Widespread Down-Regulation of Cardiac Mitochondrial and Sarcomeric Genes in Patients With Sepsis

Utilizing omics technologies in the investigation of sepsis-induced cardiomyopathy

Sepsis-induced cardiomyopathy (SIC) is a common and high-mortality complication among critically ill patients. Uncertainties persist regarding the pathogenesis, pathophysiology, and diagnosis of SIC, underscoring the necessity to investigate potential biological mechanisms. With the rise of omics technologies, leveraging their high throughput and big data advantages, a systems biology perspective is employed to study the biological processes of SIC. This approach aids in gaining a better understanding of the disease's onset, progression, and outcomes, ultimately providing improved guidance for clinical practices. This review summarizes the currently applied omics technologies, omics studies related to SIC, and relevant omics databases.

Identification of senescence related hub genes and potential therapeutic compounds for dilated cardiomyopathy via comprehensive transcriptome analysis

BACKGROUND

Dilated cardiomyopathy (DCM) is a common cause of heart failure. However, the role of cellular senescence in DCM has not been fully elucidated. Here, we aimed to investigate senescence in DCM, identify senescence related characteristic genes, and explore the potential small molecule compounds for DCM treatment.

METHODS

DCM-associated datasets and senescence-related genes were respectively obtained from Gene Expression Omnibus (GEO) database and CellAge database. The characteristic genes were identified through methods including weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO), and random forest. The expression of characteristic genes was verified in the mouse DCM model. Moreover, the CIBERSORT algorithm was applied to analyze immune characteristics of DCM. Finally, several therapeutic compounds were predicted by CMap analysis, and the potential mechanism of chlorogenic acid (CGA) was investigated by molecular docking and molecular dynamics simulation.

RESULTS

Three DCM- and senescence-related characteristic genes (MME, GNMT and PLA2G2A) were ultimately identified through comprehensive transcriptome analysis, and were experimentally verified in the doxorubicin induced mouse DCM. Meanwhile, the established diagnostic model, derived from dataset analysis, showed ideal diagnostic performance for DCM. Immune cell infiltration analysis suggested dysregulation of inflammation in DCM, and the characteristic genes were significantly associated with invasive immune cells. Finally, based on the specific gene expression profile of DCM, several potential therapeutic compounds were predicted through CMap analysis. In addition, molecular docking and molecular dynamics simulations suggested that CGA could bind to the active pocket of MME protein.

CONCLUSION

Our study presents three characteristic genes (MME, PLA2G2A, and GNMT) and a novel senescence-based diagnostic nomogram, and discusses potential therapeutic compounds, providing new insights into the diagnosis and treatment of DCM.

ANXA1sp modulates the protective effect of Sirt3-induced mitophagy against sepsis-induced myocardial injury in mice

AIM

Sepsis-induced myocardial injury (SIMI) may be associated with insufficient mitophagy in cardiomyocytes, but the exact mechanism involved remains unknown. Sirtuin 3 (Sirt3) is mainly found in the mitochondrial matrix and is involved in repairing mitochondrial function through means such as the activation of autophagy. Previously, we demonstrated that the annexin-A1 small peptide (ANXA1sp) can promote Sirt3 expression in mitochondria. In this study, we hypothesized that the activation of Sirt3 by ANXA1sp induces mitophagy, thereby providing a protective effect against SIMI in mice.

METHODS

A mouse model of SIMI was established via cecal ligation and puncture. Intraperitoneal injections of ANXA1sp, 3TYP, and 3MA were administered prior to modeling. After successful modeling, IL-6, TNF-α, CK-MB, and CTn-I levels were measured; cardiac function was assessed using echocardiography; myocardial mitochondrial membrane potential, ROS, and ATP production were determined; myocardial mitochondrial ultrastructure was observed using transmission electron microscopy; and the expression levels of Sirt3 and autophagy-related proteins were detected using western blotting.

RESULTS

ANXA1sp significantly reduced serum IL-6, TNF-α, CK-MB, and CTn-I levels; decreased myocardial ROS production; increased mitochondrial membrane potential and ATP synthesis; and improved myocardial mitochondrial ultrastructure in septic mice. Furthermore, ANXA1sp promoted Sirt3 expression and activated the AMPK-mTOR pathway to induce myocardial mitophagy. These protective effects of ANXA1sp were reversed upon treatment with the Sirt3 blocker, 3-TYP.

CONCLUSION

ANXA1sp can reverse SIMI, and the underlying mechanism may be related to the activation of the AMPK-mTOR pathway following upregulation of Sirt3 by ANXA1sp, which, in turn, induces autophagy.

S100A9 as a Key Myocardial Injury Factor Interacting with ATP5 Exacerbates Mitochondrial Dysfunction and Oxidative Stress in Sepsis-Induced Cardiomyopathy

Purpose

Sepsis-induced cardiomyopathy (SICM) is a prevalent cardiac dysfunction caused by sepsis. Mitochondrial dysfunction is a crucial pathogenic factor associated with adverse cardiovascular adverse events; however, research on SICM remains insufficient.

Methods

To investigate the factors contributing to the pathological progression of SICM, we performed a comprehensive analysis of transcriptomic data from the GEO database using bioinformatics and machine learning techniques. CRISPR-Cas9 S100A9 knockout mice and primary cardiomyocytes were exposed to lipopolysaccharide to simulate SICM. Transcriptome analysis and mass spectrometry of primary cardiomyocytes were used to determine the potential pathogenic mechanisms of S100A9. The mitochondrial ultrastructure and mitochondrial membrane potential (MMP) were detected using transmission electron microscopy and flow cytometry, respectively. Pink1/Parkin and Drp1 proteins were detected using Western blotting to evaluate mitochondrial autophagy and division. The mtDNA and mRNA levels of mitochondrial transcription factors and synthases were evaluated using real-time polymerase chain reaction.

Results

Bioinformatics analysis identified 12 common differentially expressed genes, including SERPINA3N, LCN2, MS4A6D, LRG1, OSMR, SOCS3, FCGR2b, S100A9, S100A8, CASP4, ABCA8A, and NFKBIZ. Significant S100A9 upregulation was closely associated with myocardial injury exacerbation and cardiac function deterioration. GSEA revealed that myocardial contractile function, oxidative stress, and mitochondrial function were significantly affected by S100A9. Knocking out S100A9 alleviates the inflammatory response and mitochondrial dysfunction. The interaction of S100A9 with ATP5 enhanced mitochondrial division and autophagy, inhibited MMP and ATP synthesis, and induced oxidative stress, which are related to the Nlrp3-Nfkb-Caspase1 and Drp1-Pink1-Parkin signaling pathways. The expression of mitochondrial transcription factors (TFAM and TFBM) and ATP synthetases (ATP6 and ATP8, as well as COX1, COX2, and COX3) was further suppressed by S100A9 in SICM. Targeted S100A9 inhibition by paquinimod partially reversed myocardial mitochondrial dysfunction and oxidative stress.

Conclusion

The interaction of S100A9 with ATP5 exacerbates myocardial damage in sepsis by inducing mitochondrial dysfunction and oxidative stress.

Integrated Bioinformatics Analysis Reveals the Aberrantly Methylated Differentially Expressed Genes in Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) causes heart failure and sudden death. Epigenetics is crucial in cardiomyopathy susceptibility and progression; however, the relationship between epigenetics, particularly DNA methylation, and DCM remains unknown. Therefore, this study identified aberrantly methylated differentially expressed genes (DEGs) associated with DCM using bioinformatics analysis and characterized their clinical utility in DCM. DNA methylation expression profiles and transcriptome data from public datasets of human DCM and healthy control cardiac tissues were obtained from the Gene Expression Omnibus public datasets. Then an epigenome-wide association study was performed. DEGs were identified in both DCM and healthy control cardiac tissues. In total, 3,353 cytosine-guanine dinucleotide sites annotated to 2,818 mRNAs were identified, and 479 DCM-related genes were identified. Subsequently, core genes were screened using logistic, least absolute shrinkage and selection operator, random forest, and support vector machine analyses. The overlapping of these genes resulted in DEGs with abnormal methylation patterns. Cross-tabulation analysis identified 8 DEGs with abnormal methylation. Real-time quantitative polymerase chain reaction confirmed the expression of aberrantly methylated DEGs in mice. In DCM murine cardiac tissues, the expressions of SLC16A9, SNCA, PDE5A, FNDC1, and HTRA1 were higher compared to normal murine cardiac tissues. Moreover, logistic regression model associated with aberrantly methylated DEGs was developed to evaluate the diagnostic value, and the area under the receiver operating characteristic curve was 0.949, indicating that the diagnostic model could reliably distinguish DCM from non-DCM samples. In summary, our study identified 5 DEGs through integrated bioinformatic analysis and in vivo experiments, which could serve as potential targets for further comprehensive investigation.

SIRT1-Rab7 axis attenuates NLRP3 and STING activation through late endosomal-dependent mitophagy during sepsis-induced acute lung injury

BACKGROUND

Acute lung injury (ALI) is a leading cause of mortality in patients with sepsis due to proinflammatory endothelial changes and endothelial permeability defects. Mitochondrial dysfunction is recognized as a critical mediator in the pathogenesis of sepsis-induced ALI. Although mitophagy regulation of mitochondrial quality is well recognized, little is known about its role in lung ECs during sepsis-induced ALI. Sirtuin 1 (SIRT1) is a histone protein deacetylase involved in inflammation, mitophagy, and cellular senescence. Here, the authors show a type of late endosome-dependent mitophagy that inhibits NLRP3 and STING activation through SIRT1 signaling during sepsis-induced ALI.

METHODS

C57BL/6J male mice with or without administration of the SIRT1 inhibitor EX527 in the CLP model and lung ECs in vitro were developed to identify mitophagy mechanisms that underlie the cross-talk between SIRT1 signaling and sepsis-induced ALI.

RESULTS

SIRT1 deficient mice exhibited exacerbated sepsis-induced ALI. Knockdown of SIRT1 interfered with mitophagy through late endosome Rab7, leading to the accumulation of damaged mitochondria and inducing excessive mitochondrial reactive oxygen species (mtROS) generation and cytosolic release of mitochondrial DNA (mtDNA), which triggered NLRP3 inflammasome and the cytosolic nucleotide sensing pathways (STING) over-activation. Pharmacological inhibition of STING and NLRP3 i n vivo or genetic knockdown in vitro reversed SIRT1 deficiency mediated endothelial permeability defects and endothelial inflammation in sepsis-induced ALI. Moreover, activation of SIRT1 with SRT1720 in vivo or overexpression of SIRT1 in vitro protected against sepsis-induced ALI.

CONCLUSION

These findings suggest that SIRT1 signaling is essential for restricting STING and NLRP3 hyperactivation by promoting endosomal-mediated mitophagy in lung ECs, providing potential therapeutic targets for treating sepsis-induced ALI.

PLCE1 enhances mitochondrial dysfunction to promote GSDME-mediated pyroptosis in doxorubicin-induced cardiotoxicity

BACKGROUND

The therapeutic value and long-term application of doxorubicin (DOX) were hampered by its severe irreversible cardiotoxicity. Phospholipase C epsilon 1 (PLCE 1) was reported as a new member of the phospholipase C (PLC) family which controls the level of phosphoinositides in cells. Pyroptosis is a newly discovered inflammatory type of regulated cell death. Recent studies have consolidated that chemotherapeutic drugs lead to pyroptosis. Additionally, the phosphoinositide signaling system has remarkable effects on the execution of cell death. We aim to investigate the role of PLCE1 and the mechanism of pyroptosis from the context of DOX-induced cardiotoxicity.

METHODS

In the current study, in vitro and in vivo experiments were performed to dissect the underlying mechanism of cardiomyocyte pyroptosis during DOX-induced cardiac injury. The molecular mechanism of PLCE1 was identified by the human cardiomyocyte AC16 cell line and C57BL/6 mouse model.

RESULTS

The results here indicated that PLCE1 high expressed and pyroptotic cell death presented in cardiomyocytes after DOX application, which was negatively correlated to heart function. DOX-induced cell model disclosed pyroptosis mediated by Gasdermin E (GSDME) protein and involved in mitochondrial damage. Conversely, the deletion of PLCE1 ameliorated mitochondrial dysfunction by suppressing ROS accumulation and reversing mitochondrial membrane potential, and then increased cell viability effectively. More importantly, the in vivo experiment demonstrated that inhibition of PLCE1 reduced pyroptotic cell death and improved heart effect.

CONCLUSIONS

We discovered firstly that PLCE1 inhibition protected cardiomyocytes from DOX-induced pyroptotic injury and promoted cardiac function. This information offers a theoretical basis for promising therapy.

CIRC_0003907 MODULATES SEPSIS-INDUCED MYOCARDIAL INJURY VIA ENHANCING MYD88/NLRP3/NF-ΚB AXIS BY SPONGING MIR-944

ABSTRACT

Background : Sepsis-induced cardiomyopathy ( SIC ) is a common complication of sepsis with high morbidity and mortality but lacks specific therapy. The purpose of this study was to investigate the role of circularRNA_0003907 (circ_0003907) in myocardium injury induced by sepsis. Methods: In this experiment, human AC16 cells were treated with lipopolysaccharide (LPS) to induce an in vitro cardiomyocyte injury model. Expression of circ_0003907, microRNA-944 (miR-944), and MYD88 was detected using quantitative real-time polymerase chain reaction. Cell proliferation and apoptosis were assessed using 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide, thymidine analog 5-ethynyl-2'-deoxyuridine, and flow cytometry assays. Secretions of proinflammatory cytokines IL-6 and TNF-α were detected using ELISA kits. Superoxide dismutase (SOD) activity and malondialdehyde (MDA) level were detected using special kits. Protein levels of cyclin D1, cleaved caspase-3, MYD88, NLRP3, P65, and IκBα were determined using western blot assay. After being predicted using Circineractome and starBase, the interaction between miR-944 and circ_0003907 or MYD88 was confirmed using dual-luciferase reporter and RNA immunoprecipitation assays. Results: Circ_0003907 expression was increased in serum from SIC patients and in LPS-treated AC16 cells. Circ_0003907 knockdown might abolish LPS-triggered proliferation inhibition, and the promotion of apoptosis, inflammatory response, and oxidative stress in AC16 cells. In mechanism, circ_0003907 acted as a sponge for miR-944 to increase MYD88 expression. Meanwhile, the absence of circ_0003907 induced miR-944 expression and suppressed MYD88/NLRP3/NF-κB levels. Conclusion: Circ_0003907 sponged miR-944 to aggravate LPS-induced AC16 cell dysfunction via activating the MYD88/NLRP3/NF-κB axis during sepsis, which might provide a new direction for the treatment of SIC .

Uncovering hub genes and immunological characteristics for heart failure utilizing RRA, WGCNA and Machine learning

Background

Heart failure (HF) is a major public health issue with high mortality and morbidity. This study aimed to find potential diagnostic markers for HF by the combination of bioinformatics analysis and machine learning, as well as analyze the role of immune infiltration in the pathological process of HF.

Methods

The gene expression profiles of 124 HF patients and 135 nonfailing donors (NFDs) were obtained from six datasets in the NCBI Gene Expression Omnibus (GEO) public database. We applied robust rank aggregation (RRA) and weighted gene co-expression network analysis (WGCNA) method to identify critical genes in HF. To discover novel diagnostic markers in HF, three machine learning methods were employed, including best subset regression, regularization technique, and support vector machine-recursive feature elimination (SVM-RFE). Besides, immune infiltration was investigated in HF by single-sample gene set enrichment analysis (ssGSEA).

Results

Combining RRA with WGCNA method, we recognized 39 critical genes associated with HF. Through integrating three machine learning methods, FCN3 and SMOC2 were determined as novel diagnostic markers in HF. Differences in immune infiltration signature were also found between HF patients and NFDs. Moreover, we explored the potential associations between two diagnostic markers and immune response in the pathogenesis of HF.

Conclusions

In summary, FCN3 and SMOC2 can be used as diagnostic markers of HF, and immune infiltration plays an important role in the initiation and progression of HF.

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.

Integrative analysis of bioinformatics and machine learning to identify cuprotosis-related biomarkers and immunological characteristics in heart failure

Backgrounds

Cuprotosis is a newly discovered programmed cell death by modulating tricarboxylic acid cycle. Emerging evidence showed that cuprotosis-related genes (CRGs) are implicated in the occurrence and progression of multiple diseases. However, the mechanism of cuprotosis in heart failure (HF) has not been investigated yet.

Methods

The HF microarray datasets GSE16499, GSE26887, GSE42955, GSE57338, GSE76701, and GSE79962 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed CRGs between HF patients and nonfailing donors (NFDs). Four machine learning models were used to identify key CRGs features for HF diagnosis. The expression profiles of key CRGs were further validated in a merged GEO external validation dataset and human samples through quantitative reverse-transcription polymerase chain reaction (qRT-PCR). In addition, Gene Ontology (GO) function enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and immune infiltration analysis were used to investigate potential biological functions of key CRGs.

Results

We discovered nine differentially expressed CRGs in heart tissues from HF patients and NFDs. With the aid of four machine learning algorithms, we identified three indicators of cuprotosis (DLAT, SLC31A1, and DLST) in HF, which showed good diagnostic properties. In addition, their differential expression between HF patients and NFDs was confirmed through qRT-PCR. Moreover, the results of enrichment analyses and immune infiltration exhibited that these diagnostic markers of CRGs were strongly correlated to energy metabolism and immune activity.

Conclusions

Our study discovered that cuprotosis was strongly related to the pathogenesis of HF, probably by regulating energy metabolism-associated and immune-associated signaling pathways.

Proinflammatory cytokines driving cardiotoxicity in COVID-19

AIMS

Cardiac involvement is common in patients hospitalized with COVID-19 and correlates with an adverse disease trajectory. While cardiac injury has been attributed to direct viral cytotoxicity, serum-induced cardiotoxicity secondary to serological hyperinflammation constitutes a potentially amenable mechanism that remains largely unexplored.

METHODS AND RESULTS

To investigate serological drivers of cardiotoxicity in COVID-19 we have established a robust bioassay that assessed the effects of serum from COVID-19 confirmed patients on human embryonic stem cell (hESC)-derived cardiomyocytes. We demonstrate that serum from COVID-19 positive patients significantly reduced cardiomyocyte viability independent of viral transduction, an effect that was also seen in non-COVID-19 acute respiratory distress syndrome (ARDS). Serum from patients with greater disease severity led to worse cardiomyocyte viability and this significantly correlated with levels of key inflammatory cytokines, including IL-6, TNF-α, IL1-β, IL-10, CRP, and neutrophil to lymphocyte ratio with a specific reduction of CD4+ and CD8+ cells. Combinatorial blockade of IL-6 and TNF-α partly rescued the phenotype and preserved cardiomyocyte viability and function. Bulk RNA sequencing of serum-treated cardiomyocytes elucidated specific pathways involved in the COVID-19 response impacting cardiomyocyte viability, structure, and function. The observed effects of serum-induced cytotoxicity were cell-type selective as serum exposure did not adversely affect microvascular endothelial cell viability but resulted in endothelial activation and a procoagulant state.

CONCLUSION

These results provide direct evidence that inflammatory cytokines are at least in part responsible for the cardiovascular damage seen in COVID-19 and characterise the downstream activated pathways in human cardiomyocytes. The serum signature of patients with severe disease indicates possible targets for therapeutic intervention.

Circulating N-lactoyl-amino acids and N-formyl-methionine reflect mitochondrial dysfunction and predict mortality in septic shock

INTRODUCTION

Sepsis is a highly morbid condition characterized by multi-organ dysfunction resulting from dysregulated inflammation in response to acute infection. Mitochondrial dysfunction may contribute to sepsis pathogenesis, but quantifying mitochondrial dysfunction remains challenging.

OBJECTIVE

To assess the extent to which circulating markers of mitochondrial dysfunction are increased in septic shock, and their relationship to severity and mortality.

METHODS

We performed both full-scan and targeted (known markers of genetic mitochondrial disease) metabolomics on plasma to determine markers of mitochondrial dysfunction which distinguish subjects with septic shock (n = 42) from cardiogenic shock without infection (n = 19), bacteremia without sepsis (n = 18), and ambulatory controls (n = 19) - the latter three being conditions in which mitochondrial function, proxied by peripheral oxygen consumption, is presumed intact.

RESULTS

Nine metabolites were significantly increased in septic shock compared to all three comparator groups. This list includes N-formyl-L-methionine (f-Met), a marker of dysregulated mitochondrial protein translation, and N-lactoyl-phenylalanine (lac-Phe), representative of the N-lactoyl-amino acids (lac-AAs), which are elevated in plasma of patients with monogenic mitochondrial disease. Compared to lactate, the clinical biomarker used to define septic shock, there was greater separation between survivors and non-survivors of septic shock for both f-Met and the lac-AAs measured within 24 h of ICU admission. Additionally, tryptophan was the one metabolite significantly decreased in septic shock compared to all other groups, while its breakdown product kynurenate was one of the 9 significantly increased.

CONCLUSION

Future studies which validate the measurement of lac-AAs and f-Met in conjunction with lactate could define a sepsis subtype characterized by mitochondrial dysfunction.

Septic Cardiomyopathy

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis-induced myocardial dysfunction represents reversible myocardial dysfunction which ultimately results in left ventricular dilatation or both, with consequent loss of contractility. Studies on septic cardiomyopathy report a wide range of prevalence ranging from 10% to 70%. Myocardial damage occurs as a result of weakened myocardial circulation, direct myocardial depression, and mitochondrial dysfunction. Mitochondrial dysfunction is the leading problem in the development of septic cardiomyopathy and includes oxidative phosphorylation, production of reactive oxygen radicals, reprogramming of energy metabolism, and mitophagy. Echocardiography provides several possibilities for the diagnosis of septic cardiomyopathy. Systolic and diastolic dysfunction of left ventricular is present in 50-60% of patients with sepsis. Right ventricular dysfunction is present in 50-55% of cases, while isolated right ventricular dysfunction is present in 47% of cases. Left ventricle (LV) diastolic dysfunction is very common in septic shock, and it represents an early biomarker, it has prognostic significance. Right ventricular dysfunction associated with sepsis patients with worse early prognosis. Global longitudinal stress and magnetic resonance imaging (MRI) of the heart are sufficiently sensitive methods, but at the same time MRI of the heart is difficult to access in intensive care units, especially when dealing with critically ill patients. Previous research has identified two biomarkers as a result of the integrated mitochondrial response to stress, and these are fibroblast growth factor-21 (FGF-21) and growth differentiation factor-15 (GDF-15). Both of the mentioned biomarkers can be easily quantified in serum or plasma, but they are difficult to be specific in patients with multiple comorbidities. Mitochondrial dysfunction is also associated with reduced levels of miRNA (microRNA), some research showed significance of miRNA in sepsis-induced myocardial dysfunction, but further research is needed to determine the clinical significance of these molecules in septic cardiomyopathy. Therapeutic options in the treatment of septic cardiomyopathy are not specific, and include the optimization of hemodynamic parameters and the use of antibiotic thera-pies with targeted action. Future research aims to find mechanisms of targeted action on the initial mechanisms of the development of septic cardiomyopathy.

Key Cell Types and Biomarkers in Heart Failure Identified through Analysis of Single-Cell and Bulk RNA Sequencing Data

Heart failure (HF) is a complex clinical syndrome resulting from various cardiac diseases and a significant medical issue worldwide. Although the role of inflammation in HF pathogenesis is well-known, the specific cell types and regulatory molecules involved remain poorly understood. Here, we identified key cell types and novel biomarkers via an analysis of single-cell and bulk RNA sequencing data obtained from patients with two major HF types of ischemic cardiomyopathy and dilated cardiomyopathy. Myeloid cells were identified as the primary cell population involved in HF through cellular fraction and gene set enrichment analysis. Additionally, differential analysis of myeloid cells revealed crosstalk between cellular communication and cytokine-regulated immune responses in HF, with the MIF pathway emerging as a crucial immune regulatory pathway. The CD74/CXCR4 receptor complex in myeloid cell subgroup Mφ2 was significantly upregulated, potentially acting as a crucial regulator in HF. Upon receiving the MIF signal molecule, the CD74/CXCR4 receptor can activate NF-κB signaling to produce chemokines and thereby enhance the inflammatory response. CD74 and CXCR4 may serve as biomarkers and treatment targets for HF.

Extending the 'host response' paradigm from sepsis to cardiogenic shock: evidence, limitations and opportunities

Recent clinical and research efforts in cardiogenic shock (CS) have largely focussed on the restoration of the low cardiac output state that is the conditio sine qua non of the clinical syndrome. This approach has failed to translate into improved outcomes, and mortality has remained static at 30-50%. There is an unmet need to better delineate the pathobiology of CS to understand the observed heterogeneity of presentation and treatment effect and to identify novel therapeutic targets. Despite data in other critical illness syndromes, specifically sepsis, the role of dysregulated inflammation and immunity is hitherto poorly described in CS. High-dimensional molecular profiling, particularly through leukocyte transcriptomics, may afford opportunity to better characterise subgroups of patients with shared mechanisms of immune dysregulation. In this state-of-the-art review, we outline the rationale for considering molecular subtypes of CS. We describe how high-dimensional molecular technologies can be used to identify these subtypes, and whether they share biological features with sepsis and other critical illness states. Finally, we propose how the identification of molecular subtypes of patients may enrich future clinical trial design and identification of novel therapies for CS.

A bibliometric analysis of cardiomyocyte apoptosis from 2014 to 2023: A review

Cardiomyocyte apoptosis is an important factor in cardiac function decline observed in various cardiovascular diseases. To understand the progress in the field of cardiomyocyte apoptosis research, this paper uses bibliometrics to statistically analyze publications in this field. A total of 5939 articles were retrieved from the core Web of Science database, and then VOSviewer and Citespace were used to conduct a scientometric analysis of the authors, countries, institutions, references and keywords included in the articles to determine the cooperative relationships between researchers that study cardiomyocyte apoptosis. At present, the research hotspots in this field mainly include experimental research, molecular mechanisms, pathophysiology and cardiac regeneration of cardiomyocyte apoptosis-related diseases. NOD-like receptor thermal protein domain associated protein 3 inflammasome, circular RNA, and sepsis are the research frontiers in this field and are emerging as new areas of research focus. This work provides insight into research directions and the clinical application value for the continued advancement of cardiomyocyte apoptosis research.

Integrating scRNA-seq to explore novel macrophage infiltration-associated biomarkers for diagnosis of heart failure

OBJECTIVE

Inflammation and immune cells are closely intertwined mechanisms that contribute to the progression of heart failure (HF). Nonetheless, there is a paucity of information regarding the distinct features of dysregulated immune cells and efficient diagnostic biomarkers linked with HF. This study aims to explore diagnostic biomarkers related to immune cells in HF to gain new insights into the underlying molecular mechanisms of HF and to provide novel perspectives for the detection and treatment of HF.

METHOD

The CIBERSORT method was employed to quantify 22 types of immune cells in HF and normal subjects from publicly available GEO databases (GSE3586, GSE42955, GSE57338, and GSE79962). Machine learning methods were utilized to screen for important cell types. Single-cell RNA sequencing (GSE145154) was further utilized to identify important cell types and hub genes. WGCNA was employed to screen for immune cell-related genes and ultimately diagnostic models were constructed and evaluated. To validate these predictive results, blood samples were collected from 40 normal controls and 40 HF patients for RT-qPCR analysis. Lastly, key cell clusters were divided into high and low biomarker expression groups to identify transcription factors that may affect biomarkers.

RESULTS

The study found a noticeable difference in immune environment between HF and normal subjects. Macrophages were identified as key immune cells by machine learning. Single-cell analysis further showed that macrophages differed dramatically between HF and normal subjects. This study revealed the existence of five subsets of macrophages that have different differentiation states. Based on module genes most relevant to macrophages, macrophage differentiation-related genes (MDRGs), and DEGs in HF and normal subjects from GEO datasets, four genes (CD163, RNASE2, LYVE1, and VSIG4) were identified as valid diagnostic markers for HF. Ultimately, a diagnostic model containing two hub genes was constructed and then validated with a validation dataset and clinical samples. In addition, key transcription factors driving or maintaining the biomarkers expression programs were identified.

CONCLUSION

The analytical results and diagnostic model of this study can assist clinicians in identifying high-risk individuals, thereby aiding in guiding treatment decisions for patients with HF.

Abnormal expression of PRKAG2-AS results in dysfunction of cardiomyocytes through regulating PRKAG2 transcription by interacting with PPARG

The role of PRKAG2 in the maintenance of heart function is well established, but little is known about how PRKAG2 is regulated in cardiomyocytes. In this study, we investigated the role of the lncRNA PRKAG2-AS, which is present at the PRKAG2 promoter, in the regulation of PRKAG2 expression. PRKAG2-AS expression was predominantly nuclear, as determined by RNA nucleoplasmic separation and fluorescence in situ hybridization. Knockdown of PRKAG2-AS in the nucleus, but not the cytoplasm, significantly decreased the expression of PRKAG2b and PRKAG2d. Interestingly, we found that PRKAG2-AS and its target genes, PRKAG2b and PRKAG2d, were reduced in the hearts of patients with ischemic cardiomyopathy, suggesting a potential role for PRKAG2-AS in myocardial ischemia. Indeed, knockdown of PRKAG2-AS in the nucleus resulted in apoptosis of cardiomyocytes. We further elucidated the mechanism by which PRKAG2-AS regulates PRKAG2 transcription by identifying 58 PRKAG2-AS interacting proteins. Among them, PPARG was selected for further investigation based on its correlation and potential interaction with PRKAG2-AS in regulating transcription. Overexpression of PPARG, or its activation with rosiglitazone, led to a significant increase in the expression of PRKAG2b and PRKAG2d in cardiomyocytes, which could be attenuated by PRKAG2-AS knockdown. This finding suggests that PRKAG2-AS mediates, at least partially, the protective effects of rosiglitazone on hypoxia-induced apoptosis. However, given the risk of rosiglitazone in heart failure, we also examined the involvement of PRKAG2-AS in this condition and found that PRKAG2-AS, as well as PRKAG2b and PRKAG2d, was elevated in hearts with dilated cardiomyopathy (DCM) and that overexpression of PRKAG2-AS led to a significant increase in PRKAG2b and PRKAG2d expression, indicating that up-regulation of PRKAG2-AS may contribute to the mechanism of heart failure by promoting transcription of PRKAG2. Consequently, proper expression of PRKAG2-AS is essential for maintaining cardiomyocyte function, and aberrant PRKAG2-AS expression induced by hypoxia or other stimuli may cause cardiac dysfunction.

Decoding molecular signature on heart of septic mice with distinct left ventricular ejection fraction

Dysregulated cardiac function after sepsis in intensive care unit is known to predict poor long-term outcome and increase mortality. Their pathological feature and molecular mechanism remain unclear. We observed that septic patients with depressed left ventricular ejection fraction (LVEF) have the highest in-hospital and 28 days mortality comparing to patients with hyperdynamic LVEF or with heart failure with preserved LVEF. Echocardiograms reveal that survivors post cecum ligation and puncture (CLP) on rodents have stable LVEF and non-survivors have fluctuated LVEF at CLP early phase. CLP-induced mice fall into three groups based on LVEF 24 h post-surgery: high-, low-, and normal-LVEF. Transcriptomic and proteomic analyses identify jointly and distinctively changed genes, proteins and biologically essential pathways in left ventricles from three CLP groups. Notably, transmission electron microscopy shows different mitochondrial and sarcomere defects associated with LVEF variances. Together, this study systematically characterizes the molecular, morphological, and functional alterations in CLP-induced cardiac injury.

Melatonin as a potential treatment for septic cardiomyopathy

Septic cardiomyopathy (SCM) is a common complication of sepsis contributing to high mortality rates. Its pathophysiology involves complex factors, including inflammatory cytokines, mitochondrial dysfunction, oxidative stress, and immune dysregulation. Despite extensive research, no effective pharmacological agent has been established for sepsis-induced cardiomyopathy. Melatonin, a hormone with diverse functions in the body, has emerged as a potential agent for SCM through its anti-oxidant, anti-inflammatory, anti-apoptotic, and cardioprotective roles. Through various molecular levels of its mechanism of action, it counterattacks the adverse event of sepsis. Experimental studies have mentioned that melatonin protects against many cardiovascular diseases and exerts preventive effects on SCM. Moreover, melatonin has been investigated in combination with other drugs such as antibiotics, resveratrol, and anti-oxidants showing synergistic effects in reducing inflammation, anti-oxidant, and improving cardiac function. While preclinical studies have demonstrated positive results, clinical trials are required to establish the optimal dosage, route of administration, and treatment duration for melatonin in SCM. Its safety profile, low toxicity, and natural occurrence in the human body provide a favorable basis for its clinical use. This review aims to provide an overview of the current evidence of the use of melatonin in sepsis-induced cardiomyopathy (SICM). Melatonin appears to be promising as a possible treatment for sepsis-induced cardiomyopathy and demands further investigation.

Knockdown of histone deacetylase 9 attenuates sepsis-induced myocardial injury and inflammatory response

Myocardial cell damage is associated with apoptosis and excessive inflammatory response in sepsis. Histone deacetylases (HDACs) are implicated in the progression of heart diseases. This study aims to explore the role of histone deacetylase 9 (HDAC9) in sepsis-induced myocardial injury. Lipopolysaccharide (LPS)-induced Sprague Dawley rats and cardiomyocyte line H9C2 were used as models in vivo and in vitro. The results showed that HDAC9 was significantly upregulated after LPS stimulation, and HDAC9 knockdown remarkably improved cardiac function, as evidenced by decreased left ventricular internal diameter end diastole (LVEDD) and left ventricular internal diameter end systole (LVESD), and increased fractional shortening (FS)% and ejection fraction (EF)%. In addition, HDAC9 silencing alleviated release of inflammatory cytokines (tumor necrosis factor-α (TNF-α), IL-6 and IL-1β) and cardiomyocyte apoptosis in vivo and in vitro. Furthermore, HDAC9 inhibition was proved to suppress nuclear factor-kappa B (NF-κB) activation with reducing the levels of p-IκBα and p-p65, and p65 nuclear translocation. Additionally, interaction between miR-214-3p and HDAC9 was determined through bioinformatics analysis, RT-qPCR, western blot and dual luciferase reporter assay. Our data revealed that miR-214-3p directly targeted the 3'UTR of HDAC9. Our findings demonstrate that HDAC9 suppression ameliorates LPS-induced cardiac dysfunction by inhibiting the NF-κB signaling pathway and presents a promising therapeutic agent for the treatment of LPS-stimulated myocardial injury.

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.

Landscape of co-expressed genes between the myocardium and blood in sepsis and ceRNA network construction: a bioinformatic approach

Septic cardiomyopathy is a serious complication of sepsis. The mechanism of disease pathogenesis, which is caused by infection, is well researched. Despite ongoing efforts, there are no viable biological markers in the peripheral blood for early detection and diagnosis of septic cardiomyopathy. We aimed to uncover potential biomarkers of septic cardiomyopathy by comparing the covaried genes and pathways in the blood and myocardium of sepsis patients. Gene expression profiling of GSE79962, GSE65682, GSE54514, and GSE134364 was retrieved from the GEO database. Student's t-test was used for differential expression analysis. K-means clustering analysis was applied for subgroup identification. Least absolute shrinkage and selection operator (LASSO) and logistic regression were utilized for screening characteristic genes and model construction. Receiver operating characteristic (ROC) curves were generated for estimating the diagnostic efficacy. For ceRNA information prediction, miWalk and lncBase were applied. Cytoscape was used for ceRNA network construction. Inflammation-associated genes were upregulated, while genes related to mitochondria and aerobic metabolism were downregulated in both blood and the myocardium. Three groups with a significantly different mortality were identified by these covaried genes, using clustering analysis. Five characteristic genes-BCL2A1, CD44, ADGRG1, TGIF1, and ING3-were identified, which enabled the prediction of mortality of sepsis. The pathophysiological changes in the myocardium of patients with sepsis were also reflected in peripheral blood to some extent. The co-occurring pathological processes can affect the prognosis of sepsis. Thus, the genes we identified have the potential to become biomarkers for septic cardiomyopathy.

Identification of Signature Genes of Dilated Cardiomyopathy Using Integrated Bioinformatics Analysis

Dilated cardiomyopathy (DCM) is characterized by left ventricular or biventricular enlargement with systolic dysfunction. To date, the underlying molecular mechanisms of dilated cardiomyopathy pathogenesis have not been fully elucidated, although some insights have been presented. In this study, we combined public database resources and a doxorubicin-induced DCM mouse model to explore the significant genes of DCM in full depth. We first retrieved six DCM-related microarray datasets from the GEO database using several keywords. Then we used the "LIMMA" (linear model for microarray data) R package to filter each microarray for differentially expressed genes (DEGs). Robust rank aggregation (RRA), an extremely robust rank aggregation method based on sequential statistics, was then used to integrate the results of the six microarray datasets to filter out the reliable differential genes. To further improve the reliability of our results, we established a doxorubicin-induced DCM model in C57BL/6N mice, using the "DESeq2" software package to identify DEGs in the sequencing data. We cross-validated the results of RRA analysis with those of animal experiments by taking intersections and identified three key differential genes (including BEX1, RGCC and VSIG4) associated with DCM as well as many important biological processes (extracellular matrix organisation, extracellular structural organisation, sulphur compound binding, and extracellular matrix structural components) and a signalling pathway (HIF-1 signalling pathway). In addition, we confirmed the significant effect of these three genes in DCM using binary logistic regression analysis. These findings will help us to better understand the pathogenesis of DCM and may be key targets for future clinical management.

Rosmarinic acid protects against lipopolysaccharide-induced cardiac dysfunction via activating Sirt1/PGC-1α pathway to alleviate mitochondrial impairment

Sepsis-induced cardiomyopathy is a decisive factor that plays a critical role in the high mortality of septic patients in the critically ill. Mitochondrial dysfunction occurring during sepsis is a vital contributor to the pathogenesis of myocardial damage. Rosmarinic acid (RA), a natural poly-phenolic compound, has showed cardio-protective and mitochondrial protective effect. The present study was aimed to investigate the effect of RA on sepsis-induced cardiomyopathy. Adult mice were subjected to intraperitoneal injection of saline (control) or lipopolysaccharide (LPS, 5 mg/kg) to mimic sepsis-induced cardiomyopathy. Immediately after LPS challenge, vehicle or RA (100 mg/kg/day) was administrated via gavage. Cardiac function was examined with echocardiographic analyses 12 hours after LPS challenge and cumulative survival of mice was recorded for 8 days. Heart tissues were harvested 12 hours after LPS challenge to perform histological analyses and determine mitochondrial function. We found RA significantly improved cardiac function and survival of LPS-injected mice. Histologically, RA attenuated LPS-mediated cardiomyocyte damage, indicated by decreased cardiomyocyte apoptosis and improved myocardial swollen and disarrangement. Moreover, RA attenuated LPS-mediated myocardial mitochondrial dysfunction, indicated by improved mitochondrial ultrastructure, increased mitochondrial membrane potential (MMP), synthesis of adenosine triphosphate (ATP), markedly decreased reactive oxygen species (ROS) level and alleviated oxidative stress in heart tissues. RA treatment downregulated protein expression of Sirt1 and peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α), and Sirt1 inhibition blocked protective effect of RA on LPS-induced myocardial damage and mitochondrial dysfunction. Collectively, RA attenuates LPS-induced cardiac dysfunction via activating Sirt1/PGC-1α pathway to alleviate mitochondrial impairment. It may be a promising cardio-protective drug to be used for septic patients.

Identification of m7G regulator-mediated RNA methylation modification patterns and related immune microenvironment regulation characteristics in heart failure

BACKGROUND

N⁷-methylguanosine (m⁷G) modification has been reported to regulate RNA expression in multiple pathophysiological processes. However, little is known about its role and association with immune microenvironment in heart failure (HF).

RESULTS

One hundred twenty-four HF patients and 135 nonfailing donors (NFDs) from six microarray datasets in the gene expression omnibus (GEO) database were included to evaluate the expression profiles of m⁷G regulators. Results revealed that 14 m⁷G regulators were differentially expressed in heart tissues from HF patients and NFDs. Furthermore, a five-gene m⁷G regulator diagnostic signature, NUDT16, NUDT4, CYFIP1, LARP1, and DCP2, which can easily distinguish HF patients and NFDs, was established by cross-combination of three machine learning methods, including best subset regression, regularization techniques, and random forest algorithm. The diagnostic value of five-gene m⁷G regulator signature was further validated in human samples through quantitative reverse-transcription polymerase chain reaction (qRT-PCR). In addition, consensus clustering algorithms were used to categorize HF patients into distinct molecular subtypes. We identified two distinct m⁷G subtypes of HF with unique m⁷G modification pattern, functional enrichment, and immune characteristics. Additionally, two gene subgroups based on m⁷G subtype-related genes were further discovered. Single-sample gene-set enrichment analysis (ssGSEA) was utilized to assess the alterations of immune microenvironment. Finally, utilizing protein-protein interaction network and weighted gene co-expression network analysis (WGCNA), we identified UQCRC1, NDUFB6, and NDUFA13 as m⁷G methylation-associated hub genes with significant clinical relevance to cardiac functions.

CONCLUSIONS

Our study discovered for the first time that m⁷G RNA modification and immune microenvironment are closely correlated in HF development. A five-gene m⁷G regulator diagnostic signature for HF (NUDT16, NUDT4, CYFIP1, LARP1, and DCP2) and three m⁷G methylation-associated hub genes (UQCRC1, NDUFB6, and NDUFA13) were identified, providing new insights into the underlying mechanisms and effective treatments of HF.

Integrated genomic analysis defines molecular subgroups in dilated cardiomyopathy and identifies novel biomarkers based on machine learning methods

Aim: As the most common cardiomyopathy, dilated cardiomyopathy (DCM) often leads to progressive heart failure and sudden cardiac death. This study was designed to investigate the molecular subgroups of DCM. Methods: Three datasets of DCM were downloaded from GEO database (GSE17800, GSE79962 and GSE3585). After log2-transformation and background correction with "limma" package in R software, the three datasets were merged into a metadata cohort. The consensus clustering was conducted by the "Consensus Cluster Plus" package to uncover the molecular subgroups of DCM. Moreover, clinical characteristics of different molecular subgroups were compared in detail. We also adopted Weighted gene co-expression network analysis (WGCNA) analysis based on subgroup-specific signatures of gene expression profiles to further explore the specific gene modules of each molecular subgroup and its biological function. Two machine learning methods of LASSO regression algorithm and SVM-RFE algorithm was used to screen out the genetic biomarkers, of which the discriminative ability of molecular subgroups was evaluated by receiver operating characteristic (ROC) curve. Results: Based on the gene expression profiles, heart tissue samples from patients with DCM were clustered into three molecular subgroups. No statistical difference was found in age, body mass index (BMI) and left ventricular internal diameter at end-diastole (LVIDD) among three molecular subgroups. However, the results of left ventricular ejection fraction (LVEF) statistics showed that patients from subgroup 2 had a worse condition than the other group. We found that some of the gene modules (pink, black and grey) in WGCNA analysis were significantly related to cardiac function, and each molecular subgroup had its specific gene modules functions in modulating occurrence and progression of DCM. LASSO regression algorithm and SVM-RFE algorithm was used to further screen out genetic biomarkers of molecular subgroup 2, including TCEAL4, ISG15, RWDD1, ALG5, MRPL20, JTB and LITAF. The results of ROC curves showed that all of the genetic biomarkers had favorable discriminative effectiveness. Conclusion: Patients from different molecular subgroups have their unique gene expression patterns and different clinical characteristics. More personalized treatment under the guidance of gene expression patterns should be realized.

Identification of iron metabolism-related genes in the circulation and myocardium of patients with sepsis via applied bioinformatics analysis

Background

Early diagnosis of septic cardiomyopathy is essential to reduce the mortality rate of sepsis. Previous studies indicated that iron metabolism plays a vital role in sepsis-induced cardiomyopathy. Here, we aimed to identify shared iron metabolism-related genes (IMRGs) in the myocardium and blood monocytes of patients with sepsis and to determine their prognostic signature.

Methods

First, an applied bioinformatics-based analysis was conducted to identify shared IMRGs differentially expressed in the myocardium and peripheral blood monocytes of patients with sepsis. Second, Cytoscape was used to construct a protein-protein interaction network, and immune infiltration of the septic myocardium was assessed using single-sample gene set enrichment analysis. In addition, a prognostic prediction model for IMRGs was established by Cox regression analysis. Finally, the expression of key mRNAs in the myocardium of mice with sepsis was verified using quantitative polymerase chain reaction analysis.

Results

We screened common differentially expressed genes in septic myocardium and blood monocytes and identified 14 that were related to iron metabolism. We found that HBB, SLC25A37, SLC11A1, and HMOX1 strongly correlated with monocytes and neutrophils, whereas HMOX1 and SLC11A1 strongly correlated with macrophages. We then established a prognostic model (HIF1A and SLC25A37) using the common differentially expressed IMRGs. The prognostic model we established was expected to better aid in diagnosing septic cardiomyopathy. Moreover, we verified these genes using datasets and experiments and found a significant difference between the sepsis and control groups.

Conclusion

Common differential expression of IMRGs was identified in blood monocytes and myocardium between sepsis and control groups, among which HIF1A and SLC25A37 might predict prognosis in septic cardiomyopathy. The study may help us deeply understand the molecular mechanisms of iron metabolism and aid in the diagnosis and treatment of septic cardiomyopathy.

A brief morning rest period benefits cardiac repair in pressure overload hypertrophy and postmyocardial infarction

Rest has long been considered beneficial to patient healing; however, remarkably, there are no evidence-based experimental models determining how it benefits disease outcomes. Here, we created an experimental rest model in mice that briefly extends the morning rest period. We found in 2 major cardiovascular disease conditions (cardiac hypertrophy, myocardial infarction) that imposing a short, extended period of morning rest each day limited cardiac remodeling compared with controls. Mechanistically, rest mitigates autonomic-mediated hemodynamic stress on the cardiovascular system, relaxes myofilament contractility, and attenuates cardiac remodeling genes, consistent with the benefits on cardiac structure and function. These same rest-responsive gene pathways underlie the pathophysiology of many major human cardiovascular conditions, as demonstrated by interrogating open-source transcriptomic data; thus, patients with other conditions may also benefit from a morning rest period in a similar manner. Our findings implicate rest as a key driver of physiology, creating a potentially new field - as broad and important as diet, sleep, or exercise - and provide a strong rationale for investigation of rest-based therapy for major clinical diseases.

Identification of hub genes and transcription factor regulatory network for heart failure using RNA-seq data and robust rank aggregation analysis

Background

Heart failure (HF) is the end stage of various cardiovascular diseases with a high mortality rate. Novel diagnostic and therapeutic biomarkers for HF are urgently required. Our research aims to identify HF-related hub genes and regulatory networks using bioinformatics and validation assays.

Methods

Using four RNA-seq datasets in the Gene Expression Omnibus (GEO) database, we screened differentially expressed genes (DEGs) of HF using Removal of Unwanted Variation from RNA-seq data (RUVSeq) and the robust rank aggregation (RRA) method. Then, hub genes were recognized using the STRING database and Cytoscape software with cytoHubba plug-in. Furthermore, reliable hub genes were validated by the GEO microarray datasets and quantitative reverse transcription polymerase chain reaction (qRT-PCR) using heart tissues from patients with HF and non-failing donors (NFDs). In addition, R packages “clusterProfiler” and “GSVA” were utilized for enrichment analysis. Moreover, the transcription factor (TF)–DEG regulatory network was constructed by Cytoscape and verified in a microarray dataset.

Results

A total of 201 robust DEGs were identified in patients with HF and NFDs. STRING and Cytoscape analysis recognized six hub genes, among which ASPN, COL1A1, and FMOD were confirmed as reliable hub genes through microarray datasets and qRT-PCR validation. Functional analysis showed that the DEGs and hub genes were enriched in T-cell-mediated immune response and myocardial glucose metabolism, which were closely associated with myocardial fibrosis. In addition, the TF–DEG regulatory network was constructed, and 13 significant TF–DEG pairs were finally identified.

Conclusion

Our study integrated different RNA-seq datasets using RUVSeq and the RRA method and identified ASPN, COL1A1, and FMOD as potential diagnostic biomarkers for HF. The results provide new insights into the underlying mechanisms and effective treatments of HF.

Septic Cardiomyopathy: From Pathophysiology to the Clinical Setting

The onset of cardiomyopathy is a common feature in sepsis, with relevant effects on its pathophysiology and clinical care. Septic cardiomyopathy is characterized by reduced left ventricular (LV) contractility eventually associated with LV dilatation with or without right ventricle failure. Unfortunately, such a wide range of ultrasonographic findings does not reflect a deep comprehension of sepsis-induced cardiomyopathy, but rather a lack of consensus about its definition. Several echocardiographic parameters intrinsically depend on loading conditions (both preload and afterload) so that it may be challenging to discriminate which is primitive and which is induced by hemodynamic perturbances. Here, we explore the state of the art in sepsis-related cardiomyopathy. We focus on the shortcomings in its definition and point out how cardiac performance dynamically changes in response to different hemodynamic clusters. A special attention is also given to update the knowledge about molecular mechanisms leading to myocardial dysfunction and that recall those of myocardial hibernation. Ultimately, the aim of this review is to highlight the unsolved issue in the field of sepsis-induced cardiomyopathy as their implementation would lead to improve risk stratification and clinical care.

Exploration of the Shared Gene Signatures between Myocardium and Blood in Sepsis: Evidence from Bioinformatics Analysis

Background

Septic cardiomyopathy is widespread during sepsis and has adverse effects on mortality. Diagnosis of septic cardiomyopathy now mainly depends on transthoracic echocardiogram. Although some laboratory tests such as troponin T and atrial brain natriuretic peptide play a role in the diagnosis, specific blood biochemistry biomarkers are still lacking. Objective and Methods. In our study, we sought to find potential biological markers from genes and pathways that are covariant in the blood and myocardium of septic patients. Bioinformatics and machine learning methods were applied to achieve our goal. Datasets of myocardium and peripheral blood of patients with sepsis were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were selected and received functional enrichment analysis. Unsupervised hierarchical clustering analysis was performed to identify the subtypes of sepsis. Random forest, lasso regression, and logistic regression were used for variable screening and model construction. Internal and external validation sets were applied to verify the efficiency of the model in classifying disease and predicting mortality.

Results

By defining significance for genes using Student's t-test, we obtained 1,049 genes commonly changed in both myocardium and blood of patients with sepsis. The upregulated genes (LogFC >0) were related to inflammation pathways, and downregulated (LogFC <0) genes were related to mitochondrial and aerobic metabolism. We divided 468 sepsis patients into two groups with different clinical result based on the mortality-related commonly changed genes (104 genes), using unsupervised hierarchical clustering analysis. In our validation datasets, a six-gene model (SMU1, CLIC3, SP100, ARHGAP25, DECR1, and TNS3) was obtained and proven to perform well in classifying groups and predicting mortality.

Conclusion

We have identified genes that have the potential to become biomarkers for septic cardiomyopathy. Additionally, the pathophysiological changes in the myocardium of patients with sepsis were also reflected in peripheral blood to some extent. The co-occurring pathological processes can affect the prognosis of sepsis.

MicroRNAs Promote the Progression of Sepsis-Induced Cardiomyopathy and Neurovascular Dysfunction Through Upregulation of NF-kappaB Signaling Pathway-Associated HDAC7/ACTN4

Introduction

The objective of this study was to determine the NF-kappaB pathway, hub genes, and transcription factors (TFs) in monocytes implicated in the progression of neurovascular-related sepsis-induced cardiomyopathy (SIC) as well as potential miRNAs with regulatory functions.

Methods

: Sepsis-induced cardiomyopathy—and heart failure (HF)-related differentially expressed genes (DEGs) between SIC and HF groups were identified separately by differential analysis. In addition, DEGs and differentially expressed miRNAs (DEmiRNAs) in monocytes between sepsis and the HC group were identified. Then, common DEGs in SIC, HF, and monocyte groups were identified by intersection analysis. Based on the functional pathways enriched by these DEGs, genes related to the NF-kB-inducing kinase (NIK)/NF-kappaB signaling pathway were selected for further intersection analysis to obtain hub genes. These common DEGs, together with sepsis-related DEmiRNAs, were used to construct a molecular interplay network and to identify core TFs in the network.

Results

: A total of 153 upregulated genes and 25 downregulated genes were obtained from SIC-, HF-, and monocyte-related DEGs. Functional pathway analysis revealed that the upregulated genes were enriched in NF-κB signaling pathway. A total of eight genes associated with NF-κB signaling pathway were then further identified from the 178 DEGs. In combination with sepsis-related DEmiRNAs, HDAC7/ACTN4 was identified as a key transcriptional regulatory pair in the progression of SIC and in monocyte regulation. hsa-miR-23a-3p, hsa-miR-3175, and hsa-miR-23b-3p can regulate the progression of SIC through the regulation of HDAC7/ACTN4. Finally, gene set enrichment analysis (GSEA) suggested that HDAC7/ACTN4 may be associated with apoptosis in addition to the inflammatory response.

Conclusion

: hsa-miR-23a-3p, hsa-miR-3175, and hsa-miR-23b-3p are involved in SIC progression by regulating NF-κB signaling signaling pathway-related HDAC7/ACTN4 in monocytes and cardiac tissue cells. These mechanisms may contribute to sepsis-induced neurovascular damage.

Female hormones prevent sepsis-induced cardiac dysfunction: an experimental randomized study

Although epidemiologic research has demonstrated significant differences in incidence and outcomes of sepsis according to sex, their underlying biological mechanisms are poorly understood. Here, we studied the influence of hormonal status by comparing in vivo cardiac performances measured by MRI in non-ovariectomized and ovariectomized septic female rats. Control and ovariectomized rats were randomly allocated to the following groups: sham, sepsis and sepsis plus landiolol. Sepsis was induced by caecum ligation and punction (CLP). Landiolol, a short-acting selective β1-adrenergic blocker improving the in vivo cardiac performance of septic male rats was perfused continuously after sepsis induction. Cardiac MRI was carried out 18 h after induction of sepsis to assess in vivo cardiac function. Capillary permeability was evaluated by Evans Blue administration and measurement of its tissue extravasation. Variation in myocardial gene and protein expression was also assessed by qPCR and western-blot in the left ventricular tissue. Sepsis reduced indexed stroke volume, cardiac index and indexed end-diastolic volume compared to sham group in ovariectomized females whereas it had no effect in control females. This was associated with an overexpression of JAK2 expression and STAT3 phosphorylation on Ser727 site, and an inhibition of the adrenergic pathways in OVR females. Landiolol increased the indexed stroke volume by reversing the indexed end-diastolic volume reduction after sepsis in ovariectomized females, while it decreased indexed stroke volume and cardiac index in control. This was supported by an overexpression of genes involved in calcium influx in OVR females while an inactivation of the β-adrenergic and a calcium efflux pathway was observed in control females. Sepsis decreased in vivo cardiac performances in ovariectomized females but not in control females, presumably associated with a more pronounced inflammation, inhibition of the adrenergic pathway and calcium efflux defects. Administration of landiolol prevents this cardiac dysfunction in ovariectomized females with a probable activation of calcium influx, while it has deleterious effects in control females in which calcium efflux pathways were down-regulated.

Exploring the Communal Pathogenesis, Ferroptosis Mechanism, and Potential Therapeutic Targets of Dilated Cardiomyopathy and Hypertrophic Cardiomyopathy via a Microarray Data Analysis

Background

Cardiomyopathies are a heterogeneous group of heart diseases that can gradually cause severe heart failure. In particular, dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) are the two main types of cardiomyopathies, yet the independent and communal biological mechanisms of both remain far from elucidated. Meanwhile, ferroptosis is a non-apoptotic form of cell death that has been proven to be associated with cardiomyopathies, but the concrete nature of the interaction remains unclear. Hence, this study explored the pathogenesis and ferroptosis mechanism of HCM and DCM via a bioinformatics analysis.

Methods

Six datasets were downloaded from the Gene Expression Omnibus (GEO) database based on the study inclusion/exclusion criteria. After screening the differentially expressed genes (DEGs) and hub genes of HCM and DCM, subsequent analyses, including functional annotation, co-expression, validation, and transcription factors (TF)–mRNA–microRNA (miRNA) regulatory network construction, were performed. In addition, ferroptosis-related DEGs were also identified and verified in HCM and DCM.

Results

We found 171 independent DEGs of HCM mainly enriched in the regulation of ERK1 and ERK2 cascade, while 171 independent DEGs of DCM were significantly involved in cell adhesion. Meanwhile, 32 communal DEGs (26 upregulated genes and 6 downregulated genes) and 3 hub genes [periostin (POSTN), insulin-like growth factor-binding protein-5 (IGFBP5), and fibromodulin (FMOD)] were determined to be shared between HCM and DCM and the functional annotation of these genes highlighted the important position of growth hormone in HCM and DCM. Moreover, we identified activating transcription factor 3 (ATF3), lysophosphatidylcholine acyltransferase 3 (LPCAT3), and solute carrier family 1 member 5 (SLC1A5) as ferroptosis-related genes in HCM and STAT3 as a ferroptosis-related gene in DCM.

Conclusion

The identified independent and communal DEGs contribute to uncover a potentially distinct and common mechanism of HCM and DCM and ferroptosis-related genes could provide us with a novel direction for exploration. In addition, 3 hub genes could be potential biomarkers or therapeutic targets in patients with cardiomyopathy.

Systematic analysis of myocardial immune progression in septic cardiomyopathy: Immune-related mechanisms in septic cardiomyopathy

Background

The immune infiltration and molecular mechanisms underlying septic cardiomyopathy (SC) have not been completely elucidated. This study aimed to identify key genes related to SC and elucidate the potential molecular mechanisms.

Methods

The weighted correlation network analysis (WGCNA), linear models for microarray analysis (LIMMA), protein-protein interaction (PPI) network, CIBERSORT, Kyoto Encyclopedia of Genes and Genomes pathway (KEGG), and gene set enrichment analysis (GSEA) were applied to assess the key pathway and hub genes involved in SC.

Results

We identified 10 hub genes, namely, LRG1, LCN2, PTX3, E LANE, TCN1, CLEC4D, FPR2, MCEMP1, CEACAM8, and CD177. Furthermore, we used GSEA for all genes and online tools to explore the function of the hub genes. Finally, we took the intersection between differential expression genes (DEGs) and hub genes to identify LCN2 and PTX3 as key genes. We found that immune-related pathways played vital roles in SC. LCN2 and PTX3 were key genes in SC progression, which mainly showed an anti-inflammatory effect. The significant immune cells in cardiomyocytes of SC were neutrophils and M2 macrophages.

Conclusion

These cells may have the potential to be prognostic and therapeutic targets in the clinical management of SC. Excessive anti-inflammatory function and neutrophil infiltration are probably the primary causes of SC.

Identification of the distinctive role of DPT in dilated cardiomyopathy: a study based on bulk and single-cell transcriptomic analysis

Background

Dilated cardiomyopathy (DCM) is a common cause of heart failure. Cardiac remodeling is the main pathological change in DCM, yet the molecular mechanism is still unclear. Therefore, the present study aims to find potential crucial genes and regulators through bulk and single-cell transcriptomic analysis.

Methods

Three microarray datasets of DCM (GSE57338, GSE42955, GSE79962) were chosen from gene expression omnibus (GEO) to analyze the differentially expressed genes (DEGs). LASSO regression, SVM-RFE, and PPI network methods were then carried out to identify key genes. Another dataset (GSE116250) was used to validate these findings. To further identify DCM-associated specific cell types, transcription factors, and cell-cell interaction networks, GSEA, SCENIC, and CellPhoneDB were conducted on public datasets for single-cell RNA sequencing analysis of DCM (GSE109816 and GSE121893). Finally, reverse transcription-polymerase chain reaction (RT-PCR), western blot, and immunohistochemical were performed to validate DPT expression in fibroblasts and DCM.

Results

There were 281 DEGs between DCM and non-failing donors. CCL5 and DPT were identified to be key genes and both genes had a 0.844 area under the receiver operating curve (AUC) in the validation dataset. Further single-cell sequencing analysis revealed three main findings: (I) DPT was mainly expressed in fibroblasts and was significantly upregulated in DCM fibroblasts; (II) DPT⁺ fibroblasts were involved in the organization of the extracellular matrix (ECM) and collagen fibrils and were regulated by the transcription factor STAT3; and (III) DPT⁺ fibroblasts had high interactions with endothelial cells through including Ephrin-Eph, ACKR-CXCL, and JAG-NOTCH signal pathways. RT-PCR, western blot, and immunohistochemical confirmed that DPT was highly expressed and co-localized with Vimentin and p-STAT3 in DCM patients. STAT3 inhibitor S3I-201 reduced the expression of DPT in mouse cardiac fibroblasts.

Conclusions

DPT could be used as a diagnostic marker and therapeutic target of DCM. DPT⁺ fibroblasts could be a novel regulator of the cardiac remodeling process in DCM.

Genome-wide analysis of the mouse LIM gene family reveals its roles in regulating pathological cardiac hypertrophy

LIM-domain proteins have been shown to be associated with heart development and diseases. Systematic studies of LIM family members at the genome-wide level, which are crucial to further understand their functions in cardiac hypertrophy, are currently lacking. Here, 70 LIM genes were identified and characterised in mice. The expression patterns of LIM genes differ greatly during cardiac development and in the case of hypertrophy. Both Crip2 and Xirp2 are differentially expressed in cardiac hypertrophy and during heart failure. In addition, the hypertrophic state of cardiomyocytes is controlled by the relative expression levels of Crip2 and Xirp2. This study provides a foundation for further understanding of the special roles of LIM proteins in mammalian cardiac development and hypertrophy.

Immune System Disequilibrium-Neutrophils, Their Extracellular Traps, and COVID-19-Induced Sepsis

Equilibrium within the immune system can often determine the fate of its host. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease 2019 (COVID-19) pandemic. Immune dysregulation remains one of the main pathophysiological components of SARS-CoV-2-associated organ injury, with over-activation of the innate immune system, and induced apoptosis of adaptive immune cells. Here, we provide an overview of the innate immune system, both in general and relating to COVID-19. We specifically discuss "NETosis," the process of neutrophil release of their extracellular traps, which may be a more recently described form of cell death that is different from apoptosis, and how this may propagate organ dysfunction in COVID-19. We complete this review by discussing Stem Cell Therapies in COVID-19 and emerging COVID-19 phenotypes, which may allow for more targeted therapy in the future. Finally, we consider the array of potential therapeutic targets in COVID-19, and associated therapeutics.

Heart Metabolism in Sepsis-Induced Cardiomyopathy-Unusual Metabolic Dysfunction of the Heart

Due to the need for continuous work, the heart uses up to 8% of the total energy expenditure. Due to the relatively low adenosine triphosphate (ATP) storage capacity, the heart's work is dependent on its production. This is possible due to the metabolic flexibility of the heart, which allows it to use numerous substrates as a source of energy. Under normal conditions, a healthy heart obtains approximately 95% of its ATP by oxidative phosphorylation in the mitochondria. The primary source of energy is fatty acid oxidation, the rest of the energy comes from the oxidation of pyruvate. A failed heart is characterised by a disturbance in these proportions, with the contribution of individual components as a source of energy depending on the aetiology and stage of heart failure. A unique form of cardiac dysfunction is sepsis-induced cardiomyopathy, characterised by a significant reduction in energy production and impairment of cardiac oxidation of both fatty acids and glucose. Metabolic disorders appear to contribute to the pathogenesis of cardiac dysfunction and therefore are a promising target for future therapies. However, as many aspects of the metabolism of the failing heart remain unexplained, this issue requires further research.

Energetic dysfunction in sepsis: a narrative review

Background

Growing evidence associates organ dysfunction(s) with impaired metabolism in sepsis. Recent research has increased our understanding of the role of substrate utilization and mitochondrial dysfunction in the pathophysiology of sepsis-related organ dysfunction. The purpose of this review is to present this evidence as a coherent whole and to highlight future research directions.

Main text

Sepsis is characterized by systemic and organ-specific changes in metabolism. Alterations of oxygen consumption, increased levels of circulating substrates, impaired glucose and lipid oxidation, and mitochondrial dysfunction are all associated with organ dysfunction and poor outcomes in both animal models and patients. The pathophysiological relevance of bioenergetics and metabolism in the specific examples of sepsis-related immunodeficiency, cerebral dysfunction, cardiomyopathy, acute kidney injury and diaphragmatic failure is also described.

Conclusions

Recent understandings in substrate utilization and mitochondrial dysfunction may pave the way for new diagnostic and therapeutic approaches. These findings could help physicians to identify distinct subgroups of sepsis and to develop personalized treatment strategies. Implications for their use as bioenergetic targets to identify metabolism- and mitochondria-targeted treatments need to be evaluated in future studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00893-7.

Pathophysiology of sepsis-induced cardiomyopathy

Sepsis is the life-threatening organ dysfunction caused by a dysregulated host response to infection and is the leading cause of death in intensive care units. Cardiac dysfunction caused by sepsis, usually termed sepsis-induced cardiomyopathy, is common and has long been a subject of interest. In this Review, we explore the definition, epidemiology, diagnosis and pathophysiology of septic cardiomyopathy, with an emphasis on how best to interpret this condition in the clinical context. Advances in diagnostic techniques have increased the sensitivity of detection of myocardial abnormalities but have posed challenges in linking those abnormalities to therapeutic strategies and relevant clinical outcomes. Sophisticated methodologies have elucidated various pathophysiological mechanisms but the extent to which these are adaptive responses is yet to be definitively answered. Although the indications for monitoring and treating septic cardiomyopathy are clinical and directed towards restoring tissue perfusion, a better understanding of the course and implications of septic cardiomyopathy can help to optimize interventions and improve clinical outcomes.

Humanized Mice as a Tool to Study Sepsis-More Than Meets the Eye

(1) Background. Repetitive animal studies that have disappointed upon translation into clinical therapies have led to an increased appreciation of humanized mice as a remedy to the shortcomings of rodent-based models. However, their limitations have to be understood in depth. (2) Methods. This is a narrative, comprehensive review of humanized mice and sepsis literature to understand the model's benefits and shortcomings. (3) Results: Studies involving humanized models of sepsis include bacterial, viral, and protozoan etiology. Humanized mice provided several unique insights into the etiology and natural history of sepsis and are particularly useful in studying Ebola, and certain viral and protozoan infections. However, studies are relatively sparse and based on several different models of sepsis and humanized animals. (4) Conclusions. The utilization of humanized mice as a model for sepsis presents complex limitations that, once surpassed, hold some potential for the advancement of sepsis etiology and treatment.

Asporin is a Potential Promising Biomarker for Common Heart Failure

Heart failure (HF) is the end-stage of various diseases, especially ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM). We aimed to investigate the common molecular mechanism of ICM and DCM. Differentially expressed genes (DEGs) of ICM or DCM samples compared with control were identified in GSE1869, GSE5406, GSE57338, GSE79962, GSE116250, and GSE46224 datasets. Functional enrichment analysis and protein-protein network analysis of the coregulated DEGs in at least four datasets were performed using the online tools of DAVID, the Metascape database, and the STRING database. Hub genes of HF were identified and validated by western blotting (WB) and immunohistochemistry in our tissue microarray (TMA). Seventy-four coregulated ICM and 126 coregulated DCM relevant DEGs were identified. Moreover, 59 common genes between ICM and DCM relevant DEGs were obtained, which were mainly involved in cardiac fibrosis and several signal pathways, such as Wnt signal pathway, PI3K-Akt signal pathway, and HIF-1A signal pathway. Among the six hub genes with top degrees, asporin (ASPN) had a relatively higher correlation with LVEF. Finally, TMA and WB results revealed that the ASPN protein was significantly increased in ICM and DCM left ventricular samples. The present study revealed some common molecular mechanisms of HF with different causes. Furthermore, ASPN may be a potential promising biomarker for HF.

The effects of UCP2 on autophagy through the AMPK signaling pathway in septic cardiomyopathy and the underlying mechanism

Background

Mitochondrial dysfunction plays an important role in the development of septic cardiomyopathy. This study aimed to reveal the protective role of uncoupling protein 2 (UCP2) in mitochondria through AMP-activated protein kinase (AMPK) on autophagy during septic cardiomyopathy.

Methods

UCP2 knockout mice via a cecal ligation and puncture (CLP) model and the H9C2 cardiomyocyte cell line in response to lipopolysaccharide (LPS) in vitro were used to study the effect. The myocardial morphological alterations, indicators of mitochondrial injury and levels of autophagy-associated proteins (pAMPK, pmTOR, pULK1, pTSC2, Beclin-1, and LC3-I/II) were assessed. In addition, the mechanism of the interaction between UCP2 and AMPK was further studied through gain- and loss-of-function studies.

Results

Compared with the wild-type mice, the UCP2 knockout mice exhibited more severe cardiomyocyte injury after CLP, and the AMPK agonist AICAR protected against such injury. Consistent with this result, silencing UCP2 augmented the LPS-induced pathological damage and mitochondrial injury in the H9C2 cells, limited the upregulation of autophagy proteins and reduced AMPK phosphorylation. AICAR protected the cells from morphological changes and mitochondrial membrane potential loss and promoted autophagy. The silencing and overexpression of UCP2 led to correlated changes in the AMPK upstream kinases pLKB1 and CAMKK2.

Conclusions

UCP2 exerts cardioprotective effects on mitochondrial dysfunction during sepsis via the action of AMPK on autophagy.

Functional and molecular effects of TNF-α on human iPSC-derived cardiomyocytes

Proinflammatory molecule tumor necrosis factor alpha (TNF-α) is predominantly elevated in cytokine storm as well as worsening cardiac function. Here we model the molecular and functional effects of TNF-α in cardiomyocytes (CMs) derived from human induced pluripotent stem cells (hiPSC). We found that treatment of hiPSC-CMs with TNF-α increased reactive oxygen species (ROS) and caspase 3/7 activity and caused cell death and apoptosis. TNF-α treatment also resulted in dysregulation of cardiomyocyte function with respect to the increased abnormal calcium handling, calcium wave propagation between cells and excitation–contraction coupling. We also uncovered significant changes in gene expression and protein localization caused by TNF-α treatment. Notably, TNF-α treatment altered the expression of ion channels, dysregulated cadherins, and affected the localization of gap-junction protein connexin-43. In addition, TNF-α treatment up-regulated IL-32 (a human specific cytokine, not present in rodents and an inducer of TNF-α) and IL-34 and down-regulated glutamate receptors and cardiomyocyte contractile proteins. These findings provide insights into the molecular and functional consequences from the exposure of human cardiomyocytes to TNF-α. Our study provides a model to incorporate inflammatory factors into hiPSC-CM-based studies to evaluate mechanistic aspects of heart disease.

Monitoring mitochondrial PO2: the next step

PURPOSE OF REVIEW

To fully exploit the concept of hemodynamic coherence in resuscitating critically ill one should preferably take into account information about the state of parenchymal cells. Monitoring of mitochondrial oxygen tension (mitoPO2) has emerged as a clinical means to assess information of oxygen delivery and oxygen utilization at the mitochondrial level. This review will outline the basics of the technique, summarize its development and describe the rationale of measuring oxygen at the mitochondrial level.

RECENT FINDINGS

Mitochondrial oxygen tension can be measured by means of the protoporphyrin IX-Triplet State Lifetime Technique (PpIX-TSLT). After validation and use in preclinical animal models, the technique has recently become commercially available in the form of a clinical measuring system. This system has now been used in a number of healthy volunteer studies and is currently being evaluated in studies in perioperative and intensive care patients in several European university hospitals.

SUMMARY

PpIX-TSLT is a noninvasive and well tolerated method to assess aspects of mitochondrial function at the bedside. It allows doctors to look beyond the macrocirculation and microcirculation and to take the oxygen balance at the cellular level into account in treatment strategies.

Systematic analysis of molecular mechanisms of heart failure through the pathway and network-based approach

AIMS

The molecular networks and pathways involved in heart failure (HF) are still largely unknown. The present study aimed to systematically investigate the genes associated with HF, comprehensively explore their interactions and functions, and identify possible regulatory networks involved in HF.

MAIN METHODS

The weighted gene coexpression network analysis (WGCNA), crosstalk analysis, and Pivot analysis were used to identify gene connections, interaction networks, and molecular regulatory mechanisms. Functional analysis and protein-protein interaction (PPI) were performed using DAVID and STRING databases. Gene set variation analysis (GSVA) and receiver operating characteristic (ROC) curve analysis were also performed to evaluate the relationship of the hub genes with HF.

KEY FINDINGS

A total of 5968 HF-related genes were obtained to construct the co-expression networks, and 18 relatively independent and closely linked modules were identified. Pivot analysis suggested that four transcription factors and five noncoding RNAs were involved in regulating the process of HF. The genes in the module with the highest positive correlation to HF was mainly enriched in cardiac remodeling and response to stress. Five upregulated hub genes (ASPN, FMOD, NT5E, LUM, and OGN) were identified and validated. Furthermore, the GSVA scores of the five hub genes for HF had a relatively high areas under the curve (AUC).

SIGNIFICANCE

The results of this study revealed specific molecular networks and their potential regulatory mechanisms involved in HF. These may provide new insight into understanding the mechanisms underlying HF and help to identify more effective therapeutic targets for HF.

Songorine promotes cardiac mitochondrial biogenesis via Nrf2 induction during sepsis

Septic cardiomyopathy is characterized by impaired contractive function with mitochondrial dysregulation. Songorine is a typical active C₂₀-diterpene alkaloid from the lateral root of Aconitum carmichaelii, which has been used for the treatment of heart failure. This study investigated the protective role of songorine in septic heart injury from the aspect of mitochondrial biogenesis. Songorine (10, 50 mg/kg) protected cardiac contractive function against endotoxin insult in mice with Nrf2 induction. In cardiomyocytes, lipopolysaccharide (LPS) evoked mitochondrial reactive oxygen species (ROS) production and redistributed STIM1 to interact with Orai1 for the formation of calcium release-activated calcium (CRAC) channels, mediating calcium influx, which were prevented by songorine, likely due to ROS suppression. Songorine activated Nrf2 by promoting Keap1 degradation, having a contribution to enhancing antioxidant defenses. When LPS shifted metabolism away from mitochondrial oxidative phosphorylation (OXPHOS) in cardiomyocytes, songorine upregulated mitochondrial genes involved in fatty acid β-oxidation, tricarboxylic acid (TCA) cycle and electron transport chain in a manner dependent on Nrf2, resultantly protecting the capability of OXPHOS. Songorine increased luciferase report gene activities of nuclear respiratory factor-1 (Nrf1) and mitochondrial transcription factor A (Tfam) dependently on Nrf2, indicative of the regulation of Nrf2/ARE and NRF1 signaling cascades. Songorine promoted PGC-1α binding to Nrf2, and the cooperation was required for songorine to activate Nrf2/ARE and NRF1 for the control of mitochondrial quality and quantity. In support, the beneficial effects of songorine on cardioprotection and mitochondrial biogenesis were diminished by cardiac Nrf2 deficiency in mice subjected to LPS challenge. Taken together, these results showed that Nrf2 transcriptionally promoted mitochondrial biogenesis in cooperation with PGC-1α. Songorine activated Nrf2/ARE and NRF1 signaling cascades to rescue cardiomyocytes from endotoxin insult, suggesting that protection of mitochondrial biogenesis was a way for pharmacological intervention to prevent septic heart injury.

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Mitochondrial ROS increased calcium influx through CRAC channels.

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Nrf2 interacted with PGC-1α to regulate mitochondrial biogenesis.

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Songorine activated Nrf2 by promoting Keap1 degradation.

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Songorine regulated Nrf2/ARE and PGC-1α cascades to protect cardiac function.