Molecular signatures and the study of gene expression profiles in inflammatory heart diseases

LncRNA HCG18 affects diabetic cardiomyopathy and its association with miR-9-5p/IGF2R axis

This paper aimed to investigate the role of lncRNA HCG18 (HCG18) in the progression of diabetic cardiomyopathy (DCM) and potential mechanisms. Streptozocin (STZ) was used to induce DCM model in rats, which was confirmed by blood glucose concentration, body weight, and HE staining. Myocardial apoptosis was detected by TUNEL. H9c2 cardiomyocytes were used to construct cell models of DCM through treatment of high glucose. The results showed that HCG18 was overexpressed in STZ induced DCM rat model and high glucose induced H9c2 cardiomyocytes. Si-HCG18 significantly increased cell viability, reduced cell apoptosis, attenuated activities of myocardial enzymes and enhanced activities of antioxidant enzymes in STZ induced DM model and high glucose induced H9c2 cardiomyocytes, while the results of upregulation of HCG18, in high glucose induced H9c2 cardiomyocytes, were opposite with that of si-HCG18. MiR-9-5p was a target of HCG18, and which was down-regulated in cardiomyocytes of DCM. The overexpression of miR-9-5p could neutralize the high glucose induced cardiomyocyte injury, and the silence of miR-9-5p could reverse the effect of si-HCG18 on high glucose induced cardiomyocytes. MiR-9-5p could directly target to IGF2R, and IGF2R was overexpressed in cardiomyocytes of DCM. Up-regulation of IGF2R can reverse the protective effect of si-HCG18 on cardiomyocytes. Taken together, HCG18 is significantly increased in cardiomyocytes of DCM. Down-regulation of HCG18 can improve cardiomyocyte injury through miR-9-5p/IGF2R axis in DCM.

Myocarditis: A multi-omics approach

Myocarditis, an inflammatory condition of weakened heart muscles often triggered by a variety of causes, that can result in heart failure and sudden death. Novel ways to enhance our understanding of myocarditis pathogenesis is available through newer modalities (omics). In this review, we examine the roles of various biomolecules and associated functional pathways across genomics, transcriptomics, proteomics, and metabolomics in the pathogenesis of myocarditis. Our analysis further explores the reproducibility and variability intrinsic to omics studies, underscoring the necessity and significance of employing a multi-omics approach to gain profound insights into myocarditis pathogenesis. This integrated strategy not only enhances our understanding of the disease, but also confirms the critical importance of a holistic multi-omics approach in disease analysis.

Heart Infection Prognosis Analysis by Two-dimensional Spot Tracking Imaging

Cardiovascular death is one of the leading causes worldwide; an accurate identification followed by diagnosing the cardiovascular disease increases the chance of a better recovery. Among different demonstrated strategies, imaging on cardiac infections yields a visible result and highly reliable compared to other analytical methods. Two-dimensional spot tracking imaging is the emerging new technology that has been used to study the function and structure of the heart and test the deformation and movement of the myocardium. Particularly, it helps to capture the images of each segment in different directions of myocardial strain values, such as valves of radial strain, longitudinal strain, and circumferential strain. In this overview, we discussed the imaging of infections in the heart by using the two-dimensional spot tracking.

Muscle Gene Sets: a versatile methodological aid to functional genomics in the neuromuscular field

BACKGROUND

The approach of building large collections of gene sets and then systematically testing hypotheses across these collections is a powerful tool in functional genomics, both in the pathway analysis of omics data and to uncover the polygenic effects associated with complex diseases in genome-wide association study. The Molecular Signatures Database includes collections of oncogenic and immunologic signatures enabling researchers to compare transcriptional datasets across hundreds of previous studies and leading to important insights in these fields, but such a resource does not currently exist for neuromuscular research. In previous work, we have shown the utility of gene set approaches to understand muscle cell physiology and pathology.

METHODS

Following a systematic survey of public muscle data, we passed gene expression profiles from 4305 samples through a robust pre-processing and standardized data analysis pipeline. Two hundred eighty-two samples were discarded based on a battery of rigorous global quality controls. From among the remaining studies, 578 comparisons of interest were identified by a combination of text mining and manual curation of the study meta-data. For each comparison, significantly dysregulated genes (FDR adjusted p < 0.05) were identified.

RESULTS

Lists of dysregulated genes were divided between upregulated and downregulated to give 1156 Muscle Gene Sets (MGS). This resource is available for download ( www.sys-myo.com/muscle_gene_sets ) and is accessible through three commonly used functional genomics platforms (GSEA, EnrichR, and WebGestalt). Basic guidance and recommendations are provided for the use of MGS through these platforms. In addition, consensus muscle gene sets were created to capture the overlap between the results of similar studies, and analysis of these highlighted the potential for novel disease-relevant findings.

CONCLUSIONS

The MGS resource can be used to investigate the behaviour of any list of genes across previous comparisons of muscle conditions, to compare previous studies to one another, and to explore the functional relationship of muscle dysregulation to the Gene Ontology. Its major intended use is in enrichment testing for functional genomics analysis.

[Inflammatory cardiomyopathy and myocarditis]

We describe diagnosis, differential diagnosis, multimodality imaging and medical and invasive diagnostic treatment in patients with inflammatory cardiomyopathy and myocarditis under etiological considerations in reference to a landmark position paper of the Working Group Myocardial and Pericardial Diseases of the European Society of Cardiology together with recent developments in diagnosis and treatment. Diagnosis of the symptomatic patient is the assessment of etiology of inflammatory cardiomyopathy, followed by the clinical presentation, course, treatment option and prognosis. Viral myocarditis in its different facets can clearly be separated from autoreactive forms by histological and molecular methods in the endomyocardial biopsy, thus leading to an individualized targeted therapy beyond heart failure treatment.

Relevance of cardiac parvovirus B19 in myocarditis and dilated cardiomyopathy: review of the literature

Over the last decade, parvovirus B19 (B19V) has frequently been linked to the pathogenesis of myocarditis (MC) and its progression towards dilated cardiomyopathy (DCM). The exact role of the presence of B19V and its load remains controversial, as this virus is also found in the heart of healthy subjects. Moreover, the prognostic relevance of B19V prevalence in endomyocardial biopsies still remains unclear. As a result, it is unclear whether the presence of B19V should be treated. This review provides an overview of recent literature investigating the presence of B19V and its pathophysiological relevance in MC and DCM, as well as in normal hearts. In brief, no difference in B19V prevalence is observed between MC/DCM and healthy control hearts. Therefore, the question remains open whether and how cardiac B19V may be of pathogenetic importance. Findings suggest that B19V is aetiologically relevant either in the presence of other cardiotropic viruses, or when B19V load is high and/or actively replicating, which both may maintain myocardial (low-grade) inflammation. Therefore, future studies should focus on the prognostic relevance of the viral load, replicative status and virus co-infections. In addition, the immunogenetic background of MC/DCM patients that makes them susceptible to develop heart failure upon presence of B19V should be more thoroughly investigated.

Src/Syk/IRAK1-targeted anti-inflammatory action of Torreya nucifera butanol fraction in lipopolysaccharide-activated RAW264.7 cells

ETHNOPHARMACOLOGICAL RELEVANCE

Seed of Torreya nucifera (L.) Siebold & Zucc is used to treat several diseases in Asia. Reports document that T. nucifera has anti-cancer, anti-inflammatory, anti-oxidative activities. In spite of numerous findings on its pharmacological effects, the understanding of the molecular inhibitory mechanisms of the plant remains to be studied. Therefore, we aimed to explore in vitro anti-inflammatory mechanisms of ethyl acetate fraction (Tn-EE-BF) prepared from the seed of T. nucifera in LPS-stimulated macrophage inflammatory responses.

MATERIALS AND METHODS

For this purpose, we measured nitric oxide (NO) and prostaglandin E2 (PGE2) in LPS-stimulated macrophages. Additionally, using RT-PCR, luciferase reporter gene assay, immunoblotting analysis, and kinase assay, the levels of inflammatory genes, transcription factors, and inflammatory signal-regulatory proteins were investigated. Finally, the constituent of Tn-EE-BF was identified using HPLC.

RESULTS

Tn-EE-BF inhibits NO and PGE2 production and also blocks mRNA levels of inducible NO synthase (iNOS), tumor necrosis factor (TNF)-α, and cyclooxygenase (COX)-2 in a dose dependent manner. Tn-EE-BF reduces nuclear levels of the transcriptional factors NF-κB (p65) and AP-1 (c-Jun and FRA-1). Surprisingly, we found that Tn-EE-BF inhibits phosphorylation levels of Src and Syk in the NF-κB pathway, as well as, IRAK1 at the protein level, part of the AP-1 pathway. By kinase assay, we confirmed that Src, Syk, and IRAK1 are suppressed directly. HPLC analysis indicates that arctigenin, amentoflavone, and quercetin may be active components with anti-inflammatory activities.

CONCLUSION

Tn-EE-BF exhibits anti-inflammatory activities by direct inhibition of Src/Syk/NF-κB and IRAK1/AP-1.

Bioinformatics multivariate analysis determined a set of phase-specific biomarker candidates in a novel mouse model for viral myocarditis

BACKGROUND

Myocarditis is an inflammatory disease of the cardiac muscle and is mainly caused by viral infections. Viral myocarditis has been proposed to be divided into 3 phases: the acute viral phase, the subacute immune phase, and the chronic cardiac remodeling phase. Although individualized therapy should be applied depending on the phase, no clinical or experimental studies have found biomarkers that distinguish between the 3 phases. Theiler's murine encephalomyelitis virus belongs to the genus Cardiovirus and can cause myocarditis in susceptible mouse strains.

METHODS AND RESULTS

Using this novel model for viral myocarditis induced with Theiler's murine encephalomyelitis virus, we conducted multivariate analysis including echocardiography, serum troponin and viral RNA titration, and microarray to identify the biomarker candidates that can discriminate the 3 phases. Using C3H mice infected with Theiler's murine encephalomyelitis virus on 4, 7, and 60 days post infection, we conducted bioinformatics analyses, including principal component analysis and k-means clustering of microarray data, because our traditional cardiac and serum assays, including 2-way comparison of microarray data, did not lead to the identification of a single biomarker. Principal component analysis separated heart samples clearly between the groups of 4, 7, and 60 days post infection. Representative genes contributing to the separation were as follows: 4 and 7 days post infection, innate immunity-related genes, such as Irf7 and Cxcl9; 7 and 60 days post infection, acquired immunity-related genes, such as Cd3g and H2-Aa; and cardiac remodeling-related genes, such as Mmp12 and Gpnmb.

CONCLUSIONS

Sets of molecules, not single molecules, identified by unsupervised principal component analysis, were found to be useful as phase-specific biomarkers.

Stem cell systems informatics for advanced clinical biodiagnostics: tracing molecular signatures from bench to bedside

Development of innovative high throughput technologies has enabled a variety of molecular landscapes to be interrogated with an unprecedented degree of detail. Emergence of next generation nucleotide sequencing methods, advanced proteomic techniques, and metabolic profiling approaches continue to produce a wealth of biological data that captures molecular frameworks underlying phenotype. The advent of these novel technologies has significant translational applications, as investigators can now explore molecular underpinnings of developmental states with a high degree of resolution. Application of these leading-edge techniques to patient samples has been successfully used to unmask nuanced molecular details of disease vs healthy tissue, which may provide novel targets for palliative intervention. To enhance such approaches, concomitant development of algorithms to reprogram differentiated cells in order to recapitulate pluripotent capacity offers a distinct advantage to advancing diagnostic methodology. Bioinformatic deconvolution of several “-omic” layers extracted from reprogrammed patient cells, could, in principle, provide a means by which the evolution of individual pathology can be developmentally monitored. Significant logistic challenges face current implementation of this novel paradigm of patient treatment and care, however, several of these limitations have been successfully addressed through continuous development of cutting edge in silico archiving and processing methods. Comprehensive elucidation of genomic, transcriptomic, proteomic, and metabolomic networks that define normal and pathological states, in combination with reprogrammed patient cells are thus poised to become high value resources in modern diagnosis and prognosis of patient disease.

Stem cell systems informatics for advanced clinical biodiagnostics: tracing molecular signatures from bench to bedside

Development of innovative high throughput technologies has enabled a variety of molecular landscapes to be interrogated with an unprecedented degree of detail. Emergence of next generation nucleotide sequencing methods, advanced proteomic techniques, and metabolic profiling approaches continue to produce a wealth of biological data that captures molecular frameworks underlying phenotype. The advent of these novel technologies has significant translational applications, as investigators can now explore molecular underpinnings of developmental states with a high degree of resolution. Application of these leading-edge techniques to patient samples has been successfully used to unmask nuanced molecular details of disease vs healthy tissue, which may provide novel targets for palliative intervention. To enhance such approaches, concomitant development of algorithms to reprogram differentiated cells in order to recapitulate pluripotent capacity offers a distinct advantage to advancing diagnostic methodology. Bioinformatic deconvolution of several "-omic" layers extracted from reprogrammed patient cells, could, in principle, provide a means by which the evolution of individual pathology can be developmentally monitored. Significant logistic challenges face current implementation of this novel paradigm of patient treatment and care, however, several of these limitations have been successfully addressed through continuous development of cutting edge in silico archiving and processing methods. Comprehensive elucidation of genomic, transcriptomic, proteomic, and metabolomic networks that define normal and pathological states, in combination with reprogrammed patient cells are thus poised to become high value resources in modern diagnosis and prognosis of patient disease.