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1.
Nutrients ; 14(24)2022 Dec 18.
Article in English | MEDLINE | ID: covidwho-2163542

ABSTRACT

COVID-19 and imposed restrictions are linked with numerous health consequences, especially among endurance athletes (EA). Unfavorable changes in physical activity and nutrition may affect later sports and competition performance. The aims of this study were: (1) to assess the impact of COVID-19 infection and pandemic restrictions on the nutrition and physical activity of EAs and (2) to compare them with the results of cardiopulmonary exercise testing (CPET). In total, 49 EAs (nmale = 43, nfemale = 6, mean age = 39.9 ± 7.8 year., height = 178.4 ± 6.8 cm, weight = 76.3 ± 10.4 kg; BMI = 24.0 ± 2.6 kg·m−2) underwent pre- and post-COVID-19 CPET and fulfilled the dietary and physical activity survey. COVID-19 infection significantly deteriorated CPET performance. There was a reduction in oxygen uptake and in heart rate post-COVID-19 (both p < 0.001). Consuming processed meat and replacing meat with plant-based protein affected blood lactate concentration (p = 0.035). Fat-free mass was linked with consuming unsaturated fatty acids (p = 0.031). Adding salt to meals influenced maximal speed/power (p = 0.024) and breathing frequency (p = 0.033). Dietary and Fitness Practitioners and Medical Professionals should be aware of possible COVID-19 infection and pandemic consequences among EA. The results of this study are a helpful guideline to properly adjust the treatment, nutrition, and training of EA.


Subject(s)
COVID-19 , Physical Endurance , Humans , Adult , Middle Aged , Physical Endurance/physiology , Exercise/physiology , Nutritional Status , Athletes
2.
RNA Biol ; 19(1): 963-979, 2022 01.
Article in English | MEDLINE | ID: covidwho-1978152

ABSTRACT

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 curveAß, 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.


Subject(s)
COVID-19 , Induced Pluripotent Stem Cells , MicroRNAs , Thrombosis , Amyloid beta-Peptides , Angiotensin-Converting Enzyme 2 , Biomarkers , COVID-19/genetics , Heat-Shock Proteins , Humans , Induced Pluripotent Stem Cells/metabolism , Leukocytes, Mononuclear/metabolism , MicroRNAs/genetics , MicroRNAs/metabolism , SARS-CoV-2/genetics , Severity of Illness Index , Thrombosis/genetics
3.
J Clin Med ; 10(12)2021 Jun 08.
Article in English | MEDLINE | ID: covidwho-1264479

ABSTRACT

Atherosclerotic cardiovascular diseases (ASCVD) are the major cause of mortality worldwide. Despite the continuous progress in ASCVD therapy, the residual risk persists beyond the management of traditional risk factors. Several infections including Helicobacter pylori infection, periodontal disease, and viral infections are associated with the increased risk of ASCVD, both directly by damage to the heart muscle and vasculature, and indirectly by triggering a systemic proinflammatory state. Hence, beyond the optimal management of the traditional ASCVD risk factors, infections should be considered as an important non-classical risk factor to enable early diagnosis and appropriate treatment. Here, we summarized the currently available evidence regarding the role of inflammation in ASCVD and the association between the particular infections and pathogens (Helicobacter pylori, periodontal disease, pneumonia, Cytomegalovirus, Human immunodeficiency virus, Herpes simplex virus, and severe acute respiratory syndrome coronavirus 2) on the development and progression of ASCVD. We also speculated about the potential therapeutic implications of the anti-inflammatory and anti-infective drugs on ASCVD outcomes, including drugs routinely administered in patients with ASCVD (statins, P2Y12 receptor inhibitors, and angiotensin-converting enzyme inhibitors/angiotensin receptor blockers) and novel strategies aiming at residual risk reduction (colchicine, anti-cytokine drugs, and methotrexate). Considering the emerging association between infections and ASCVD, it is crucial to determine the possible advantages of infection prevention and treatment in patients with ASCVD.

4.
Front Med (Lausanne) ; 7: 607786, 2020.
Article in English | MEDLINE | ID: covidwho-1069727

ABSTRACT

Background: Most respiratory viruses show pronounced seasonality, but for SARS-CoV-2, this still needs to be documented. Methods: We examined the disease progression of COVID-19 in 6,914 patients admitted to hospitals in Europe and China. In addition, we evaluated progress of disease symptoms in 37,187 individuals reporting symptoms into the COVID Symptom Study application. Findings: Meta-analysis of the mortality risk in seven European hospitals estimated odds ratios per 1-day increase in the admission date to be 0.981 (0.973-0.988, p < 0.001) and per increase in ambient temperature of 1°C to be 0.854 (0.773-0.944, p = 0.007). Statistically significant decreases of comparable magnitude in median hospital stay, probability of transfer to the intensive care unit, and need for mechanical ventilation were also observed in most, but not all hospitals. The analysis of individually reported symptoms of 37,187 individuals in the UK also showed the decrease in symptom duration and disease severity with time. Interpretation: Severity of COVID-19 in Europe decreased significantly between March and May and the seasonality of COVID-19 is the most likely explanation.

5.
J Clin Med ; 9(11)2020 Nov 21.
Article in English | MEDLINE | ID: covidwho-945845

ABSTRACT

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.

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