Micro-RNAs Are Related to Epicardial Adipose Tissue in Participants With Atrial Fibrillation: Data From the MiRhythm Study

Introduction: Epicardial adipose tissue (EAT) has been linked to incidence and recurrence of atrial fibrillation (AF), but the underlying mechanisms that mediate this association remain unclear. Circulating microRNAs (miRNAs) contribute to the regulation of gene expression in cardiovascular diseases, including AF. Thus, we sought to test the hypothesis that circulating miRNAs relate to burden of EAT. Methods: We examined the plasma miRNA profiles of 91 participants from the miRhythm study, an ongoing study examining associations between miRNA and AF. We quantified plasma expression of 86 unique miRNAs commonly expressed in cardiomyocytes using quantitative reverse transcriptase polymerase chain reaction (qPCR). From computed tomography, we used validated methods to quantify the EAT area surrounding the left atrium (LA) and indexed it to body surface area (BSA) to calculate indexed LA EAT (iLAEAT). Participants were divided into tertiles of iLAEAT to identify associations with unique miRNAs. We performed logistic regression analyses adjusting for factors associated with AF to examine relations between iLAEAT and miRNA. We performed further bioinformatics analysis of miRNA predicted target genes to identify potential molecular pathways are regulated by the miRNAs. Results: The mean age of the participants was 59 +/- 9, 35% were women, and 97% were Caucasian. Participants in the highest tertile of iLAEAT were more likely to have hypertension, heart failure, and thick posterior walls. In regression analyses, we found that miRNAs 155-5p (p \u3c 0.001) and 302a-3p (p \u3c 0.001) were significantly associated with iLAEAT in patients with AF. The predicted targets of the miRNAs identified were implicated in the regulation of cardiac hypertrophy, adipogenesis, interleukin-8 (IL-8), and nerve growth factor (NGF) signaling. Conclusion: miRNA as well as EAT have previously been linked to AF. Our finding that iLAEAT and miRNAs 155-5p and 302a-3p are associated suggest a possible direct link to between these entities in the development and maintenance of AF. Further research is needed to study causal relationships between these biomarkers

Relations between plasma microRNAs, echocardiographic markers of atrial remodeling, and atrial fibrillation: Data from the Framingham Offspring study

BACKGROUND: Circulating microRNAs may reflect or influence pathological cardiac remodeling and contribute to atrial fibrillation (AF). OBJECTIVE: The purpose of this study was to identify candidate plasma microRNAs that are associated with echocardiographic phenotypes of atrial remodeling, and incident and prevalent AF in a community-based cohort. METHODS: We analyzed left atrial function index (LAFI) of 1788 Framingham Offspring 8 participants. We quantified expression of 339 plasma microRNAs. We examined associations between microRNA levels with LAFI and prevalent and incident AF. We constructed pathway analysis of microRNAs\u27 predicted gene targets to identify molecular processes involved in adverse atrial remodeling in AF. RESULTS: The mean age of the participants was 66 +/- 9 years, and 54% were women. Five percent of participants had prevalent AF at the initial examination and 9% (n = 157) developed AF over a median 8.6 years of follow-up (IQR 8.1-9.2 years). Plasma microRNAs were associated with LAFI (N = 73, p \u3c 0.0001). Six of these plasma microRNAs were significantly associated with incident AF, including 4 also associated with prevalent AF (microRNAs 106b, 26a-5p, 484, 20a-5p). These microRNAs are predicted to regulate genes involved in cardiac hypertrophy, inflammation, and myocardial fibrosis. CONCLUSIONS: Circulating microRNAs 106b, 26a-5p, 484, 20a-5p are associated with atrial remodeling and AF

Circulating extracellular RNAs, myocardial remodeling, and heart failure in patients with acute coronary syndrome

Background: Given high on-treatment mortality in heart failure (HF), identifying molecular pathways that underlie adverse cardiac remodeling may offer novel biomarkers and therapeutic avenues. Circulating extracellular RNAs (ex-RNAs) regulate important biological processes and are emerging as biomarkers of disease, but less is known about their role in the acute setting, particularly in the setting of HF. Methods: We examined the ex-RNA profiles of 296 acute coronary syndrome (ACS) survivors enrolled in the Transitions, Risks, and Actions in Coronary Events Center for Outcomes Research and Education Cohort. We measured 374 ex-RNAs selected a priori, based on previous findings from a large population study. We employed a two-step, mechanism-driven approach to identify ex-RNAs associated with echocardiographic phenotypes (left ventricular [LV] ejection fraction, LV mass, LV end-diastolic volume, left atrial [LA] dimension, and LA volume index) then tested relations of these ex-RNAs with prevalent HF (N=31, 10.5%). We performed further bioinformatics analysis of microRNA (miRNAs) predicted targets\u27 genes ontology categories and molecular pathways. Results: We identified 44 ex-RNAs associated with at least one echocardiographic phenotype associated with HF. Of these 44 exRNAs, miR-29-3p, miR-584-5p, and miR-1247-5p were also associated with prevalent HF. The three microRNAs were implicated in the regulation p53 and transforming growth factor-beta signaling pathways and predicted to be involved in cardiac fibrosis and cell death; miRNA predicted targets were enriched in gene ontology categories including several involving the extracellular matrix and cellular differentiation. Conclusions: Among ACS survivors, we observed that miR-29-3p, miR-584-5p, and miR-1247-5p were associated with both echocardiographic markers of cardiac remodeling and prevalent HF. Relevance for Patients: miR-29c-3p, miR-584-5p, and miR-1247-5p were associated with echocardiographic phenotypes and prevalent HF and are potential biomarkers for adverse cardiac remodeling in HF

Simvastatin ameliorates established pulmonary hypertension through a heme oxygenase-1 dependent pathway in rats

<p>Abstract</p> <p>Background</p> <p>Simvastatin has been shown to ameliorate pulmonary hypertension by several mechanisms in experimental animal models. In this study, we hypothesized that the major benefits of simvastatin in pulmonary hypertension occur via the heme oxygenase-1 pathway.</p> <p>Methods</p> <p>Simvastatin (10 mg/kgw/day) was tested in two rat models of pulmonary hypertension (PH): monocrotaline administration and chronic hypoxia. The hemodynamic changes, right heart hypertrophy, HO-1 protein expression, and heme oxygenase (HO) activity in lungs were measured in both models with and without simvastatin treatment. Tin-protoporphyrin (SnPP, 20 μmol/kg w/day), a potent inhibitor of HO activity, was used to confirm the role of HO-1.</p> <p>Results</p> <p>Simvastatin significantly ameliorated pulmonary arterial hypertension from 38.0 ± 2.2 mm Hg to 22.1 ± 1.9 mm Hg in monocrotaline-induced PH (MCT-PH) and from 33.3 ± 0.8 mm Hg to 17.5 ± 2.9 mm Hg in chronic hypoxia-induced PH (CH-PH) rats. The severity of right ventricular hypertrophy was significantly reduced by simvastatin in MCT-PH and CH-PH rats. Co-administration with SnPP abolished the benefits of simvastatin. Simvastatin significantly increased HO-1 protein expression and HO activity in the lungs of rats with PH; however co-administration of SnPP reduced HO-1 activity only. These observations indicate that the simvastatin-induced amelioration of pulmonary hypertension was directly related to the activity of HO-1, rather than its expression.</p> <p>Conclusion</p> <p>This study demonstrated that simvastatin treatment ameliorates established pulmonary hypertension primarily through an HO-1-dependent pathway.</p

Proteomic Analyses Reveal High Expression of Decorin and Endoplasmin (HSP90B1) Are Associated with Breast Cancer Metastasis and Decreased Survival

BACKGROUND: Breast cancer is the most common malignancy among women worldwide in terms of incidence and mortality. About 10% of North American women will be diagnosed with breast cancer during their lifetime and 20% of those will die of the disease. Breast cancer is a heterogeneous disease and biomarkers able to correctly classify patients into prognostic groups are needed to better tailor treatment options and improve outcomes. One powerful method used for biomarker discovery is sample screening with mass spectrometry, as it allows direct comparison of protein expression between normal and pathological states. The purpose of this study was to use a systematic and objective method to identify biomarkers with possible prognostic value in breast cancer patients, particularly in identifying cases most likely to have lymph node metastasis and to validate their prognostic ability using breast cancer tissue microarrays. METHODS AND FINDINGS: Differential proteomic analyses were employed to identify candidate biomarkers in primary breast cancer patients. These analyses identified decorin (DCN) and endoplasmin (HSP90B1) which play important roles regulating the tumour microenvironment and in pathways related to tumorigenesis. This study indicates that high expression of Decorin is associated with lymph node metastasis (p&lt;0.001), higher number of positive lymph nodes (p&lt;0.0001) and worse overall survival (p = 0.01). High expression of HSP90B1 is associated with distant metastasis (p&lt;0.0001) and decreased overall survival (p&lt;0.0001) these patients also appear to benefit significantly from hormonal treatment. CONCLUSIONS: Using quantitative proteomic profiling of primary breast cancers, two new promising prognostic and predictive markers were found to identify patients with worse survival. In addition HSP90B1 appears to identify a group of patients with distant metastasis with otherwise good prognostic features

Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors

[Abstract] The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order kth (Wk). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the Wk(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated Wk(i) values were used as inputs for different ANNs in order to discriminate correct node connectivity patterns from incorrect random patterns. The MIANN models obtained present good values of Sensitivity/Specificity (%): MRNs (78/78), IWDBNs (90/88), and SFLN (86/84). These preliminary results are very promising from the point of view of a first exploratory study and suggest that the use of these models could be extended to the high-throughput re-evaluation of connectivity in known complex networks (collation)

Immunoscreening of the extracellular proteome of colorectal cancer cells

<p>Abstract</p> <p>Background</p> <p>The release of proteins from tumors can trigger an immune response in cancer patients involving T lymphocytes and B lymphocytes, which results in the generation of antibodies to tumor-derived proteins. Many studies aim to use humoral immune responses, namely autoantibody profiles, directly, as clinical biomarkers. Alternatively, the antibody immune response as an amplification system for tumor associated alterations may be used to indicate putative protein biomarkers with high sensitivity. Aiming at the latter approach we here have implemented an autoantibody profiling strategy which particularly focuses on proteins released by tumor cells in vitro: the so-called secretome.</p> <p>Methods</p> <p>For immunoscreening, the extracellular proteome of five colorectal cancer cell lines was resolved on 2D gels, immobilized on PVDF membranes and used for serological screening with individual sera from 21 colorectal cancer patients and 24 healthy controls. All of the signals from each blot were assigned to a master map, and autoantigen candidates were defined based of the pattern of immunoreactivities. The corresponding proteins were isolated from preparative gels, identified by MALDI-MS and/or by nano-HPLC/ESI-MS/MS and exemplarily confirmed by duplex Western blotting combining the human serum samples with antibodies directed against the protein(s) of interest.</p> <p>Results</p> <p>From 281 secretome proteins stained with autoantibodies in total we first defined the "background patterns" of frequently immunoreactive extracellular proteins in healthy and diseased people. An assignment of these proteins, among them many nominally intracellular proteins, to the subset of exosomal proteins within the secretomes revealed a large overlap. On this basis we defined and consequently confirmed novel biomarker candidates such as the extreme C-terminus of the extracellular matrix protein agrin within the set of cancer-enriched immunorectivities.</p> <p>Conclusions</p> <p>Our findings suggest, first, that autoantibody responses may be due, in large part, to cross-presentation of antigens to the immune system via exosomes, membrane vesicles released by tumor cells and constituting a significant fraction of the secretome. In addition, this immunosecretomics approach has revealed novel biomarker candidates, some of them secretome-specific, and thus serves as a promising complementary tool to the frequently reported immunoproteomic studies for biomarker discovery.</p

Multiple network properties overcome random connectivity to enable stereotypic sensory responses

Connections between neuronal populations may be genetically hardwired or random. In the insect olfactory system, projection neurons of the antennal lobe connect randomly to Kenyon cells of the mushroom body. Consequently, while the odor responses of the projection neurons are stereotyped across individuals, the responses of the Kenyon cells are variable. Surprisingly, downstream of Kenyon cells, mushroom body output neurons show stereotypy in their responses. We found that the stereotypy is enabled by the convergence of inputs from many Kenyon cells onto an output neuron, and does not require learning. The stereotypy emerges in the total response of the Kenyon cell population using multiple odor-specific features of the projection neuron responses, benefits from the nonlinearity in the transfer function, depends on the convergence:randomness ratio, and is constrained by sparseness. Together, our results reveal the fundamental mechanisms and constraints with which convergence enables stereotypy in sensory responses despite random connectivity