Omega-3 to omega-6 fatty acid oxidation ratio as a novel inflammation resolution marker for metabolic complications in obesity.

BACKGROUND AND AIMS: The oxidative metabolism of polyunsaturated fatty acids (PUFAs) leads to bioactive isoprostanoids. The aim was to establish the associations of a complete urinary isoprostanoid profiling in a cohort study of carefully phenotyped obese subjects to determine possible potential differential implications for omega-6 PUFA- and omega-3 PUFA-derived isoprostanoids for obesity, metabolic indicators, and inflammation. METHODS AND RESULTS: PUFA peroxidation compounds were determined in urine samples from obese human subjects (n = 46) by liquid chromatography coupled to tandem mass spectrometry. Increased omega-6 arachidonic acid (AA) oxidation, mainly represented by 5-F2c isoprostane (5-F2c-IsoP) and metabolites of 15-F2t-IsoP, was associated with body mass index, glycated hemoglobin (HbA1c) and mean arterial blood pressure. In addition, we identified the omega-3 PUFA-derived urinary metabolites 14-F4t-NeuroP from docosahexaenoic acid (DHA) and 5-F3t-IsoP from eicosapentaenoic acid (EPA), which declined with age. The omega-3 to omega-6 oxidation ratio was a significant predictor of inflammation in obesity. CONCLUSION: The findings point to full urinary isoprostanoid profiling as a more sensitive measure of PUFA oxidative stress in obesity-induced metabolic complications compared with individual isoprostanoid measures. Furthermore, the results suggest the balance between the omega-3 and omega-6 PUFA oxidation as determinative for the consequences of oxidative stress on inflammation in obesity.

Decreased oxidative stress and altered urinary oxylipidome by intravenous omega-3 fatty acid emulsion in a randomized controlled trial of older subjects hospitalized for COVID-19.

Proinflammatory bioactive lipid mediators and oxidative stress are increased in coronavirus disease 2019 (COVID-19). The randomized controlled single-blind trial COVID-Omega-F showed that intravenous omega-3 polyunsaturated fatty acids (n-3 PUFA) shifted the plasma lipid signature of COVID-19 towards increased proresolving precursor levels and decreased leukotoxin diols, associated with a beneficial immunodulatory response. The present study aimed to determine the effects of n-3 PUFA on the urinary oxylipidome and oxidative stress in COVID-19. From the COVID-Omega-F trial, 20 patients hospitalized for COVID-19 had available serial urinary samples collected at baseline, after 24-48 h, and after completing 5 days treatment with one daily intravenous infusion (2 mL/kg) of either placebo (NaCl; n = 10) or a lipid emulsion containing 10 g of n-3 PUFA per 100 mL (n = 10). Urinary eicosanoids and isoprostanes were analyzed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Erythrocytes obtained at the different time-points from n = 10 patients (n = 5 placebo and n = 5 n-3 PUFA) were used for determination of reactive oxygen species. Intravenous n-3 PUFA emulsion administration altered eicosanoid metabolites towards decreased levels for mediators of inflammation and thrombosis, and increased levels of the endothelial function mediator prostacyclin. Furthermore, non-enzymatic metabolism was skewed towards n-3 PUFA-derived metabolites with potential anti-inflammatory and pro-resolving effects. The oxidative stress marker 15-F2t-isoprostane was significantly lower in patients receiving n-3 PUFA treatment, who also exhibited significantly decreased erythrocyte oxidative stress compared with placebo-treated patients. These findings point to additional beneficial effects of intravenous n-3 PUFA emulsion treatment through a beneficial oxylipin profile and decreased oxidative stress in COVID-19.

Incidence, associated outcomes, and predictors of upper gastrointestinal bleeding following acute myocardial infarction: a SWEDEHEART-based nationwide cohort study.

AIMS: Of all spontaneous bleeding complications in patients with acute myocardial infarction (MI), upper gastrointestinal bleeding (UGIB) is common and of specific interest since it could be prevented by several prophylactic measures. We aimed to determine the incidence, associated outcomes, and predictors of UGIB following acute MI. METHODS AND RESULTS: All patients with acute MI enrolled in the SWEDEHEART (Swedish Web-system for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies) registry from January 2007 to June 2016 and discharged alive on any antithrombotic therapy (n = 149 477) were followed regarding UGIB for 1 year. Associated outcomes were determined by Cox proportional hazards regression with UGIB as a time-dependent covariate, adjusting for baseline characteristics, invasive treatment, and medical treatment at discharge. Predictors of UGIB were determined by logistic regression and machine learning models.At 1 year, UGIB had occurred in 2230 patients (cumulative incidence 1.5%) and was significantly associated with an increased risk of all-cause death [hazard ratio (HR) 2.86, 95% confidence interval (CI) 2.58-3.16] and stroke (HR 1.80, 95% CI 1.32-2.45) but not with recurrent MI (HR 1.17, 95% CI 0.97-1.42). The most important predictors of UGIB were haemoglobin, age, systolic blood pressure, blood glucose, smoking status, previous upper gastrointestinal bleeding, and antithrombotic and gastroprotective treatment. CONCLUSION: After acute MI, readmission because of UGIB is common and significantly associated with poor prognosis. By using machine learning in addition to traditional logistic regression, new predictors of UGIB, such as blood glucose and smoking status, were identified.

Artificial Intelligence Models Reveal Sex-Specific Gene Expression in Aortic Valve Calcification.

Male and female aortic stenosis patients have distinct valvular phenotypes, increasing the complexities in the evaluation of valvular pathophysiology. In this study, we present cutting-edge artificial intelligence analyses of transcriptome-wide array data from stenotic aortic valves to highlight differences in gene expression patterns between the sexes, using both sex-differentiated transcripts and unbiased gene selections. This approach enabled the development of efficient models with high predictive ability and determining the most significant sex-dependent contributors to calcification. In addition, analyses of function-related gene groups revealed enriched fibrotic pathways among female patients. Ultimately, we demonstrate that artificial intelligence models can be used to accurately predict aortic valve calcification by carefully analyzing sex-specific gene transcripts.

Cardiovascular Autonomic Function Changes and Predictors During a 2-Year Physical Activity Program in Rheumatoid Arthritis: A PARA 2010 Substudy.

Background: Chronic inflammation leads to autonomic dysfunction, which may contribute to the increased risk of cardiovascular diseases (CVD) in patients with rheumatoid arthritis (RA). Exercise is known to restore autonomic nervous system (ANS) activity and particularly its parasympathetic component. A practical clinical tool to assess autonomic function, and in particular parasympathetic tone, is heart rate recovery (HRR). The aim of this substudy from the prospective PARA 2010 study was to determine changes in HRR post-maximal exercise electrocardiogram (ECG) after a 2-year physical activity program and to determine the main predictive factors associated with effects on HRR in RA. Methods: Twenty-five participants performed physiotherapist-guided aerobic and muscle-strengthening exercises for 1 year and were instructed to continue the unsupervised physical activity program autonomously in the next year. All participants were examined at baseline and at years 1 and 2 with a maximal exercise ECG on a cycle ergometer. HRR was measured at 1, 2, 3, 4, and 5 min following peak heart rate during exercise. Machine-learning algorithms with the elastic net linear regression models were performed to predict changes in HRR1 and HRR2 at 1 year and 2 years of the PARA program. Results: Mean age was 60 years, range of 41-73 years (88% women). Both HRR1 and HRR2 increased significantly from baseline to year 1 with guided physical activity and decreased significantly from year 1 to year 2 with unsupervised physical activity. Blood pressure response to exercise, low BMI, and muscular strength were the best predictors of HRR1/HRR2 increase during the first year and HRR1/HRR2 decrease during the second year of the PARA program. Conclusion: ANS activity in RA assessed by HRR was improved by guided physical activity, and machine learning allowed to identify predictors of the HRR response at the different time points. HRR could be a relevant marker of the effectiveness of physical activity recommended in patients with RA at high risk of CVD. Very inactive and/or high CVD risk RA patients may get substantial benefits from a physical activity program.

Physical Activity Does Not Reduce Aortic Valve Stenosis Incidence.

BACKGROUND: Physical activity is associated with lower risk of coronary and cerebrovascular disease but its potential role in prevention of aortic valve stenosis (AVS) is unclear. Methods and Results: We investigated whether physical activity influences AVS risk in a cohort of 69,288 adults. During a mean follow-up of 15.3 years, 1,238 AVS cases were diagnosed. No associations were observed between AVS and walking/bicycling (≥1 h/day vs. almost never: hazard ratio 0.92, 95% CI 0.74-1.15) or exercise (≥4 hs/week vs. <1 h/week: hazard ratio 1.18, 95% CI 0.97-1.43). CONCLUSIONS: Physical activity did not reduce the incidence of AVS.