Synergism between obesity and HFpEF on neutrophils phenotype and its regulation by adipose tissue-molecules and SGLT2i dapagliflozin

Molecular remodeling in comorbidities associated with heart failure: a current update

Recent advances in genomics and proteomics have helped in understanding the molecular mechanisms and pathways of comorbidities and heart failure. In this narrative review, we reviewed molecular alterations in common comorbidities associated with heart failure such as obesity, diabetes mellitus, systemic hypertension, pulmonary hypertension, coronary artery disease, hypercholesteremia and lipoprotein abnormalities, chronic kidney disease, and atrial fibrillation. We searched the electronic databases, PubMed, Ovid, EMBASE, Google Scholar, CINAHL, and PhysioNet for articles without time restriction. Although the association between comorbidities and heart failure is already well established, recent studies have explored the molecular pathways in much detail. These molecular pathways demonstrate how novels drugs for heart failure works with respect to the pathways associated with comorbidities. Understanding the altered molecular milieu in heart failure and associated comorbidities could help to develop newer medications and targeted therapies that incorporate these molecular alterations as well as key molecular variations across individuals to improve therapeutic outcomes. The molecular alterations described in this study could be targeted for novel and personalized therapeutic approaches in the future. This knowledge is also critical for developing precision medicine strategies to improve the outcomes for patients living with these conditions.

Sex-specific role of high-fat diet and stress on behavior, energy metabolism, and the ventromedial hypothalamus

BACKGROUND

Scientific evidence highlights the influence of biological sex on the relationship between stress and metabolic dysfunctions. However, there is limited understanding of how diet and stress concurrently contribute to metabolic dysregulation in both males and females. Our study aimed to investigate the combined effects of high-fat diet (HFD) induced obesity and repeated stress on fear-related behaviors, metabolic, immune, and hypothalamic outcomes in male and female mice.

METHODS

To investigate this, we used a highly reliable rodent behavioral model that faithfully recapitulates key aspects of post-traumatic stress disorder (PTSD)-like fear. We subjected mice to footshock stressor followed by a weekly singular footshock stressor or no stressor for 14 weeks while on either an HFD or chow diet. At weeks 10 and 14 we conducted glucose tolerance and insulin sensitivity measurements. Additionally, we placed the mice in metabolic chambers to perform indirect calorimetric measurements. Finally, we collected brain and peripheral tissues for cellular analysis.

RESULTS

We observed that HFD-induced obesity disrupted fear memory extinction, increased glucose intolerance, and affected energy expenditure specifically in male mice. Conversely, female mice on HFD exhibited reduced respiratory exchange ratio (RER), and a significant defect in glucose tolerance only when subjected to repeated stress. Furthermore, the combination of repeated stress and HFD led to sex-specific alterations in proinflammatory markers and hematopoietic stem cells across various peripheral metabolic tissues. Single-nuclei RNA sequencing (snRNAseq) analysis of the ventromedial hypothalamus (VMH) revealed microglial activation in female mice on HFD, while male mice on HFD exhibited astrocytic activation under repeated stress.

CONCLUSIONS

Overall, our findings provide insights into complex interplay between repeated stress, high-fat diet regimen, and their cumulative effects on health, including their potential contribution to the development of PTSD-like stress and metabolic dysfunctions, emphasizing the need for further research to fully understand these interconnected pathways and their implications for health.

Semaglutide modulates prothrombotic and atherosclerotic mechanisms, associated with epicardial fat, neutrophils and endothelial cells network

BACKGROUND

Obesity has increased in recent years with consequences on diabetes and other comorbidities. Thus, 1 out of 3 diabetic patients suffers cardiovascular disease (CVD). The network among glucose, immune system, endothelium and epicardial fat has an important role on pro-inflammatory and thrombotic mechanisms of atherogenesis. Since semaglutide, long-acting glucagon like peptide 1- receptor agonist (GLP-1-RA), a glucose-lowering drug, reduces body weight, we aimed to study its effects on human epicardial fat (EAT), aortic endothelial cells and neutrophils as atherogenesis involved-cardiovascular cells.

METHODS

EAT and subcutaneous fat (SAT) were collected from patients undergoing cardiac surgery. Differential glucose consumption and protein cargo of fat-released exosomes, after semaglutide or/and insulin treatment were analyzed by enzymatic and TripleTOF, respectively. Human neutrophils phenotype and their adhesion to aortic endothelial cells (HAEC) or angiogenesis were analyzed by flow cytometry and functional fluorescence analysis. Immune cells and plasma protein markers were determined by flow cytometry and Luminex-multiplex on patients before and after 6 months treatment with semaglutide.

RESULTS

GLP-1 receptor was expressed on fat and neutrophils. Differential exosomes-protein cargo was identified on EAT explants after semaglutide treatment. This drug increased secretion of gelsolin, antithrombotic protein, by EAT, modulated CD11b on neutrophils, its migration and endothelial adhesion, induced by adiposity protein, FABP4, or a chemoattractant. Monocytes and neutrophils phenotype and plasma adiposity, stretch, mesothelial, fibrotic, and inflammatory markers on patients underwent semaglutide treatment for 6 months showed a 20% reduction with statistical significance on FABP4 levels and an 80% increase of neutrophils-CD88.

CONCLUSION

Semaglutide increases endocrine activity of epicardial fat with antithrombotic properties. Moreover, this drug modulates the pro-inflammatory and atherogenic profile induced by the adiposity marker, FABP4, which is also reduced in patients after semaglutide treatment.

Clinical Profiling and Biomarkers for Post-Operative Atrial Fibrillation Prediction in Patients Undergoing Cardiac Surgery

Post-operative atrial fibrillation (POAF) is the most common arrhythmia in the post-operative period after cardiac surgery. We aim to investigate the main clinical, local, and/or peripheral biochemical and molecular predictors for POAF in patients undergoing coronary and/or valve surgery. Between August 2020 and September 2022, consecutive patients undergoing cardiac surgery without previous history of AF were studied. Clinical variables, plasma, and biological tissues (epicardial and subcutaneous fat) were obtained before surgery. Pre-operative markers associated with inflammation, adiposity, atrial stretch, and fibrosis were analyzed on peripheral and local samples with multiplex assay and real-time PCR. Univariate and multivariate logistic regression analyses were performed in order to identify the main predictors for POAF. Patients were followed-up until hospital discharge. Out of 123 consecutive patients without prior AF, 43 (34.9%) developed POAF during hospitalization. The main predictors were cardiopulmonary bypass time (odds ratio (OR) 1.008 (95% confidence interval (CI), 1.002-1.013), p = 0.005), and plasma pre-operative orosomucoid levels (OR 1.008 (1.206-5.761). After studying differences regarding sex, orosomucoid was the best predictor for POAF in women (OR 2.639 (95% CI, 1.455-4.788), p = 0.027) but not in men. The results support the pre-operative inflammation pathway as a factor involved in the risk of POAF, mainly in women.

Personalized Management for Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous clinical syndrome with multiple underlying mechanisms and comorbidities that leads to a variety of clinical phenotypes. The identification and characterization of these phenotypes are essential for better understanding the precise pathophysiology of HFpEF, identifying appropriate treatment strategies, and improving patient outcomes. Despite accumulating data showing the potentiality of artificial intelligence (AI)-based phenotyping using clinical, biomarker, and imaging information from multiple dimensions in HFpEF management, contemporary guidelines and consensus do not incorporate these in daily practice. In the future, further studies are required to authenticate and substantiate these findings in order to establish a more standardized approach for clinical implementation.