Alterations in Circulating MicroRNAs and the Relation of MicroRNAs to Maximal Oxygen Consumption and Intima-Media Thickness in Ultra-Marathon Runners

Non-coding RNAs in exercise immunology: A systematic review

Regular physical exercise has been recognized as a potent modulator of immune function, with its effects including enhanced immune surveillance, reduced inflammation, and improved overall health. While strong evidence exists that physical exercise affects the specific expression and activity of non-coding RNAs (ncRNAs) also involved in immune system regulation, heterogeneity in individual study designs and analyzed exercise protocols exists, and a condensed list of functional, exercise-dependent ncRNAs with known targets in the immune system is missing from the literature. A systematic review and qualitative analysis was used to identify and categorize ncRNAs participating in immune modulation by physical exercise. Two combined approaches were used: (a) a systematic literature search for "ncRNA and exercise immunology", (b) and a database search for microRNAs (miRNAs) (miRTarBase and DIANA-Tarbase v8) aligned with known target genes in the immune system based on the Reactome database, combined with a systematic literature search for "ncRNA and exercise". Literature searches were based on PubMed, Web of Science, and SPORTDiscus; and miRNA databases were filtered for targets validated by in vitro experimental data. Studies were eligible if they reported on exercise-based interventions in healthy humans. After duplicate removal, 95 studies were included reporting on 164 miRNAs, which were used for the qualitative synthesis. Six studies reporting on long-noncoding RNAs (lncRNAs) or circular RNAs were also identified. Results were analyzed using ordering tables that included exercise modality (endurance/resistance exercise), acute or chronic interventions, as well as the consistency in reported change between studies. Evaluation criteria were defined as "validated" with 100% of ≥3 independent studies showing identical direction of regulation, "plausible" (≥80%), or "suggestive" (≥70%). For resistance exercise, upregulation of miR-206 was validated while downregulation of miR-133a appeared plausible. For endurance exercise, 15 miRNAs were categorized as validated, with 12 miRNAs being consistently elevated and 3 miRNAs being downregulated, most of them after acute exercise training. In conclusion, our approach provides evidence that miRNAs play a major role in exercise-induced effects on the innate and adaptive immune system by targeting different pathways affecting immune cell distribution, function, and trafficking as well as production of (anti-)inflammatory cytokines. miRNAs miR-15, miR-29c, miR-30a, miR-142/3, miR-181a, and miR-338 emerged as key players in mediating the immunomodulatory effects of exercise predominantly after acute bouts of endurance exercise.

Circular RNAs in Ischemic Stroke: Biological Role and Experimental Models

Ischemic stroke is among the leading causes of morbidity, disability, and mortality worldwide. Despite the recent progress in the management of acute ischemic stroke, timely intervention still represents a challenge. Hence, strategies to counteract ischemic brain injury during and around the acute event are still lacking, also due to the limited knowledge of the underlying mechanisms. Despite the increasing understanding of the complex pathophysiology underlying ischemic brain injury, some relevant pieces of information are still required, particularly regarding the fine modulation of biological processes. In this context, there is emerging evidence that the modulation of circular RNAs, a class of highly conserved non-coding RNA with a closed-loop structure, are involved in pathophysiological processes behind ischemic stroke, unveiling a number of potential therapeutic targets and possible clinical biomarkers. This paper aims to provide a comprehensive overview of experimental studies on the role of circular RNAs in ischemic stroke.

Physical exercise and the functions of microRNAs

MicroRNAs (miRNAs) control RNA translation and are a class of small, tissue-specific, non-protein-coding RNAs that maintain cellular homeostasis through negative gene regulation. Maintenance of the physiological environment depends on the proper control of miRNA expression, as these molecules influence almost all genetic pathways, from the cell cycle checkpoint to cell proliferation and apoptosis, with a wide range of target genes. Dysregulation of the expression of miRNAs is correlated with several types of diseases, acting as regulators of cardiovascular functions, myogenesis, adipogenesis, osteogenesis, hepatic lipogenesis, and important brain functions. miRNAs can be modulated by environmental factors or external stimuli, such as physical exercise, and can eventually induce specific and adjusted changes in the transcriptional response. Physical exercise is used as a preventive and non-pharmacological treatment for many diseases. It is well established that physical exercise promotes various benefits in the human body such as muscle hypertrophy, mental health improvement, cellular apoptosis, weight loss, and inhibition of cell proliferation. This review highlights the current knowledge on the main miRNAs altered by exercise in the skeletal muscle, cardiac muscle, bone, adipose tissue, liver, brain, and body fluids. In addition, knowing the modifications induced by miRNAs and relating them to the results of prescribed physical exercise with different protocols and intensities can serve as markers of physical adaptation to training and responses to the effects of physical exercise for some types of chronic diseases. This narrative review consists of randomized exercise training experiments with humans and/or animals, combined with analyses of miRNA modulation.

Diagnostic Performance of Circulating miRNAs and Extracellular Vesicles in Acute Ischemic Stroke

Background: Increased inflammation activates blood coagulation system, higher platelet activation plays a key role in the pathophysiology of ischemic stroke (IS). During platelet activation and aggregation process, platelets may cause increased release of several proinflammatory, and prothrombotic mediators, including microRNAs (miRNAs) and extracellular vesicles (EVs). In the current study we aimed to assess circulating miRNAs profile related to platelet function and inflammation and circulating EVs from platelets, leukocytes, and endothelial cells to analyse their diagnostic and predictive utility in patients with acute IS. Methods: The study population consisted of 28 patients with the diagnosis of the acute IS. The control group consisted of 35 age- and gender-matched patients on acetylsalicylic acid (ASA) therapy without history of stroke and/or TIA with established stable coronary artery disease (CAD) and concomitant cardiovascular risk factors. Venous blood samples were collected from the control group and patients with IS on ASA therapy (a) 24 h after onset of acute IS, (b) 7-days following index hospitalization. Flow cytometry was used to determine the concentration of circulating EVs subtypes (from platelets, leukocytes, and endothelial cells) in platelet-depleted plasma and qRT-PCR was used to determine several circulating plasma miRNAs (miR-19a-3p, miR-186-5p and let-7f). Results: Patients with high platelet reactivity (HPR, based on arachidonic acid-induced platelet aggregometry) had significantly elevated platelet-EVs (CD62+) and leukocyte-EVs (CD45+) concentration compared to patients with normal platelet reactivity at the day of 1 acute-stroke (p = 0.012, p = 0.002, respectively). Diagnostic values of baseline miRNAs and EVs were evaluated with receiver operating characteristic (ROC) curve analysis. The area under the ROC curve for miR-19a-3p was 0.755 (95% CI, 0.63–0.88) p = 0.004, for let-7f, it was 0.874 (95% CI, 0.76–0.99) p = 0.0001; platelet-EVs was 0.776 (95% CI, 0.65–0.90) p = 0.001, whereas for leukocyte-EVs, it was 0.715 (95% CI, 0.57–0.87) p = 0.008. ROC curve showed that pooling the miR-19a-3p expressions, platelet-EVs, and leukocyte-EVs concentration yielded a higher AUC than the value of each individual biomarker as AUC was 0.893 (95% CI, 0.79–0.99). Patients with moderate stroke had significantly elevated miR-19a-3p expression levels compared to patients with minor stroke at the first day of IS. (AUC: 0.867, (95% CI, 0.74–0.10) p = 0.001). Conclusion: Combining different biomarkers of processes underlying IS pathophysiology might be beneficial for early diagnosis of ischemic events. Thus, we believe that in the future circulating biomarkers might be used in the prehospital phase of IS. In particular, circulating plasma EVs and non-coding RNAs including miRNAs are interesting candidates as bearers of circulating biomarkers due to their high stability in the blood and making them highly relevant biomarkers for IS diagnostics.

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