Identification of three novel pathogenic mutations in sarcomere genes associated with familial hypertrophic cardiomyopathy based on multi-omics study

Cardiometabolic Modulation by Semaglutide Contributes to Cardioprotection in Rats with Myocardial Infarction

Background

Acute myocardial infarction (AMI) is a significant clinical challenge. Semaglutide has therapeutic potential in cardiovascular disease management, but its specific impact and mechanisms in AMI are not fully understood.

Methods

Twenty-four male Sprague-Dawley rats were divided into three groups: control (Control), infarction-only (MI), and semaglutide-treated (SEMA). Weight, blood glucose, and lipid profiles were analyzed. Cardiac function was evaluated via echocardiography. Histopathological assessment and immunohistochemical analysis were performed. Untargeted metabolomic analysis using LC-MS/MS was utilized.

Results

Semaglutide treatment was associated with a reduction in body weight, blood glucose, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C), as well as an enhancement in the left ventricular ejection fraction (Control vs MI vs SEMA, 69.13±4.30 vs 30.16±3.17 vs 39.81±6.13, P < 0.05). It also had a lower collagen volume fraction (3.05 vs 34.05 vs 17.73, P < 0.05) and ameliorated the accumulation of glycogen in the myocardium. Metabolomic profiling revealed differentially expressed metabolites between the control/MI and MI/SEMA groups, predominantly within benzenoid, lipid, and organic acid categories. Pathway enrichment analysis highlighted amino sugar and nucleotide sugar metabolism, chlorocyclohexane and chlorobenzene degradation, and phenylalanine, tyrosine, and tryptophan biosynthesis. Random forest analysis identified key metabolites, including downregulated Docusate sodium, 1-(2-Thienyl)-1-heptanone, and Adenylyl-molybdopterin, alongside upregulated Methylenediphosphonic acid, Choline sulfate, and Lactosamine.

Conclusion

Semaglutide significantly ameliorated myocardial fibrosis and metabolic dysregulation in rats post-myocardial infarction. Its mechanism involves modulating glucose metabolism, lipid metabolism, and organic acid metabolism. Targeted metabolites, including Docusate sodium, 1-(2-Thienyl)-1-heptanone, Adenylyl-molybdopterin, Methylenediphosphonic acid, Choline sulfate, and Lactosamine, are implicated in the metabolic reprogramming induced by semaglutide.

Serum metabolism distribution in individuals exposed to dioxins: A case study of residents near the municipal solid waste incinerators in China

Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) have attracted considerable attention owing to their environmental persistence, bioaccumulation, and high toxicity. This study aimed to investigate changes in serum metabolites following exposure to PCDD/Fs and to reveal a novel pathogenesis of PCDD/Fs. Serum samples were collected from 75 residents living near a municipal solid waste incinerator in China to analyse the relationship between PCDD/Fs and serum metabolic components. The serum level in the low-exposure group [19.07 (13.44-23.89) pg-TEQ/L] was significantly lower than that in the high-exposure group [115.60 (52.28-592.65) pg-TEQ/L]. Non-targeted metabolomic studies based on liquid chromatography-high resolution mass spectrometry have been applied to the metabolomic analysis of serum. Thirty-seven metabolites with significant differences among the different groups were identified as biomarkers. Pathway analysis revealed that high dioxin exposure perturbed various biological processes, including glycerol phospholipid metabolism and the interconversion of pentose and glucuronate. The results of a population health survey showed that the serum dioxin concentration in patients with diabetes was significantly higher than that in the control population. These findings suggest that dioxin exposure is associated with several potential adverse health risks, including inflammation, diabetes, and cardiovascular disease, through metabolic changes.

Metabolite correlation permutation after mice acute exposure to PM2.5: Holistic exploration of toxicometabolomics by network analysis

Many environmental toxicants can cause systemic effects, such as fine particulate matter (PM2.5), which can penetrate the respiratory barrier and induce effects in multiple tissues. Although metabolomics has been used to identify biomarkers for PM2.5, its multi-tissue toxicology has not yet been explored holistically. Our objective is to explore PM2.5 induced metabolic alterations and unveil the intra-tissue responses along with inter-tissue communicational effects. In this study, following a single intratracheal instillation of multiple doses (0, 25, and 150 μg as the control, low, and high dose), non-targeted metabolomics was employed to evaluate the metabolic impact of PM2.5 across multiple tissues. PM2.5 induced tissue-specific and dose-dependent disturbances of metabolites and their pathways. The remarkable increase of both intra- and inter-tissue correlations was observed, with emphasis on the metabolism connectivity among lung, spleen, and heart; the tissues' functional specificity has marked their toxic modes. Beyond the inter-status comparison of the metabolite fold-changes, the current correlation network built on intra-status can offer additional insights into how the multiple tissues and their metabolites coordinately change in response to external stimuli such as PM2.5 exposure.

Fine tuning contractility: atrial sarcomere function in health and disease

The molecular mechanisms of sarcomere proteins underlie the contractile function of the heart. Although our understanding of the sarcomere has grown tremendously, the focus has been on ventricular sarcomere isoforms due to the critical role of the ventricle in health and disease. However, atrial-specific or -enriched myofilament protein isoforms, as well as isoforms that become expressed in disease, provide insight into ways this complex molecular machine is fine-tuned. Here, we explore how atrial-enriched sarcomere protein composition modulates contractile function to fulfill the physiological requirements of atrial function. We review how atrial dysfunction negatively affects the ventricle and the many cardiovascular diseases that have atrial dysfunction as a comorbidity. We also cover the pathophysiology of mutations in atrial-enriched contractile proteins and how they can cause primary atrial myopathies. Finally, we explore what is known about contractile function in various forms of atrial fibrillation. The differences in atrial function in health and disease underscore the importance of better studying atrial contractility, especially as therapeutics currently in development to modulate cardiac contractility may have different effects on atrial sarcomere function.

Prediction of diagnostic gene biomarkers for hypertrophic cardiomyopathy by integrated machine learning

OBJECTIVES

Hypertrophic cardiomyopathy (HCM), a leading cause of heart failure and sudden death, requires early diagnosis and treatment. This study investigated the underlying pathogenesis and explored potential diagnostic gene biomarkers for HCM.

METHODS

Transcriptional profiles of myocardial tissues from patients with HCM (dataset GSE36961) were downloaded from the Gene Expression Omnibus database and subjected to bioinformatics analyses, including differentially expressed gene (DEG) identification, enrichment analyses, and protein-protein interaction (PPI) network analysis. Least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination were performed to identify candidate diagnostic gene biomarkers. mRNA expression levels of candidate biomarkers were tested in an external dataset (GSE141910); area under the receiver operating characteristic curve (AUC) values were obtained to validate diagnostic efficacy.

RESULTS

Overall, 156 DEGs (109 downregulated, 47 upregulated) were identified. Enrichment and PPI network analyses indicated that the DEGs were involved in biological functions and molecular pathways including inflammatory response, platelet activity, complement and coagulation cascades, extracellular matrix organization, phagosome, apoptosis, and VEGFA-VEGFR2 signaling. RASD1, CDC42EP4, MYH6, and FCN3 were identified as diagnostic biomarkers for HCM.

CONCLUSIONS

RASD1, CDC42EP4, MYH6, and FCN3 might be diagnostic gene biomarkers for HCM and can provide insights concerning HCM pathogenesis.

Using whole genome sequence findings to assess gene-disease causality in cardiomyopathy and arrhythmia patients

Aim: The genetic etiologies of cardiomyopathies and arrhythmias have not been fully elucidated. Materials & methods: Research findings from genome analyses in a cardiomyopathy and arrhythmia cohort were gathered. Gene-disease relationships from two databases were compared with patient phenotypes. A literature review was conducted for genes with limited evidence. Results: Of 43 genes with candidate findings from 18 cases, 23.3% of genes had never been curated, 15.0% were curated for cardiomyopathies, 16.7% for arrhythmias and 31.3% for other conditions. 25.5% of candidate findings were curated for the patient's specific phenotype with 11.8% having definitive evidence. MYH6 and TPCN1 were flagged for recuration. Conclusion: Findings from genome sequencing in disease cohorts may be useful to guide gene-curation efforts.

Identification and analysis of key hypoxia- and immune-related genes in hypertrophic cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM), an autosomal dominant genetic disease, is the main cause of sudden death in adolescents and athletes globally. Hypoxia and immune factors have been revealed to be related to the pathology of HCM. There is growing evidence of a role for hypoxia and inflammation as triggers and enhancers in the pathology in HCM. However, the role of hypoxia- and immune-related genes in HCM have not been reported.

METHODS

Firstly, we obtained four HCM-related datasets from the Gene Expression Omnibus (GEO) database for differential expression analysis. Immune cells significantly expressed in normal samples and HCM were then screened by a microenvironmental cell population counter (MCP-counter) algorithm. Next, hypoxia- and immune-related genes were screened by the LASSO + support vector machine recursive feature elimination (SVM-RFE) and weighted gene co-expression network analysis (WGCNA). Single-gene enrichment analysis and expression validation of key genes were then performed. Finally, we constructed a competing endogenous RNA (ceRNA) network of key genes.

RESULTS

In this study, 35 differentially expressed hypoxia genes were found. By using LASSO + SVM-RFE analysis, 10 more targets with differentially expressed hypoxia genes were identified. The MCP-count algorithm yielded five differentially expressed immune cells, and after assessing them for WGCNA characteristics, 612 immune genes were discovered. When hypoxia and immune genes were combined for cross-tabulation analysis, three hypoxia- and immune-related genes (ATP2A2, DDAH1, and OMA1) were identified.

CONCLUSION

Based on hypoxia characteristic genes, three key genes were identified. These were also significantly related to immune activation, which proves a theoretical basis and reference value for studying the relationship between HCM and hypoxia and immunity.

Significance of α-Myosin Heavy Chain (MYH6) Variants in Hypoplastic Left Heart Syndrome and Related Cardiovascular Diseases

Hypoplastic left heart syndrome (HLHS) is a severe congenital heart disease (CHD) with complex genetic inheritance. HLHS segregates with other left ventricular outflow tract (LVOT) malformations in families, and can present as either an isolated phenotype or as a feature of a larger genetic disorder. The multifactorial etiology of HLHS makes it difficult to interpret the clinical significance of genetic variants. Specific genes have been implicated in HLHS, including rare, predicted damaging MYH6 variants that are present in >10% of HLHS patients, and which have been shown to be associated with decreased transplant-free survival in our previous studies. MYH6 (α-myosin heavy chain, α-MHC) variants have been reported in HLHS and numerous other CHDs, including LVOT malformations, and may provide a genetic link to these disorders. In this paper, we outline the MYH6 variants that have been identified, discuss how bioinformatic and functional studies can inform clinical decision making, and highlight the importance of genetic testing in HLHS.

Metabolic Reprogramming of the Right Ventricle and Pulmonary Arteries in a Flow-Associated Pulmonary Arterial Hypertension Rat Model

Pulmonary arterial hypertension (PAH) is a complex devastating disease relevant to remarkable metabolic dysregulation. Although various research studies on PAH from a metabolic perspective have been emerging, pathogenesis of PAH varies in different categories. Research on metabolic reprogramming in flow-associated PAH remains insufficient. An untargeted metabolomic profiling platform was used to evaluate the metabolic profile of pulmonary arteries (PAs) as well as the right ventricle (RV) in a flow-associated PAH rat model in the present work. A total of 79 PAs and 128 RV metabolites were significantly altered in PAH rats, among which 39 metabolites were assessed as shared dysregulated metabolites in PAs and the RV. Pathway analysis elucidated that, in PAs of PAH rats, pathways of phenylalanine, tyrosine, and tryptophan biosynthesis and linoleic acid metabolism were significantly altered, while in the RV, arginine biosynthesis and linoleic acid metabolism were altered dramatically. Further integrated analysis of shared dysregulated PA and RV metabolites demonstrated that the linoleic acid metabolism and the arachidonic acid (AA) metabolism were the key pathways involved in the pathogenesis of flow-associated PAH. Results obtained from the present work indicate that the PAH pathogenesis could be mediated by widespread metabolic reprogramming. In particular, the dysregulation of AA metabolism may considerably contribute to the development of high blood flow-associated PAH.