine, partially by regulating the ROS-induced PI3K/AKT-dependent signaling pathway.

Comprehensive effects of traditional Chinese medicine treatment on heart failure and changes in B-type natriuretic peptide levels: A meta-analysis

BACKGROUND

Heart failure (HF), a common cardiovascular condition, is characterized by significant morbidity and mortality. While traditional Chinese medicine (TCM) is often used as a complementary approach in HF management, systematic evaluations of its impact on clinical outcomes, TCM syndrome scores, and B-type natriuretic peptide (BNP) levels are lacking. This study fills this gap through a comprehensive analysis of randomized controlled trials (RCTs) focusing on TCM for HF treatment. It encompasses an assessment of methodological quality, a meta-analysis, and an evaluation of evidence quality based on established standards. The results offer crucial insights into the potential advantages and constraints of TCM in HF management.

AIM

To systematically analyze the effects of TCM on the clinical comprehensive outcomes, TCM syndrome scores, and BNP levels in patients with HF and evaluated the quality of evidence for these trials.

METHODS

RCTs on TCM for HF treatment published since the establishment of the database were searched in four Chinese and English databases, including China National Knowledge Infrastructure, Wanfang, VIP Information Chinese Science and Technology Journal, and PubMed. Methodological quality was assessed for the included studies with the Cochrane risk-of-bias assessment tool, and the meta-analysis and publication bias assessment was performed with the RevMan5.3 software. Finally, the quality of evidence was rated according to the GRADE criteria.

RESULTS

A total of 1098 RCTs were initially retrieved. After screening, 16 RCTs were finally included in our study, which were published between 2020 and 2023. These RCTs involved 1660 HF patients, including 832 in the TCM group [TCM combined with conventional Western medicine (CMW) treatment] and 828 in the CWM group (CWM treatment). The course of treatments varied from 1 wk to 3 months. TCM syndrome differentiation was analyzed in 11 of the included RCTs. In all included RCTs, outcome indicators included comprehensive clinical outcomes, TCM syndrome scores, and BNP levels. The meta-analysis results showed significant differences between the TCM and CWM groups in terms of comprehensive clinical outcomes [risk ratio = -0.54; 95% confidence interval (CI) = -0.61, -0.47; P < 0.00001], TCM syndrome scores [weighted mean difference (WMD) = -142.07; 95%CI = -147.56, -136.57; P < 0.00001], and BNP levels (WMD = -142.07; 95%CI = -147.56, -136.57; P < 0.00001). According to the GRADE criteria, RCTs where "TCM improves clinical comprehensive outcomes" were rated as low-quality evidence, and RCTs where "TCM reduces TCM syndrome scores" or "TCM decreases BNP levels" were rated as medium-quality evidence.

CONCLUSION

TCM combined with CWM treatment effectively improves comprehensive clinical outcomes and diminishes TCM syndrome scores and BNP levels in HF patients. Given the low and medium quality of the included RCTs, the application of these results should be cautious.

A Set of Possible Markers for Monitoring Heart Failure and Cognitive Impairment Associated: A Review of Literature from the Past 5 Years

BACKGROUND

Heart failure is an epidemiologically relevant disease because of the aging population and widespread lifestyles that promote it. In addition to the acute event, it is possible for the disease to become chronic with periodic flare-ups. It is essential to study pathology from a diagnostic and prognostic point of view and to identify parameters for effective monitoring. In addition, heart failure is associated with multiple comorbidities, including cognitive impairment, which is monitored clinically but not through specific biomarkers in these patients. The purpose of this review is to gather the most recent scientific evidence on a few possible biomarkers previously identified for monitoring heart failure and associated cognitive impairment.

METHODS

We surveyed studies inherent to a set of previously identified markers, evaluating English-language articles from the past five years conducted in adult heart failure patient populations. We used the databases PubMed, Web of Sciences, and Cochrane Library for search studies, and we considered articles published in journals with an impact factor greater than five in the publication year.

RESULTS

Among the biomarkers evaluated, a concordant indication for serial measurements for heart failure monitoring emerged only for interleukin-6. For the other markers, there is still little evidence available, which is interesting but sometimes conflicting. Interesting studies have also emerged for biomarkers of cognitive decline assessed in patients with heart failure, confirming the hypotheses of the increasingly studied heart-brain correlation.

CONCLUSION

Certainly, further studies in large populations are needed to identify effective biomarkers for monitoring heart failure and associated cognitive impairment.

Identifying OGN as a Biomarker Covering Multiple Pathogenic Pathways for Diagnosing Heart Failure: From Machine Learning to Mechanism Interpretation

BACKGROUND

The pathophysiologic heterogeneity of heart failure (HF) necessitates a more detailed identification of diagnostic biomarkers that can reflect its diverse pathogenic pathways.

METHODS

We conducted weighted gene and multiscale embedded gene co-expression network analysis on differentially expressed genes obtained from HF and non-HF specimens. We employed a machine learning integration framework and protein-protein interaction network to identify diagnostic biomarkers. Additionally, we integrated gene set variation analysis, gene set enrichment analysis (GSEA), and transcription factor (TF)-target analysis to unravel the biomarker-dominant pathways. Leveraging single-sample GSEA and molecular docking, we predicted immune cells and therapeutic drugs related to biomarkers. Quantitative polymerase chain reaction validated the expressions of biomarkers in the plasma of HF patients. A two-sample Mendelian randomization analysis was implemented to investigate the causal impact of biomarkers on HF.

RESULTS

We first identified COL14A1, OGN, MFAP4, and SFRP4 as candidate biomarkers with robust diagnostic performance. We revealed that regulating biomarkers in HF pathogenesis involves TFs (BNC2, MEOX2) and pathways (cell adhesion molecules, chemokine signaling pathway, cytokine-cytokine receptor interaction, oxidative phosphorylation). Moreover, we observed the elevated infiltration of effector memory CD4+ T cells in HF, which was highly related to biomarkers and could impact immune pathways. Captopril, aldosterone antagonist, cyclopenthiazide, estradiol, tolazoline, and genistein were predicted as therapeutic drugs alleviating HF via interactions with biomarkers. In vitro study confirmed the up-regulation of OGN as a plasma biomarker of HF. Mendelian randomization analysis suggested that genetic predisposition toward higher plasma OGN promoted the risk of HF.

CONCLUSIONS

We propose OGN as a diagnostic biomarker for HF, which may advance our understanding of the diagnosis and pathogenesis of HF.

Novel Biomarkers in Early Detection of Heart Failure: A Narrative Review

Heart failure (HF) represents a significant global health challenge, characterized by a variety of symptoms resulting from cardiac dysfunction. This dysfunction often leads to systemic and pulmonary congestion. The pathophysiology of HF is complex, involving stimulation of the sympathetic nervous system, which is insufficiently balanced by the release of natriuretic peptide. This imbalance leads to progressive hypertrophy and dilatation of the heart's chambers, impairing its pumping efficiency and increasing the risk of arrhythmias and conduction disorders. The prevalence of HF is exceptionally high in industrialized nations and is expected to increase owing to an aging population and advancements in diagnostic methods. This study emphasizes the critical role of early diagnosis in reducing morbidity and mortality associated with HF, focusing specifically on the evolving importance of biomarkers in managing this condition. Biomarkers have played a key role in transforming the diagnosis and treatment of HF. Traditional biomarkers such as b-type natriuretic peptide and N-terminal pro-b-type natriuretic peptide have been widely adopted for their cost-effectiveness and ease of access. However, the rise of novel biomarkers such as growth differentiation factor 15 and adrenomedullin has shown promising results, offering superior sensitivity and specificity. These new biomarkers enhance diagnostic accuracy, risk stratification, and prognostic evaluation in HF patients. Despite these advancements, challenges remain, such as limited availability, high costs, and the need for further validation in diverse patient populations. Through a comprehensive literature review across databases such as PubMed, Google Scholar, and the Cochrane Library, this study compiles and analyzes data from 18 relevant studies, offering a detailed understanding of the current state of HF biomarkers. The study examines both traditional and emerging biomarkers such as galectin-3 and soluble suppression of tumorigenicity 2 in HF, exploring their clinical roles and impact on patient outcomes.

Machine learning in the prediction of in-hospital mortality in patients with first acute myocardial infarction

BACKGROUND

Persistent efforts are required to further reduce the in-hospital mortality of patients suffering from acute myocardial infarction (AMI), even in the face of a global trend of declining AMI-related fatalities. We investigated deep machine learning models for in-hospital death prediction in patients on their first AMI.

METHOD

In this 2-center retrospective analysis, first AMI patients from Hospital I and Hospital II were included; 4783 patients from Hospital 1 were split in a 7:3 ratio between the training and testing sets. Data from 1053 AMI patients in Hospital II was used for further validation. 70 clinical information and laboratory examination parameters as predictive indicators were included. Logistic Regression Classifier (LR), Random Forests Classifier (RF), eXtreme Gradient Boosting (XGB), Support Vector Machine Classifier (SVM), Multilayer Perceptron (MLP), Gradient Boosting Machine (GBM), Bootstrapped Aggregation (Bagging) models with AMI patients were developed. The importance of selected variables was obtained through the Shapley Additive exPlanations (SHAP) method. The performance of each model was shown using the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (Average Precision; AP).

RESULT

The in-hospital mortality for AMI in the training, testing, and validation sets were 5.7 %, 5.6 %, and 6.0 %, respectively. The top 8 predictors were D-dimer, brain natriuretic peptide, cardiogenic shock, neutrophil, prothrombin time, blood urea nitrogen, cardiac arrest, and phosphorus. In the testing cohort, the models of LR, RF, XGB, SVM, MLP, GBM, and Bagging yielded AUROC values of 0.929, 0.931, 0.907, 0.868, 0.907, 0.923, and 0.932, respectively. Bagging has good predictive value and certain clinical value in external validation with AUROC 0.893.

CONCLUSION

In order to improve the forecasting accuracy of the risk of AMI patients, guide clinical nursing practice, and lower AMI inpatient mortality, this study looked into significant indicators and the optimal models for predicting AMI inpatient mortality.

The Role of CCTA-derived Cardiac Structure and Function Analysis in the Prediction of Readmission in Nonischemic Heart Failure

Cardiac function and structure significantly impact nonischemic heart failure (HF) patient outcomes. This study investigated 236 patients (107 nonischemic heart failure, 129 healthy) to assess the relationship between coronary computed tomography angiography (CCTA)-derived parameters and clinical outcomes. Among the nonischemic heart failure patients, 37.3% experienced readmissions. In this group, specific CCTA measurements were identified as significant predictors of readmission: epicardial adipose tissue (CTEAT) at 54.49 cm3 (HR: 1.05; 95% CI: 1.03-1.07; P < 0.001), cardiac muscle mass to lumen volume (CTV/M) at 20% (HR: 0.59; 95% CI: 0.48-0.72; P < 0.001), peri-coronary adipose (CTPCAT) at -64.68 HU (HR: 1.1; 95% CI: 1.03-1.16; P = 0.002) for the right coronary artery, -81.07 HU (HR: 1.3; 95% CI: 1.1-1.53; P = 0.002) for the left anterior descending artery, and -73.42 HU (HR: 1.33; 95% CI: 1.18-1.51; P < 0.001) for the circumflex branch of the left coronary artery. In patients with nonischemic heart failure, increased CTEAT, CTPCAT, and CTV/M independently predicted rehospitalization.

Heart transplantation and biomarkers: a review about their usefulness in clinical practice

Advanced heart failure (AdvHF) can only be treated definitively by heart transplantation (HTx), yet problems such right ventricle dysfunction (RVD), rejection, cardiac allograft vasculopathy (CAV), and primary graft dysfunction (PGD) are linked to a poor prognosis. As a result, numerous biomarkers have been investigated in an effort to identify and prevent certain diseases sooner. We looked at both established biomarkers, such as NT-proBNP, hs-troponins, and pro-inflammatory cytokines, and newer ones, such as extracellular vesicles (EVs), donor specific antibodies (DSA), gene expression profile (GEP), donor-derived cell free DNA (dd-cfDNA), microRNA (miRNA), and soluble suppression of tumorigenicity 2 (sST2). These biomarkers are typically linked to complications from HTX. We also highlight the relationships between each biomarker and one or more problems, as well as their applicability in routine clinical practice.