The crosstalk between bone metabolism, lncRNAs, microRNAs and mRNAs in coronary artery calcification

Alteration of circulating ACE2-network related microRNAs in patients with COVID-19

Angiotensin converting enzyme 2 (ACE2) serves as the primary receptor for the SARS-CoV-2 virus and has implications for the functioning of the cardiovascular system. Based on our previously published bioinformatic analysis, in this study we aimed to analyze the diagnostic and predictive utility of miRNAs (miR-10b-5p, miR-124-3p, miR-200b-3p, miR-26b-5p, miR-302c-5p) identified as top regulators of ACE2 network with potential to affect cardiomyocytes and cardiovascular system in patients with COVID-19. The expression of miRNAs was determined through qRT-PCR in a cohort of 79 hospitalized COVID-19 patients as well as 32 healthy volunteers. Blood samples and clinical data of COVID-19 patients were collected at admission, 7-days and 21-days after admission. We also performed SHAP analysis of clinical data and miRNAs target predictions and advanced enrichment analyses. Low expression of miR-200b-3p at the seventh day of admission is indicative of predictive value in determining the length of hospital stay and/or the likelihood of mortality, as shown in ROC curve analysis with an AUC of 0.730 and a p-value of 0.002. MiR-26b-5p expression levels in COVID-19 patients were lower at the baseline, 7 and 21-days of admission compared to the healthy controls (P < 0.0001). Similarly, miR-10b-5p expression levels were lower at the baseline and 21-days post admission (P = 0.001). The opposite situation was observed in miR-124-3p and miR-302c-5p. Enrichment analysis showed influence of analyzed miRNAs on IL-2 signaling pathway and multiple cardiovascular diseases through COVID-19-related targets. Moreover, the COVID-19-related genes regulated by miR-200b-3p were linked to T cell protein tyrosine phosphatase and the HIF-1 transcriptional activity in hypoxia. Analysis focused on COVID-19 associated genes showed that all analyzed miRNAs are strongly affecting disease pathways related to CVDs which could be explained by their strong interaction with the ACE2 network.

Role of ONECUT family transcription factors in cancer and other diseases

Members of ONECUT transcription factor play an essential role in several developmental processes, however, the atypical expression of ONECUT proteins lead to numerous diseases, including cancer. ONECUT family proteins promote cell proliferation, progression, invasion, metastasis, angiogenesis, and stemness. This family of proteins interacts with other proteins such as KLF4, TGF-β, VEGFA, PRC2, SMAD3 and alters their expression involved in the regulation of various signaling pathways including Jak/Stat3, Akt/Erk, TGF-β, Smad2/3, and HIF-1α. Furthermore, ONECUT proteins are proposed as predictive biomarkers for pancreatic and gastric cancers. The present review summarizes the involvement of ONECUT family proteins in the development and progression of various human cancers and other diseases.

More than the SRY: The Non-Coding Landscape of the Y Chromosome and Its Importance in Human Disease

Historically, the Y chromosome has presented challenges to classical methodology and philosophy of understanding the differences between males and females. A genetic unsolved puzzle, the Y chromosome was the last chromosome to be fully sequenced. With the advent of the Human Genome Project came a realization that the human genome is more than just genes encoding proteins, and an entire universe of RNA was discovered. This dark matter of biology and the black box surrounding the Y chromosome have collided over the last few years, as increasing numbers of non-coding RNAs have been identified across the length of the Y chromosome, many of which have played significant roles in disease. In this review, we will uncover what is known about the connections between the Y chromosome and the non-coding RNA universe that originates from it, particularly as it relates to long non-coding RNAs, microRNAs and circular RNAs.

miR-9a-5p expression is decreased in the hippocampus of rats resistant to lamotrigine: A behavioural, molecular and bioinformatics assessment

The major obstacle in developing new treatment strategies for refractory epilepsy is the complexity and poor understanding of its mechanisms. Utilizing the model of lamotrigine-resistant seizures, we evaluated whether changes in the expression of sodium channel subunits are responsible for the diminished responsiveness to lamotrigine (LTG) and if miRNAs, may also be associated. Male rats were administered LTG (5 mg/kg) before each stimulation during kindling acquisition. Challenge stimulation following LTG exposure (30 mg/kg) was performed to confirm resistance in fully kindled rats. RT-PCR was used to measure the mRNA levels of sodium channel subunits (SCN1A, SCN2A, and SCN3A) and miRNAs (miR-155-5p, miR-30b-5p, miR-137-3p, miR-342-5p, miR-301a-3p, miR-212-3p, miR-9a-5p, and miR-133a-3p). Western blot analysis was utilized to measure Nav1.2 protein, and bioinformatics tools were used to perform target prediction and enrichment analysis for miR-9a-5p, the only affected miRNA according to the responsiveness to LTG. Amygdala kindling seizures downregulated Nav1.2, miR-137-3p, miR-342-5p, miR-155-5p, and miR-9a-5p as well as upregulated miR-212-3p. miR-9a-5p was the only molecule decreased in rats resistant to LTG. The bioinformatic assessment and disease enrichment analysis revealed that miR-9a-5p targets expressed with high confidence in the hippocampus are the most significantly associated with epilepsy. Due to the miR-9a-5p dysregulation, major pathways affected are neurotrophic processes, neurotransmission, inflammatory response, cell proliferation and apoptosis. Interaction network analysis identified LTG target SCN2A as interacting with highest number of genes regulated by miR-9-5p. Further studies are needed to propose specific genes and miRNAs responsible for diminished responsiveness to LTG. miR-9a-5p targets, like KCNA4, KCNA2, CACNB2, SCN4B, KCNC1, should receive special attention in them.

Characterization of the SGLT2 Interaction Network and Its Regulation by SGLT2 Inhibitors: A Bioinformatic Analysis

Background: Sodium–glucose cotransporter 2 (SGLT2), also known as solute carrier family 5 member 2 (SLC5A2), is a promising target for a new class of drugs primarily established as kidney-targeting, effective glucose-lowering agents used in diabetes mellitus (DM) patients. Increasing evidence indicates that besides renal effects, SGLT2 inhibitors (SGLT2i) have also a systemic impact via indirectly targeting the heart and other tissues. Our hypothesis states that the pleiotropic effects of SGLT2i are associated with their binding force, location of targets in the SGLT2 networks, targets involvement in signaling pathways, and their tissue-specific expression.

Methods: Thus, to investigate differences in SGLT2i impact on human organisms, we re-created the SGLT2 interaction network incorporating its inhibitors and metformin and analyzed its tissue-specific expression using publicly available datasets. We analyzed it in the context of the so-called key terms ( autophagy, oxidative stress, aging, senescence, inflammation, AMPK pathways, and mTOR pathways) which seem to be crucial to elucidating the SGLT2 role in a variety of clinical manifestations.

Results: Analysis of SGLT2 and its network components’ expression confidence identified selected organs in the following order: kidney, liver, adipose tissue, blood, heart, muscle, intestine, brain, and artery according to the TISSUES database. Drug repurposing analysis of known SGLT2i pointed out the influence of SGLT1 regulators on the heart and intestine tissue. Additionally, dapagliflozin seems to also have a stronger impact on brain tissue through the regulation of SGLT3 and SLC5A11. The shortest path analysis identified interaction SIRT1-SGLT2 among the top five interactions across six from seven analyzed networks associated with the key terms. Other top first-level SGLT2 interactors associated with key terms were not only ADIPOQ, INS, GLUT4, ACE, and GLUT1 but also less recognized ILK and ADCY7. Among other interactors which appeared in multiple shortest-path analyses were GPT, COG2, and MGAM. Enrichment analysis of SGLT2 network components showed the highest overrepresentation of hypertensive disease, DM-related diseases for both levels of SGLT2 interactors. Additionally, for the extended SGLT2 network, we observed enrichment in obesity (including SGLT1), cancer-related terms, neuroactive ligand–receptor interaction, and neutrophil-mediated immunity.

Conclusion: This study provides comprehensive and ranked information about the SGLT2 interaction network in the context of tissue expression and can help to predict the clinical effects of the SGLT2i.

Analysis of miRNA Associated with Coronary Artery Calcification

Cardiovascular diseases seriously endanger human physical and mental health and life safety, to investigate correlation between miR-let-7b and miR-29b and coronary artery calcification of various patients. At present, real-time fluorescence quantitative PCR (qRT-PCR) was used to detect the expression levels of plasma miR-let-7b and miR-29b in patients with coronary artery calcification and noncoronary artery calcification and to analyze whether the expression levels of miR-let-7b and miR-29b were different between the two groups. It was shown that there was no significant difference in the expression of miR-let-7d-3p between the two groups. But the expression of miR-29b in the observation group was significantly lower than that in the control group. Taken together, miR-29b might be a risk factor for coronary artery calcification and may be a marker for early diagnosis of coronary artery calcification.

Altered Circulating MicroRNA Profiles After Endurance Training: A Cohort Study of Ultramarathon Runners

BACKGROUND

Despite the positive effects of endurance training on the cardiovascular (CV) system, excessive exercise induces not only physiological adaptations but also adverse changes in CV system, including the heart. We aimed to evaluate the selected miRNAs expression based on bioinformatic analysis and their changes before and after an ultramarathon run.

MATERIALS AND METHODS

Cardiac tissue-specific targets were identified with the Tissue 2.0 database. Gene-gene interaction data were retrieved from the STRING app for Cytoscape. Twenty-three endurance athletes were recruited to the study. Athletes ran to completion (100 km) or exhaustion (52-91 km, median 74 km). All participants completed pre- and post-run testing. miRNAs expressions were measured both before and after the race.

RESULTS

Enrichment analysis of the signaling pathways associated with the genes targeted by miRNAs selected for qRT-PCR validation (miR-1-3p, miR-126, miR-223, miR-125a-5p, miR-106a-5p, and miR-15a/b). All selected miRNAs showed overlap in regulation in pathways associated with cancer, IL-2 signaling, TGF-β signaling as well as BDNF signaling pathway. Analysis of metabolites revealed significant regulation of magnesium and guanosine triphosphate across analyzed miRNA targets. MiR-1-3p, miR-125a-5p, miR-126, and miR-223 expressions were measured in 23 experienced endurance athletes, before and after an ultramarathon wherein athletes ran to completion (100 km) or exhaustion (52-91 km, median 74 km). The expressions of miR-125a-5p, miR-126, and miR-223 were significantly increased after the race (p = 0.007, p = 0.001, p = 0.014, respectively). MiR-1-3p expression post-run showed a negative correlation with the post-run levels of high-sensitivity C-reactive protein (hs-CRP) (r = -0.632, p = 0.003). Higher miR-1-3p expression was found in runners, who finished the race under 10 h compared to runners who finished over 10 h (p = 0.001). Post-run miR-125a-5p expression showed a negative correlation with the peak lactate during the run (r = -0.576, p = 0.019).

CONCLUSION

Extreme physical activity, as exemplified by an ultramarathon, is associated with changes in circulating miRNAs' expression related to inflammation, fibrosis, and cardiac muscle function. In particular, the negative correlations between miR-125a-5p and lactate concentrations, and miR-1-3p and hs-CRP, support their role in specific exercise-induced adaptation. Further studies are essential to validate the long-term effect of these observations.

Thrombosis-related circulating miR-16-5p is associated with disease severity in patients hospitalised for COVID-19

SARS-CoV-2 tropism for the ACE2 receptor, along with the multifaceted inflammatory reaction, is likely to drive the generalized hypercoagulable and thrombotic state seen in patients with COVID-19. Using the original bioinformatic workflow and network medicine approaches we reanalysed four coronavirus-related expression datasets and performed co-expression analysis focused on thrombosis and ACE2 related genes. We identified microRNAs (miRNAs) which play role in ACE2-related thrombosis in coronavirus infection and further, we validated the expressions of precisely selected miRNAs-related to thrombosis (miR-16-5p, miR-27a-3p, let-7b-5p and miR-155-5p) in 79 hospitalized COVID-19 patients and 32 healthy volunteers by qRT-PCR. Consequently, we aimed to unravel whether bioinformatic prioritization could guide selection of miRNAs with a potential of diagnostic and prognostic biomarkers associated with disease severity in patients hospitalized for COVID-19. In bioinformatic analysis, we identified EGFR, HSP90AA1, APP, TP53, PTEN, UBC, FN1, ELAVL1 and CALM1 as regulatory genes which could play a pivotal role in COVID-19 related thrombosis. We also found miR-16-5p, miR-27a-3p, let-7b-5p and miR-155-5p as regulators in the coagulation and thrombosis process. In silico predictions were further confirmed in patients hospitalized for COVID-19. The expression levels of miR-16-5p and let-7b in COVID-19 patients were lower at baseline, 7-days and 21-day after admission compared to the healthy controls (p < 0.0001 for all time points for both miRNAs). The expression levels of miR-27a-3p and miR-155-5p in COVID-19 patients were higher at day 21 compared to the healthy controls (p = 0.007 and p < 0.001, respectively). A low baseline miR-16-5p expression presents predictive utility in assessment of the hospital length of stay or death in follow-up as a composite endpoint (AUC:0.810, 95% CI, 0.71-0.91, p < 0.0001) and low baseline expression of miR-16-5p and diabetes mellitus are independent predictors of increased length of stay or death according to a multivariate analysis (OR: 9.417; 95% CI, 2.647-33.506; p = 0.0005 and OR: 6.257; 95% CI, 1.049-37.316; p = 0.044, respectively). This study enabled us to better characterize changes in gene expression and signalling pathways related to hypercoagulable and thrombotic conditions in COVID-19. In this study we identified and validated miRNAs which could serve as novel, thrombosis-related predictive biomarkers of the COVID-19 complications, and can be used for early stratification of patients and prediction of severity of infection development in an individual.Abbreviations: ACE2, angiotensin-converting enzyme 2AF, atrial fibrillationAPP, Amyloid Beta Precursor ProteinaPTT, activated partial thromboplastin timeAUC, Area under the curveAβ, amyloid betaBMI, body mass indexCAD, coronary artery diseaseCALM1, Calmodulin 1 geneCaM, calmodulinCCND1, Cyclin D1CI, confidence intervalCOPD, chronic obstructive pulmonary diseaseCOVID-19, Coronavirus disease 2019CRP, C-reactive proteinCV, CardiovascularCVDs, cardiovascular diseasesDE, differentially expressedDM, diabetes mellitusEGFR, Epithelial growth factor receptorELAVL1, ELAV Like RNA Binding Protein 1FLNA, Filamin AFN1, Fibronectin 1GEO, Gene Expression OmnibushiPSC-CMs, Human induced pluripotent stem cell-derived cardiomyocytesHSP90AA1, Heat Shock Protein 90 Alpha Family Class A Member 1Hsp90α, heat shock protein 90αICU, intensive care unitIL, interleukinIQR, interquartile rangelncRNAs, long non-coding RNAsMI, myocardial infarctionMiRNA, MiR, microRNAmRNA, messenger RNAncRNA, non-coding RNANERI, network-medicine based integrative approachNF-kB, nuclear factor kappa-light-chain-enhancer of activated B cellsNPV, negative predictive valueNXF, nuclear export factorPBMCs, Peripheral blood mononuclear cellsPCT, procalcitoninPPI, Protein-protein interactionsPPV, positive predictive valuePTEN, phosphatase and tensin homologqPCR, quantitative polymerase chain reactionROC, receiver operating characteristicSARS-CoV-2, severe acute respiratory syndrome coronavirus 2SD, standard deviationTLR4, Toll-like receptor 4TM, thrombomodulinTP53, Tumour protein P53UBC, Ubiquitin CWBC, white blood cells.

Transcriptomic analysis of elderly women with low muscle mass: association with immune system pathway

Despite the well-established association of gene expression deregulation with low muscle mass (LMM), the associated biological mechanisms remain unclear. Transcriptomic studies are capable to identify key mediators in complex diseases. We aimed to identify relevant mediators and biological mechanisms associated with age-related LMM. LMM-associated genes were detected by logistic regression using microarray data of 20 elderly women with LMM and 20 age and race-matched controls extracted from our SPAH Study (GSE152073). We performed weighted gene co-expression analysis (WGCNA) that correlated the identified gene modules with laboratorial characteristics. Gene enrichment analysis was performed and an LMM predictive model was constructed using Support Vector Machine (SVM). Overall, 821 discriminating transcripts clusters were identified (|beta coefficient| >1; p-value <0.01). From this list, 45 predictors of LMM were detected by SVM and validated with 0.7 of accuracy. Our results revealed that the well-described association of inflammation, immunity and metabolic alterations is also relevant at transcriptomic level. WGCNA highlighted a correlation of genes modules involved in immunity pathways with vitamin D level (R = 0.63, p = 0.004) and the Agatston score (R = 0.51, p = 0.02). Our study generated a predicted regulatory network and revealed significant metabolic pathways related to aging processes, showing key mediators that warrant further investigation.

Gonadotropin-releasing hormone receptor pathway affects the function of human EBV-transformed B lymphocytes in an age-independent way

Immune system function changes during aging, but the molecular mechanisms of this phenomenon are not fully understood. The present study identified pathways that are associated with age-associated changes in human B lymphocytes. Initial in silico analysis of 1355 genes involved in aging revealed the strongest association (p = 4.36E-21) with the gonadotropin-releasing hormone receptor (GnRHR) pathway. Extended analysis of 2736 aging-related genes using updated databases confirmed such association (p = 2.41E-16). Genes involved in both aging and the GnRHR pathway were significantly involved in lymphocyte B and T activation and aging-related phenotypes, including hyperinsulinemia and diabetes, arthritis, cerebrovascular disease, and cancers. We, therefore, examined non-tumorigenic Epstein-Barr virus (EBV)-transformed B-lymphocyte cell lines that originated from 12 young subjects (20-31 years old) and 10 centenarians (100-102 years old). Gonadotropin-releasing hormone I (GnRH-I) and GnRHR levels did not depend on the age of the cell donors. Inhibition of the GnRHR pathway age-independently decreased cell proliferation (p < 0.001) and increased apoptosis (p < 0.001). However, the decrease in immunoglobulin G synthesis (p < 0.01) was twice as high in centenarian cells than in young cells. In conclusion, the GnRHR pathway regulated essential properties of B lymphocytes. However, upon EBV transformation, memory class-switched B cells became the dominant cell subpopulation. Therefore, the observed effects of GnRHR inhibition were attributable to this subpopulation.

ACE2 Interaction Networks in COVID-19: A Physiological Framework for Prediction of Outcome in Patients with Cardiovascular Risk Factors

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease 2019; COVID-19) is associated with adverse outcomes in patients with cardiovascular disease (CVD). The aim of the study was to characterize the interaction between SARS-CoV-2 and Angiotensin-Converting Enzyme 2 (ACE2) functional networks with a focus on CVD.

METHODS

Using the network medicine approach and publicly available datasets, we investigated ACE2 tissue expression and described ACE2 interaction networks that could be affected by SARS-CoV-2 infection in the heart, lungs and nervous system. We compared them with changes in ACE-2 networks following SARS-CoV-2 infection by analyzing public data of human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). This analysis was performed using the Network by Relative Importance (NERI) algorithm, which integrates protein-protein interaction with co-expression networks. We also performed miRNA-target predictions to identify which miRNAs regulate ACE2-related networks and could play a role in the COVID19 outcome. Finally, we performed enrichment analysis for identifying the main COVID-19 risk groups.

RESULTS

We found similar ACE2 expression confidence levels in respiratory and cardiovascular systems, supporting that heart tissue is a potential target of SARS-CoV-2. Analysis of ACE2 interaction networks in infected hiPSC-CMs identified multiple hub genes with corrupted signaling which can be responsible for cardiovascular symptoms. The most affected genes were EGFR (Epidermal Growth Factor Receptor), FN1 (Fibronectin 1), TP53, HSP90AA1, and APP (Amyloid Beta Precursor Protein), while the most affected interactions were associated with MAST2 and CALM1 (Calmodulin 1). Enrichment analysis revealed multiple diseases associated with the interaction networks of ACE2, especially cancerous diseases, obesity, hypertensive disease, Alzheimer's disease, non-insulin-dependent diabetes mellitus, and congestive heart failure. Among affected ACE2-network components connected with the SARS-Cov-2 interactome, we identified AGT (Angiotensinogen), CAT (Catalase), DPP4 (Dipeptidyl Peptidase 4), CCL2 (C-C Motif Chemokine Ligand 2), TFRC (Transferrin Receptor) and CAV1 (Caveolin-1), associated with cardiovascular risk factors. We described for the first time miRNAs which were common regulators of ACE2 networks and virus-related proteins in all analyzed datasets. The top miRNAs regulating ACE2 networks were miR-27a-3p, miR-26b-5p, miR-10b-5p, miR-302c-5p, hsa-miR-587, hsa-miR-1305, hsa-miR-200b-3p, hsa-miR-124-3p, and hsa-miR-16-5p.

CONCLUSION

Our study provides a complete mechanistic framework for investigating the ACE2 network which was validated by expression data. This framework predicted risk groups, including the established ones, thus providing reliable novel information regarding the complexity of signaling pathways affected by SARS-CoV-2. It also identified miRNAs that could be used in personalized diagnosis in COVID-19.