Circulating SERPINA3 improves prognostic stratification in patients with a de novo or worsened heart failure

Serine protease inhibitor, SerpinA3n, regulates cardiac remodelling after myocardial infarction

AIMS

Following myocardial infarction (MI), the heart repairs itself via a fibrotic repair response. The degree of fibrosis is determined by the balance between deposition of extracellular matrix (ECM) by activated fibroblasts and breakdown of nascent scar tissue by proteases that are secreted predominantly by inflammatory cells. Excessive proteolytic activity and matrix turnover has been observed in human heart failure, and protease inhibitors in the injured heart regulate matrix breakdown. Serine protease inhibitors (Serpins) represent the largest and the most functionally diverse family of evolutionary conserved protease inhibitors, and levels of the specific Serpin, SerpinA3, have been strongly associated with clinical outcomes in human MI as well as non-ischaemic cardiomyopathies. Yet, the role of Serpins in regulating cardiac remodelling is poorly understood. The aim of this study was to understand the role of Serpins in regulating scar formation after MI.

METHODS AND RESULTS

Using a SerpinA3n conditional knockout mice model, we observed the robust expression of Serpins in the infarcted murine heart and demonstrate that genetic deletion of SerpinA3n (mouse homologue of SerpinA3) leads to increased activity of substrate proteases, poorly compacted matrix, and significantly worse post-infarct cardiac function. Single-cell transcriptomics complemented with histology in SerpinA3n-deficient animals demonstrated increased inflammation, adverse myocyte hypertrophy, and expression of pro-hypertrophic genes. Proteomic analysis of scar tissue demonstrated decreased cross-linking of ECM peptides consistent with increased proteolysis in SerpinA3n-deficient animals.

CONCLUSION

Our study demonstrates a hitherto unappreciated causal role of Serpins in regulating matrix function and post-infarct cardiac remodelling.

Characterization of systolic and diastolic function, alongside proteomic profiling, in doxorubicin-induced cardiovascular toxicity in mice

BACKGROUND

The anthracycline doxorubicin (DOX) is a highly effective anticancer agent, especially in breast cancer and lymphoma. However, DOX can cause cancer therapy-related cardiovascular toxicity (CTR-CVT) in patients during treatment and in survivors. Current diagnostic criteria for CTR-CVT focus mainly on left ventricular systolic dysfunction, but a certain level of damage is required before it can be detected. As diastolic dysfunction often precedes systolic dysfunction, the current study aimed to identify functional and molecular markers of DOX-induced CTR-CVT with a focus on diastolic dysfunction.

METHODS

Male C57BL/6J mice were treated with saline or DOX (4 mg/kg, weekly i.p. injection) for 2 and 6 weeks (respectively cumulative dose of 8 and 24 mg/kg) (n = 8 per group at each time point). Cardiovascular function was longitudinally investigated using echocardiography and invasive left ventricular pressure measurements. Subsequently, at both timepoints, myocardial tissue was obtained for proteomics (liquid-chromatography with mass-spectrometry). A cohort of patients with CTR-CVT was used to complement the pre-clinical findings.

RESULTS

DOX-induced a reduction in left ventricular ejection fraction from 72 ± 2% to 55 ± 1% after 2 weeks (cumulative 8 mg/kg DOX). Diastolic dysfunction was demonstrated as prolonged relaxation (increased tau) and heart failure was evident from pulmonary edema after 6 weeks (cumulative 24 mg/kg DOX). Myocardial proteomic analysis revealed an increased expression of 12 proteins at week 6, with notable upregulation of SERPINA3N in the DOX-treated animals. The human ortholog SERPINA3 has previously been suggested as a marker in CTR-CVT. Upregulation of SERPINA3N was confirmed by western blot, immunohistochemistry, and qPCR in murine hearts. Thereby, SERPINA3N was most abundant in the endothelial cells. In patients, circulating SERPINA3 was increased in plasma of CTR-CVT patients but not in cardiac biopsies.

CONCLUSION

We showed that mice develop heart failure with impaired systolic and diastolic function as result of DOX treatment. Additionally, we could identify increased SERPINA3 levels in the mice as well as patients with DOX-induced CVT and demonstrated expression of SERPINA3 in the heart itself, suggesting that SERPINA3 could serve as a novel biomarker.

Identification of circadian rhythm-related gene classification patterns and immune infiltration analysis in heart failure based on machine learning

Background

Circadian rhythms play a key role in the failing heart, but the exact molecular mechanisms linking changes in the expression of circadian rhythm-related genes to heart failure (HF) remain unclear.

Methods

By intersecting differentially expressed genes (DEGs) between normal and HF samples in the Gene Expression Omnibus (GEO) database with circadian rhythm-related genes (CRGs), differentially expressed circadian rhythm-related genes (DE-CRGs) were obtained. Machine learning algorithms were used to screen for feature genes, and diagnostic models were constructed based on these feature genes. Subsequently, consensus clustering algorithms and non-negative matrix factorization (NMF) algorithms were used for clustering analysis of HF samples. On this basis, immune infiltration analysis was used to score the immune infiltration status between HF and normal samples as well as among different subclusters. Gene Set Variation Analysis (GSVA) evaluated the biological functional differences among subclusters.

Results

13 CRGs showed differential expression between HF patients and normal samples. Nine feature genes were obtained through cross-referencing results from four distinct machine learning algorithms. Multivariate LASSO regression and external dataset validation were performed to select five key genes with diagnostic value, including NAMPT, SERPINA3, MAPK10, NPPA, and SLC2A1. Moreover, consensus clustering analysis could divide HF patients into two distinct clusters, which exhibited different biological functions and immune characteristics. Additionally, two subgroups were distinguished using the NMF algorithm based on circadian rhythm associated differentially expressed genes. Studies on immune infiltration showed marked variances in levels of immune infiltration between these subgroups. Subgroup A had higher immune scores and more widespread immune infiltration. Finally, the Weighted Gene Co-expression Network Analysis (WGCNA) method was utilized to discern the modules that had the closest association with the two observed subgroups, and hub genes were pinpointed via protein-protein interaction (PPI) networks. GRIN2A, DLG1, ERBB4, LRRC7, and NRG1 were circadian rhythm-related hub genes closely associated with HF.

Conclusion

This study provides valuable references for further elucidating the pathogenesis of HF and offers beneficial insights for targeting circadian rhythm mechanisms to regulate immune responses and energy metabolism in HF treatment. Five genes identified by us as diagnostic features could be potential targets for therapy for HF.

Current evidence regarding the cellular mechanisms associated with cancer progression due to cardiovascular diseases

Several large cohort studies in cardiovascular disease (CVD) patients have shown an increased incidence of cancer. Previous studies in a myocardial infarction (MI) mouse model reported increased colon, breast, and lung cancer growth. The potential mechanisms could be due to secreted cardiokines and micro-RNAs from pathological hearts and immune cell reprogramming. A study in a MI-induced heart failure (HF) mouse demonstrated an increase in cardiac expression of SerpinA3, resulting in an enhanced proliferation of colon cancer cells. In MI-induced HF mice with lung cancer, the attenuation of tumor sensitivity to ferroptosis via the secretion of miR-22-3p from cardiomyocytes was demonstrated. In MI mice with breast cancer, immune cell reprogramming toward the immunosuppressive state was shown. However, a study in mice with renal cancer reported no impact of MI on tumor growth. In addition to MI, cardiac hypertrophy was shown to promote the growth of breast and lung cancer. The cardiokine potentially involved, periostin, was increased in the cardiac tissue and serum of a cardiac hypertrophy model, and was reported to increase breast cancer cell proliferation. Since the concept that CVD could influence the initiation and progression of several types of cancer is quite new and challenging regarding future therapeutic and preventive strategies, further studies are needed to elucidate the potential underlying mechanisms which will enable more effective risk stratification and development of potential therapeutic interventions to prevent cancer in CVD patients.

Current Insights and Future Directions in the Treatment of Heart Failure with Preserved Ejection Fraction

Heart failure is a clinical syndrome associated with poor quality of life, substantial healthcare resource utilization, and premature mortality, in large part related to high rates of hospitalizations. The clinical manifestations of heart failure are similar regardless of the ejection fraction. Unlike heart failure with reduced ejection fraction, there are few therapeutic options for treating heart failure with preserved ejection fraction. Molecular therapies that have shown reduced mortality and morbidity in heart failure with reduced ejection have not been proven to be effective for patients with heart failure and preserved ejection fraction. The study of pathophysiological processes involved in the production of heart failure with preserved ejection fraction is the basis for identifying new therapeutic means. In this narrative review, we intend to synthesize the existing therapeutic means, but also those under research (metabolic and microRNA therapy) for the treatment of heart failure with preserved ejection fraction.

Doxorubicin-induced cardiovascular toxicity: a longitudinal evaluation of functional and molecular markers

AIMS

Apart from cardiotoxicity, the chemotherapeutic doxorubicin (DOX) induces vascular toxicity, represented by arterial stiffness and endothelial dysfunction. Both parameters are of interest for cardiovascular risk stratification as they are independent predictors of future cardiovascular events in the general population. However, the time course of DOX-induced cardiovascular toxicity remains unclear. Moreover, current biomarkers for cardiovascular toxicity prove insufficient. Here, we longitudinally evaluated functional and molecular markers of DOX-induced cardiovascular toxicity in a murine model. Molecular markers were further validated in patient plasma.

METHODS AND RESULTS

DOX (4 mg/kg) or saline (vehicle) was administered intra-peritoneally to young, male mice weekly for 6 weeks. In vivo cardiovascular function and ex vivo arterial stiffness and vascular reactivity were evaluated at baseline, during DOX therapy (Weeks 2 and 4) and after therapy cessation (Weeks 6, 9, and 15). Left ventricular ejection fraction (LVEF) declined from Week 4 in the DOX group. DOX increased arterial stiffness in vivo and ex vivo at Week 2, which reverted thereafter. Importantly, DOX-induced arterial stiffness preceded reduced LVEF. Further, DOX impaired endothelium-dependent vasodilation at Weeks 2 and 6, which recovered at Weeks 9 and 15. Conversely, contraction with phenylephrine was consistently higher in the DOX-treated group. Furthermore, proteomic analysis on aortic tissue identified increased thrombospondin-1 (THBS1) and alpha-1-antichymotrypsin (SERPINA3) at Weeks 2 and 6. Up-regulated THBS1 and SERPINA3 persisted during follow-up. Finally, THBS1 and SERPINA3 were quantified in plasma of patients. Cancer survivors with anthracycline-induced cardiotoxicity (AICT; LVEF < 50%) showed elevated THBS1 and SERPINA3 levels compared with age-matched control patients (LVEF ≥ 60%).

CONCLUSIONS

DOX increased arterial stiffness and impaired endothelial function, which both preceded reduced LVEF. Vascular dysfunction restored after DOX therapy cessation, whereas cardiac dysfunction persisted. Further, we identified SERPINA3 and THBS1 as promising biomarkers of DOX-induced cardiovascular toxicity, which were confirmed in AICT patients.

Myeloperoxidase is a critical mediator of anthracycline-induced cardiomyopathy

Cardiotoxicity is a major complication of anthracycline therapy that negatively impacts prognosis. Effective pharmacotherapies for prevention of anthracycline-induced cardiomyopathy (AICM) are currently lacking. Increased plasma levels of the neutrophil-derived enzyme myeloperoxidase (MPO) predict occurrence of AICM in humans. We hypothesized that MPO release causally contributes to AICM. Mice intravenously injected with the anthracycline doxorubicin (DOX) exhibited higher neutrophil counts and MPO levels in the circulation and cardiac tissue compared to saline (NaCl)-treated controls. Neutrophil-like HL-60 cells exhibited increased MPO release upon exposition to DOX. DOX induced extensive nitrosative stress in cardiac tissue alongside with increased carbonylation of sarcomeric proteins in wildtype but not in Mpo-/- mice. Accordingly, co-treatment of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) with DOX and MPO aggravated loss of hiPSC-CM-contractility compared to DOX treatment alone. DOX-treated animals exhibited pronounced cardiac apoptosis and inflammation, which was attenuated in MPO-deficient animals. Finally, genetic MPO deficiency and pharmacological MPO inhibition protected mice from the development of AICM. The anticancer efficacy of DOX was unaffected by MPO deficiency. Herein we identify MPO as a critical mediator of AICM. We demonstrate that DOX induces cardiac neutrophil infiltration and release of MPO, which directly impairs cardiac contractility through promoting oxidation of sarcomeric proteins, cardiac inflammation and cardiomyocyte apoptosis. MPO thus emerges as a promising pharmacological target for prevention of AICM.

Exploring novel biomarkers in dilated cardiomyopathy‑induced heart failure by integrated analysis and in vitro experiments

Despite the availability of several effective and promising treatment methods, heart failure (HF) remains a significant public health concern that requires advanced therapeutic strategies and techniques. Dilated cardiomyopathy (DCM) is a crucial factor that contributes to the development and deterioration of HF. The aim of the present study was to identify novel biomarkers and biological pathways to enhance the diagnosis and treatment of patients with DCM-induced HF using weighted gene co-expression network analysis (WGCNA). A total of 24 co-expressed gene modules connected with DCM-induced HF were obtained by WGCNA. Among these, the blue module had the highest correlation with DCM-induced HF (r=0.91; P<0.001) and was enriched in the AGE-RAGE signaling pathway in diabetic complications, the p53 and MAPK signaling pathway, adrenergic signaling in cardiomyocytes, the Janus kinase-STAT signaling pathway and cGMP/PKG signaling. Eight key genes, including secreted protein acidic and rich in cysteine-related modular calcium-binding protein 2 (SMOC2), serpin family A member 3 (SERPINA3), myosin heavy chain 6 (MYH6), S100 calcium binding protein A9 (S100A9), tubulin α (TUBA)3E, TUBA3D, lymphatic vessel endothelial hyaluronic acid receptor 1 (LYVE1) and phospholipase C ε1 (PLCE1), were selected as the therapeutic targets of DCM-induced HF based on WGCNA and differentially expressed gene analysis. Immune cell infiltration analysis revealed that the proportion of naive B cells and CD4-activated memory T cells was markedly upregulated in DCM-induced HF tissues compared with tissues from healthy controls. Furthermore, reverse transcription-quantitative PCR in AC16 human cardiomyocyte cells treated with doxorubicin showed that among the eight key genes, only SERPINA3, MYH6, S100A9, LYVE1 and PLCE1 exhibited expression levels identical to those revealed by bioinformatics analysis, suggesting that these genes may be involved in the development of DCM-induced HF.

Cardiovascular Disease as a Consequence or a Cause of Cancer: Potential Role of Extracellular Vesicles

Both cardiovascular disease and cancer continue to be causes of morbidity and mortality all over the world. Preventing and treating heart disease in patients undergoing cancer treatment remain an important and ongoing challenge for improving the lives of cancer patients, but also for their survival. Despite ongoing efforts to improve patient survival, minimal advances have been made in the early detection of cardiovascular disease in patients suffering from cancer. Understanding the communication between cancer and cardiovascular disease can be based on a deeper knowledge of the molecular mechanisms that define the profile of the bilateral network and establish disease-specific biomarkers and therapeutic targets. The role of exosomes, microvesicles, and apoptotic bodies, together defined as extracellular vesicles (EVs), in cross talk between cardiovascular disease and cancer is in an incipient form of research. Here, we will discuss the preclinical evidence on the bilateral connection between cancer and cardiovascular disease (especially early cardiac changes) through some specific mediators such as EVs. Investigating EV-based biomarkers and therapies may uncover the responsible mechanisms, detect the early stages of cardiovascular damage and elucidate novel therapeutic approaches. The ultimate goal is to reduce the burden of cardiovascular diseases by improving the standard of care in oncological patients treated with anticancer drugs or radiotherapy.

Multiple-model machine learning identifies potential functional genes in dilated cardiomyopathy

Introduction

Machine learning (ML) has gained intensive popularity in various fields, such as disease diagnosis in healthcare. However, it has limitation for single algorithm to explore the diagnosing value of dilated cardiomyopathy (DCM). We aim to develop a novel overall normalized sum weight of multiple-model MLs to assess the diagnosing value in DCM.

Methods

Gene expression data were selected from previously published databases (six sets of eligible microarrays, 386 samples) with eligible criteria. Two sets of microarrays were used as training; the others were studied in the testing sets (ratio 5:1). Totally, we identified 20 differently expressed genes (DEGs) between DCM and control individuals (7 upregulated and 13 down-regulated).

Results

We developed six classification ML methods to identify potential candidate genes based on their overall weights. Three genes, serine proteinase inhibitor A3 (SERPINA3), frizzled-related proteins (FRPs) 3 (FRZB), and ficolin 3 (FCN3) were finally identified as the receiver operating characteristic (ROC). Interestingly, we found all three genes correlated considerably with plasma cells. Importantly, not only in training sets but also testing sets, the areas under the curve (AUCs) for SERPINA3, FRZB, and FCN3 were greater than 0.88. The ROC of SERPINA3 was significantly high (0.940 in training and 0.918 in testing sets), indicating it is a potentially functional gene in DCM. Especially, the plasma levels in DCM patients of SERPINA3, FCN, and FRZB were significant compared with healthy control.

Discussion

SERPINA3, FRZB, and FCN3 might be potential diagnosis targets for DCM, Further verification work could be implemented.

SERPINA3: Stimulator or Inhibitor of Pathological Changes

SERPINA3, also called α-1-antichymotrypsin (AACT, ACT), is one of the inhibitors of serine proteases, one of which is cathepsin G. As an acute-phase protein secreted into the plasma by liver cells, it plays an important role in the anti-inflammatory response and antiviral response. Elevated levels of SERPINA3 have been observed in heart failure and neurological diseases such as Alzheimer's disease or Creutzfeldt-Jakob disease. Many studies have shown increased expression levels of the SERPINA3 gene in various types of cancer, such as glioblastoma, colorectal cancer, endometrial cancer, breast cancer, or melanoma. In this case, the SERPINA3 protein is associated with an antiapoptotic function implemented by adjusting the PI3K/AKT or MAPK/ERK 1/2 signal pathways. However, the functions of the SERPINA3 protein are still only partially understood, mainly in the context of cancerogenesis, so it seems necessary to summarize the available information and describe its mechanism of action. In particular, we sought to amass the existing body of research focusing on the description of the underlying mechanisms of various diseases not related to cancer. Our goal was to present an overview of the correct function of SERPINA3 as part of the defense system, which unfortunately easily becomes the "Fifth Column" and begins to support processes of destruction.

Construction and analysis of heart failure diagnosis model based on random forest and artificial neural network

Heart failure is a global health problem and the number of sufferers is increasing as the population grows and ages. Existing diagnostic techniques for heart failure have various limitations in the clinical setting and there is a need to develop a new diagnostic model to complement the existing diagnostic methods. In recent years, with the development and improvement of gene sequencing technology, more genes associated with heart failure have been identified. We screened for differentially expressed genes in heart failure using available gene expression data from the Gene Expression Omnibus database and identified 6 important genes by a random forest classifier (ASPN, MXRA5, LUM, GLUL, CNN1, and SERPINA3). And we have successfully constructed a new heart failure diagnostic model using an artificial neural network and validated its diagnostic efficacy in a public dataset. We calculated heart failure-related differentially expressed genes and obtained 24 candidate genes by random forest classification, and selected the top 6 genes as important genes for subsequent analysis. The prediction weights of the genes of interest were determined by the neural network model and the model scores were evaluated in 2 independent sample datasets (GSE16499 and GSE57338 datasets). Since the weights of RNA-seq predictions for constructing neural network models were theoretically more suitable for disease classification of RNA-seq data, the GSE57338 dataset had the best performance in the validation results. The diagnostic model derived from our study can be of clinical value in determining the likelihood of HF occurring through cardiac biopsy. In the meantime, we need to further investigate the accuracy of the diagnostic model based on the results of our study.

Dysregulation and imbalance of innate and adaptive immunity are involved in the cardiomyopathy progression

Background

Cardiomyopathy is known to be a heterogeneous disease with numerous etiologies. They all have varying degrees and types of myocardial pathological changes, resulting in impaired contractility, ventricle relaxation, and heart failure. The purpose of this study was to determine the pathogenesis, immune-related pathways and important biomarkers engaged in the progression of cardiomyopathy from various etiologies.

Methods

We downloaded the gene microarray data from the Gene Expression Omnibus (GEO). The hub genes between cardiomyopathy and non-cardiomyopathy control groups were identified using differential expression analysis, least absolute shrinkage and selection operator (LASSO) regression and weighted gene co-expression network analysis (WGCNA). To assess the diagnostic precision of hub genes, receiver-operating characteristic (ROC) curves as well as the area under the ROC curve (AUC) were utilized. Then, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis and Gene Ontology (GO) analysis were conducted on the obtained differential genes. Finally, single-sample GSEA (ssGSEA) and Gene Set Enrichment Analysis (GSEA) were utilized to analyze the infiltration level of 28 immune cells and their relationship with hub genes based on gene expression profile data and all differential gene files.

Results

A total of 82 differentially expressed genes (DEGs) were screened after the training datasets were merged and intersected. The WGCNA analysis clustered the expression profile data into four co-expression modules, The turquoise module exhibited the strongest relationship with clinical traits, and nine candidate key genes were obtained from the module. Then we intersected DEGs with nine candidate genes. LASSO regression analysis identified the last three hub genes as promising biomarkers to distinguish the cardiomyopathy group from the non-cardiomyopathy control group. ROC curve analysis in the validation dataset revealed the sensitivity and accuracy of three hub genes as marker genes. The majority of the functional enrichment analysis results were concentrated on immunological and inflammatory pathways. Immune infiltration analysis revealed a significant correlation between regulatory T cells, type I helper T cells, macrophages, myeloid-derived suppressor cells, natural killer cells, activated dendritic cells and the abundance of immune infiltration in hub genes.

Conclusion

The hub genes (CD14, CCL2, and SERPINA3) can be used as markers to distinguish cardiomyopathy from non-cardiomyopathy individuals. Among them, SERPINA3 has the best diagnostic performance. T cell immunity (adaptive immune response) is closely linked to cardiomyopathy progression. Hub genes may protect the myocardium from injury through myeloid-derived suppressor cells, regulatory T cells, helper T cells, monocytes/macrophages, natural killer cells and activated dendritic cells. The innate immune response is crucial to this process. Dysregulation and imbalance of innate immune cells or activation of adaptive immune responses are involved in cardiomyopathy disease progression in patients.

Increased SERPINA3 Level Is Associated with Ulcerative Colitis

Ulcerative colitis (UC) is a recurrent, chronic intestinal disease that is currently incurable. Its pathogenesis remains to be further understood. Therefore, seeking new biomarkers and potential drug targets is urgent for the effective treatment of UC. In this study, the gene expression profile GSE38713 was obtained from the GEO (Gene Expression Omnibus) database. Data normalisation and screening of the differentially expressed genes (DEGs) were conducted using R software, and gene ontology (GO) enrichment was performed using Metascape online tools. The PubMed database was used to screen new genes that have not been reported, and SERPINA3 was selected. The correlation between SERPINA3 and other inflammatory factors was analysed by Spearman correlation analysis. Finally, colitis model mice and an in-vitro model were established to validate the function of the SERPINA3 gene. SERPINA3 gene expression was markedly increased in UC patient samples, colitis models and in-vitro models and showed an association with other inflammatory factors. ROC analysis indicated that SERPINA3 could represent a potential biomarker of active UC. Additionally, silencing SERPINA3 in an in-vitro intestinal epithelial inflammatory model significantly decreased the mRNA level of inflammatory factors. This study provides supportive evidence that SERPINA3 may act as a key biomarker and potential drug target in UC treatment.