The role of fibrosis in cardiomyopathies: An opportunity to develop novel biomarkers of disease activity.

Cardiomyopathies encompass a spectrum of heart disorders with diverse causes and presentations. Fibrosis stands out as a shared hallmark among various cardiomyopathies, reflecting a common thread in their pathogenesis. This prevalent fibrotic response is intricately linked to the consequences of dysregulated extracellular matrix (ECM) remodeling, emphasizing its significance in the development and progression the disease. This review explores the ECM involvement in various cardiomyopathies and its impact on myocardial stiffness and fibrosis. Additionally, we discuss the potential of ECM fragments as early diagnosis, prognosis, and risk stratification. Biomarkers deriving from turnover of collagens and other ECM proteins hold promise in clinical applications. We outline current clinical management, future directions, and the potential for personalized ECM-targeted therapies with specific focus on microRNAs. In summary, this review examines the role of the fibrosis in cardiomyopathies, highlighting the potential of ECM-derived biomarkers in improving disease management with implications for precision medicine.

Deciphering Pro-angiogenic Transcription Factor Profiles in Hypoxic Human Endothelial Cells by Combined Bioinformatics and in vitro Modeling.

Background: Constant supply of oxygen is crucial for multicellular tissue homeostasis and energy metabolism in cardiac tissue. As a first response to acute hypoxia, endothelial cells (ECs) promote recruitment and adherence of immune cells to the dysbalanced EC barrier by releasing inflammatory mediators and growth factors, whereas chronic hypoxia leads to the activation of a transcription factor (TF) battery, that potently induces expression of growth factors and cytokines including platelet-derived growth factor (PDGF) and vascular endothelial growth factor (VEGF). We report a hypoxia-minded, targeted bioinformatics approach aiming to identify and validate TFs that regulate angiogenic signaling. Results: A comprehensive RNA-Seq dataset derived from human ECs subjected to normoxic or hypoxic conditions was selected to identify significantly regulated genes based on (i) fold change (normoxia vs. hypoxia) and (ii) relative abundancy. Transcriptional regulation of this gene set was confirmed via qPCR in validation experiments where HUVECs were subjected to hypoxic conditions for 24 h. Screening the promoter and upstream regulatory elements of these genes identified two TFs, KLF5 and SP1, both with a potential binding site within these regions of selected target genes. In vitro, siRNA experiments confirmed SP1- and KLF5-mediated regulation of identified hypoxia-sensitive endothelial genes. Next to angiogenic signaling, we also validated the impact of TFs on inflammatory signaling, both key events in hypoxic sensing. Both TFs impacted on inflammatory signaling since endogenous repression led to increased NF-κB signaling. Additionally, SP1 silencing eventuated decreased angiogenic properties in terms of proliferation and tube formation. Conclusion: By detailed in silico analysis of promoter region and upstream regulatory elements for a list of hypoxia-sensitive genes, our bioinformatics approach identified putative binding sites for TFs of SP or KLF family in vitro. This strategy helped to identify TFs functionally involved in human angiogenic signaling and therefore serves as a base for identifying novel RNA-based drug entities in a therapeutic setting of vascularization.

Artificial Intelligence Identifies an Urgent Need for Peripheral Vascular Intervention by Multiplexing Standard Clinical Parameters.

BACKGROUND: Peripheral artery disease (PAD) is a significant burden, particularly among patients with severe disease requiring invasive treatment. We applied a general Machine Learning (ML) workflow and investigated if a multi-dimensional marker set of standard clinical parameters can identify patients in need of vascular intervention without specialized intra-hospital diagnostics. METHODS: This is a retrospective study involving patients with stable PAD (sPAD, Fontaine Class I and II, n = 38) and unstable PAD (unPAD, Fontaine Class III and IV, n = 18) in need of invasive therapeutic measures. ML algorithms such as Random Forest were utilized to evaluate a matrix consisting of multiple routinely clinically available parameters (age, complete blood count, inflammation, lipid, iron metabolism). RESULTS: ML has enabled a generation of an Artificial Intelligence (AI) PAD score (AI-PAD) that successfully divided sPAD from unPAD patients (high AI-PAD in sPAD, low AI-PAD in unPAD, cutoff at 50 AI-PAD units). Furthermore, the probability score positively coincided with gold-standard intra-hospital mean ankle-brachial index (ABI). CONCLUSION: AI-based tools may be promising to enable the correct identification of patients with unstable PAD by using existing clinical information, thus supplementing clinical decision making. Additional studies in larger prospective cohorts are necessary to determine the usefulness of this approach in comparison to standard diagnostic measures.

Reconstruction of the miR-506-Quaking axis in Idiopathic Pulmonary Fibrosis using integrative multi-source bioinformatics.

The family of RNA-binding proteins (RBP) functions as a crucial regulator of multiple biological processes and diseases. However, RBP function in the clinical setting of idiopathic pulmonary fibrosis (IPF) is still unknown. We developed a practical in silico screening approach for the characterization of RBPs using multi-sources data information and comparative molecular network bioinformatics followed by wet-lab validation studies. Data mining of bulk RNA-Sequencing data of tissues of patients with IPF identified Quaking (QKI) as a significant downregulated RBP. Cell-type specific expression was confirmed by single-cell RNA-Sequencing analysis of IPF patient data. We systematically analyzed the molecular interaction network around QKI and its functional interplay with microRNAs (miRs) in human lung fibroblasts and discovered a novel regulatory miR-506-QKI axis contributing to the pathogenesis of IPF. The in silico results were validated by in-house experiments applying model systems of miR and lung biology. This study supports an understanding of the intrinsic molecular mechanisms of IPF regulated by the miR-506-QKI axis. Initially applied to human lung disease, the herein presented integrative in silico data mining approach can be adapted to other disease entities, underlining its practical relevance in RBP research.

Combined high-throughput library screening and next generation RNA sequencing uncover microRNAs controlling human cardiac fibroblast biology.

BACKGROUND: Myocardial fibrosis is a hallmark of the failing heart, contributing to the most common causes of deaths worldwide. Several microRNAs (miRNAs, miRs) controlling cardiac fibrosis were identified in recent years; however, a more global approach to identify miRNAs involved in fibrosis is missing. METHODS AND RESULTS: Functional miRNA mimic library screens were applied in human cardiac fibroblasts (HCFs) to identify annotated miRNAs inducing proliferation. In parallel, miRNA deep sequencing was performed after subjecting HCFs to proliferating and resting stimuli, additionally enabling discovery of novel miRNAs. In-depth in vitro analysis confirmed the pro-fibrotic nature of selected, highly conserved miRNAs miR-20a-5p and miR-132-3p. To determine downstream cellular pathways and their role in the fibrotic response, targets of the annotated miRNA candidates were modulated by synthetic siRNA. We here provide evidence that repression of autophagy and detoxification of reactive oxygen species by miR-20a-5p and miR-132-3p explain some of their pro-fibrotic nature on a mechanistic level. CONCLUSION: We here identified both miR-20a-5p and miR-132-3p as crucial regulators of fibrotic pathways in an in vitro model of human cardiac fibroblast biology.

Inflammatory Drivers of Cardiovascular Disease: Molecular Characterization of Senescent Coronary Vascular Smooth Muscle Cells.

The senescence of vascular smooth muscle cells (VSMCs) has been implicated as a causal pro-inflammatory mechanism for cardiovascular disease development and progression of atherosclerosis, the instigator of ischemic heart disease. Contemporary limitations related to studying this cellular population and senescence-related therapeutics are caused by a lack of specific markers enabling their detection. Therefore, we aimed to profile a phenotypical and molecular signature of senescent VSMCs to allow reliable identification. To achieve this goal, we have compared non-senescent and senescent VSMCs from two in vitro models of senescence, replicative senescence (RS) and DNA-damage induced senescence (DS), by analyzing the expressions of established senescence markers: cell cycle inhibitors- p16 INK4a, p14 ARF, p21 and p53; pro-inflammatory factors-Interleukin 1ß (IL-1ß), IL-6 and high mobility group box-1 (HMGB-1); contractile proteins-smooth muscle heavy chain- (MYH11), smoothelin and transgelin (TAGLN), as well as structural features (nuclear morphology and LMNB1 (Lamin B1) expression). The different senescence-inducing modalities resulted in a lack of the proliferative activity. Nucleomegaly was seen in senescent VSMC as compared to freshly isolated VSMC Phenotypically, senescent VSMC appeared with a significantly larger cell size and polygonal, non-spindle-shaped cell morphology. In line with the supposed switch to a pro-inflammatory phenotype known as the senescence associated secretory phenotype (SASP), we found that both RS and DS upregulated IL-1ß and released HMGB-1 from the nucleus, while RS also showed IL-6 upregulation. In regard to cell cycle-regulating molecules, we detected modestly increased p16 levels in both RS and DS, but largely inconsistent p21, p14ARF, and p53 expressions in senescent VSMCs. Since these classical markers of senescence showed insufficient deregulation to warrant senescent VSMC detection, we have conducted a non-biased proteomics and in silico analysis of RS VSMC demonstrating altered RNA biology as the central molecular feature of senescence in this cell type. Therefore, key proteins involved with RNA functionality, HMGB-1 release, LMNB-1 downregulation, in junction with nuclear enlargement, can be used as markers of VSMC senescence, enabling the detection of these pathogenic pro-inflammatory cells in future therapeutic studies in ischemic heart disease and atherosclerosis.

Comprehensive Bioinformatics Identifies Key microRNA Players in ATG7-Deficient Lung Fibroblasts.

BACKGROUND: Deficient autophagy has been recently implicated as a driver of pulmonary fibrosis, yet bioinformatics approaches to study this cellular process are lacking. Autophagy-related 5 and 7 (ATG5/ATG7) are critical elements of macro-autophagy. However, an alternative ATG5/ATG7-independent macro-autophagy pathway was recently discovered, its regulation being unknown. Using a bioinformatics proteome profiling analysis of ATG7-deficient human fibroblasts, we aimed to identify key microRNA (miR) regulators in autophagy. METHOD: We have generated ATG7-knockout MRC-5 fibroblasts and performed mass spectrometry to generate a large-scale proteomics dataset. We further quantified the interactions between various proteins combining bioinformatics molecular network reconstruction and functional enrichment analysis. The predicted key regulatory miRs were validated via quantitative polymerase chain reaction. RESULTS: The functional enrichment analysis of the 26 deregulated proteins showed decreased cellular trafficking, increased mitophagy and senescence as the major overarching processes in ATG7-deficient lung fibroblasts. The 26 proteins reconstitute a protein interactome of 46 nodes and miR-regulated interactome of 834 nodes. The miR network shows three functional cluster modules around miR-16-5p, miR-17-5p and let-7a related to multiple deregulated proteins. Confirming these results in a biological setting, serially passaged wild-type and autophagy-deficient fibroblasts displayed senescence-dependent expression profiles of miR-16-5p and miR-17-5p. CONCLUSIONS: We have developed a bioinformatics proteome profiling approach that successfully identifies biologically relevant miR regulators from a proteomics dataset of the ATG-7-deficient milieu in lung fibroblasts, and thus may be used to elucidate key molecular players in complex fibrotic pathological processes. The approach is not limited to a specific cell-type and disease, thus highlighting its high relevance in proteome and non-coding RNA research.

Cardiac endurance training alters plasma profiles of circular RNA MBOAT2.

Marathon running is an extreme physical activity, which determines cardiopulmonary adaption of athletes. Circular RNAs (circRNAs) as potential biomarkers in the blood stream have so far not been tested after such strenuous activities. In silico approaches were performed to identify the potential candidate circRNA MBOAT2. Next, we demonstrated high stability and conservation of circRNA MBOAT2 as well as its abundancy in human plasma. In addition to Sanger sequencing of the circRNA specific head-to-tail junction, or back-splice site, we established a synthetic plasmid standard which allowed exact copy number calculations of circRNA MBOAT2. We then analyzed plasmatic circRNA MBOAT2 and observed a significantly lower level 24 h after the marathon. Such alterations were correlated to physical exercise parameters confirming the role of circRNA MBOAT2 as a promising noncoding RNA biomarker detecting cardiopulmonary adaption.NEW & NOTEWORTHY In brief, we herein report a timeline of circulating circular RNA (circRNA) MBOAT2 in a cohort of marathon runners. Time-course analysis of plasmatic circRNA MBOAT2 demonstrated a significantly lowered level 24 h after the marathon. Abundancy of circRNA was correlated to physical exercise parameters highlighting the role of circRNA MBOAT2 as a valuable noncoding RNA biomarker detecting and following up cardiopulmonary adaption.

Senescence-induced inflammation: an important player and key therapeutic target in atherosclerosis.

Inflammation is a hallmark and potent driver of pathological vascular remodelling in atherosclerosis. However, current anti-inflammatory therapeutic strategies have shown mixed results. As an alternative perspective on the conundrum of chronic inflammation emerging evidence points towards a small subset of senescent cells as a critical player and central node driving atherosclerosis. Senescent cells belonging to various cell types are a dominant and chronic source of a large array of pro-inflammatory cytokines and various additional plaque destabilizing factors, being involved with various aspects of atherosclerosis pathogenesis. Antagonizing these key agitators of local chronic inflammation and plaque instability may provide a causative and multi-purpose therapeutic strategy to treat atherosclerosis. Anti-senescence treatment options with translational potential are currently in development. However, several questions and challenges remain to be addressed before these novel treatment approaches may enter the clinical setting.