Biomarkers In Atrial Fibrillation Research Articles

Association between serum apolipoprotein A1 and atrial fibrillation in the Chinese population: a case–control study

BackgroundThe relationship between serum apolipoprotein A1 (APOA1) and atrial fibrillation (AF) is not known. Therefore, we sought to investigate the associations between APOA1 and AF in the Chinese population.MethodsThis case–control study included 950 patients with AF (29–83 years old, 50.42% male) who were hospitalized consecutively in China between January 2019 and September 2021. Controls with sinus rhythm and without AF were matched (1:1) to cases by sex and age. Pearson correlation analysis was performed to investigate the correlation between APOA1 and blood lipid profiles. Multivariate regression models were used to explore the association between APOA1 and AF. The receiver operator characteristic (ROC) curve was constructed to examine the performance of APOA1.ResultsMultivariate regression analysis showed that low serum APOA1 in men and women with AF was significantly associated with AF (OR = 0.261, 95% CI: 0.162–0.422, P < 0.001). Pearson correlation analysis indicated that serum APOA1 was positively correlated with total cholesterol (TC) (r = 0.456, p < 0.001), low-density lipoprotein cholesterol (LDL-C) (r = 0.825, p < 0.001), high-density lipoprotein cholesterol (HDL-C) (r = 0.238, p < 0.001), and apolipoprotein B (APOB) (r = 0.083, p = 0.011). ROC curve analysis showed that APOA1 levels of 1.105 g/L and 1.205 g/L were the optimal cut-off values for predicting AF in males and females, respectively.ConclusionLow APOA1 in male and female patients is significantly associated with AF in the Chinese population of non-statin users. APOA1 may be a potential biomarker for AF and contribute to the pathological progression of AF along with low blood lipid profiles. Potential mechanisms remain to be further explored.

Circulating miR-20b-5p and miR-330-3p are novel biomarkers for progression of atrial fibrillation: Intracardiac/extracardiac plasma sample analysis by small RNA sequencing.

Circulating microRNAs (miRNAs, miR) have been considered as biomarkers reflecting the underlying pathophysiology in atrial fibrillation (AF). Nevertheless, miRNA expression in the peripheral blood samples might not reflect a cardiac phenomenon since most miRNAs are expressed in numerous organs. This study aimed to identify the cardiac-specific circulating miRNAs as biomarkers for AF. Plasma samples were obtained from a luminal coronary sinus catheter (CS, cardiac-specific samples) and femoral venous sheath (FV, peripheral samples) in patients with AF and paroxysmal supraventricular tachycardia (control, CTL) undergoing catheter ablation. The circulating miRNA profiles were analyzed by small RNA sequencing. Differently expressed miRNAs between AF and CTL were identified in each sample of the CS and FV; miRNAs exhibiting similar expression patterns in the CS and FV samples were selected as candidates for cardiac-specific biomarkers. The selected miRNAs were related to the outcome of catheter ablation of AF. Small RNA sequencing detected 849 miRNAs. Among the top 30 most differently expressed miRNAs between AF and CTL, circulating hsa-miR-20b-5p, hsa-miR-330-3p, and hsa-miR-204-5p had a similar pattern in the CS and FV samples. Another set of peripheral blood samples was obtained from AF patients undergoing catheter ablation (n = 141). The expression of the miR-20b-5p and miR-330-3p, but not the miR-204-5p, negatively correlated with the echocardiographic left-atrial dimension and was decreased in patients with AF recurrence as compared to those without AF recurrence during a 1-year follow-up. Circulating miR-20b-5p and miR-330-3p can be cardiac-specific biomarkers for atrial remodeling progression and arrhythmia recurrence after catheter ablation in AF patients.

The N-Glycosylation of Total Plasma Proteins and IgG in Atrial Fibrillation

Atrial fibrillation is a disease with a complex pathophysiology, whose occurrence and persistence are caused not only by aberrant electrical signaling in the heart, but by the development of a susceptible heart substrate. These changes, such as the accumulation of adipose tissue and interstitial fibrosis, are characterized by the presence of inflammation. N-glycans have shown great promise as biomarkers in different diseases, specifically those involving inflammatory changes. To assess the changes in the N-glycosylation of the plasma proteins and IgG in atrial fibrillation, we analyzed the N-glycosylation of 172 patients with atrial fibrillation, before and six months after a pulmonary vein isolation procedure, with 54 cardiovascularly healthy controls. An analysis was performed using ultra-high-performance liquid chromatography. We found one oligomannose N-glycan structure from the plasma N-glycome and six IgG N-glycans, mainly revolving around the presence of bisecting N-acetylglucosamine, that were significantly different between the case and control groups. In addition, four plasma N-glycans, mostly oligomannose structures and a derived trait that was related to them, were found to be different in the patients who experienced an atrial fibrillation recurrence during the six-month follow-up. IgG N-glycosylation was extensively associated with the CHA2DS2-VASc score, confirming its previously reported associations with the conditions that make up the score. This is the first study looking at the N-glycosylation patterns in atrial fibrillation and warrants further investigation into the prospect of glycans as biomarkers for atrial fibrillation.

Circulating MicroRNAs as Specific Biomarkers in Atrial Fibrillation: A Meta-Analysis.

Atrial fibrillation (AF) is the most frequently occurring supraventricular arrhythmia. Although microRNAs (miRNAs) have been associated with AF pathogenesis, standard protocols for quantifying and selecting specific miRNAs for clinical use as biomarkers should be optimized. In this study, we evaluated the clinical application of miRNAs as biomarkers for the prognosis and diagnosis of AF. Literature searches were conducted on PubMed, Cochrane Library, and EMBASE. We included prospective or retrospective observational studies that had been published as of 14 February 2022; our main objective was to analyze the relationship between circulating miRNAs and AF. The data were extracted using the descriptors "Atrial fibrillation AND miRNA", "Atrial fibrillation AND diagnostic AND miRNA", and "Atrial fibrillation AND prognosis AND miRNA". No filters were applied for period delimitation, type of publication, or language. Studies using samples isolated from blood plasma and TaqMan and RT-qPCR for detecting and quantifying miRNAs were selected, and those that used atrial tissue samples were excluded. We identified 272 articles and excluded 102 duplicated articles. Two authors independently read the titles and abstracts of 170 out of 272 articles and selected 56 potential articles, 6 of which were selected for final review. Our analysis revealed a significant association between AF and miR-4798 [OR = 1.90 (95% CI 1.45-2.47)], AF and miRNA-133a [2.77 (2.73-2.82)], AF and miRNA-150 [3.77 (1.50-9.46); I2 = 70%], AF and miRNA-21 [2.23 (1.20-4.17); I2 = 99%], AF and hsa-miRNA4443 [2.32 (2.20-2.44)], and AF and miR-20a-5p [3.67 (1.42-9.49)]. The association between miRNAs and AF showed an OR of 2.51 [95% CI 1.99-3.16; I2 = 99%]. Our meta-analysis demonstrated that circulating miRNAs are potential biomarkers of AF, as they exhibit stable expression post-sample collection. In addition to regulating cellular processes, such as proliferation, differentiation, development, and cell death, miRNAs were found to be linked to arrhythmia development.

Plasmatic apelin shows a promising potential as a screening biomarker for atrial fibrillation.

Purpose of this study was to evaluate properties of apelin, a peptide detectable in peripheral blood, for atrial fibrillation (AF) detection in a diverse population of patients covering a broad spectrum from healthy to polymorbid patients. AF is the most common cardiac arrhythmia with constantly increasing incidence and prevalence. Currently available diagnostic tools do not provide sufficient detection rate. Large proportion of patients with AF remains undiagnosed and the possibility of screening at-risk groups would be significantly beneficial. We designed this study as a multi-centre retrospective study. Study population included 183 patients. 64 in non-AF and 119 in AF group. Apelin plasma concentration was significantly lower in AF group comparedto non-AF group(p <0.001).Receiver operating characteristic analysis ofapelin as a predictor of AF scored area under the curve of0.79,sensitivity=0.941and specificity=0.578.Multivariate analysis using logistic regression adjusted for age, BMI, apelin, dilated LV, dilated LA, arterial hypertension, and gender showed only apelin and age to be statistically significant contributors for AF. Apelin might be a promising biomarker for detecting AF in our study population. These results suggest promising potential of apelin as a screening biomarker for AF (Tab. 2, Fig. 1, Ref. 46). Text in PDF www.elis.sk Keywords: biomarker, apelin, arrhythmia, atrial fibrillation.

Dysregulation of Fatty Acid Binding Protein and Its Relationship With Inflammatory Biomarkers in Atrial Fibrillation and Renal Dysfunction

Dysregulation of Fatty Acid Binding Protein and Its Relationship With Inflammatory Biomarkers in Atrial Fibrillation and Renal Dysfunction

Systemic immune inflammation index and system inflammation response index are potential biomarkers of atrial fibrillation among the patients presenting with ischemic stroke

BackgroundChronic inflammatory disorders in atrial fibrillation (AF) contribute to the onset of ischemic stroke. Systemic immune inflammation index (SIII) and system inflammation response index (SIRI) are the two novel and convenient measurements that are positively associated with body inflammation. However, little is known regarding the association between SIII/SIRI with the presence of AF among the patients with ischemic stroke.MethodsA total of 526 ischemic stroke patients (173 with AF and 353 without AF) were consecutively enrolled in our study from January 2017 to June 2019. SIII and SIRI were measured in both groups. Logistic regression analysis was used to analyse the potential association between SIII/SIRI and the presence of AF. Finally, the correlation between hospitalization expenses, changes in the National Institutes of Health Stroke Scale (NIHSS) scores and SIII/SIRI values were measured.ResultsIn patients with ischemic stroke, SIII and SIRI values were significantly higher in AF patients than in non-AF patients (all p < 0.001). Moreover, with increasing quartiles of SIII and SIRI in all patients, the proportion of patients with AF was higher than that of non-AF patients gradually. Logistic regression analyses demonstrated that log-transformed SIII and log-transformed SIRI were independently associated with the presence of AF in patients with ischemic stroke (log-transformed SIII: odds ratio [OR]: 1.047, 95% confidence interval CI = 0.322–1.105, p = 0.047; log-transformed SIRI: OR: 6.197, 95% CI = 2.196–17.484, p = 0.001). Finally, a positive correlation between hospitalization expenses, changes in the NIHSS scores and SIII/SIRI were found, which were more significant in patients with AF (all p < 0.05).ConclusionsOur study suggests SIII and SIRI are convenient and effective measurements for predicting the presence of AF in patients with ischemic stroke. Moreover, they were correlated with increased financial burden and poor short-term prognosis in AF patients presenting with ischemic stroke.

Association between serum apolipoprotein B and atrial fibrillation: a case–control study

The relationship between apolipoprotein B (APOB) and atrial fibrillation (AF) is less well-known. We aimed to investigate the association between APOB and AF by gender. We conducted a case–control study including 1913 consecutive hospitalized patients to analyze the association between APOB and AF. 950 AF patients and 963 age-, sex-matched non-AF patients with sinus rhythm were evaluated. T-test, Mann–Whitney test, ANOVA, and Chi-square analysis were performed to analyze baseline data and intergroup comparisons. Pearson's correlation tests or Spearman correlation tests were performed to determine the interrelationships. Multiple regression analysis was performed to adjust for covariables. The receiver operator characteristic (ROC) curve was constructed to examine the performance of APOB. AF patients had lower APOB (P < 0.001) and an independent negative association between APOB and AF in both genders adjusting for confounding factors (OR 0.121, 95% CI 0.067–0.220, P < 0.001), regardless of statin use. APOB was positively correlated with total cholesterol (TC) (r = 0.529, p < 0.001), low-density lipoprotein cholesterol (LDL-C) (r = 0.545, p < 0.001), apolipoprotein A1 (APOA1) (r = 0.083, p < 0.001), and albumin (ALB) (r = 0.134, p < 0.001). ROC curve analysis showed that APOB level = 0.895 g/L was the most optimal cut-off value, the area under the ROC curve was 0.722. This study shows a protective association of APOB with AF in men and women. It implies APOB may be a potential biomarker for AF with a promising cut-off point of 0.895 g/L and may involve initiating and maintaining AF along with several metabolic factors.

Analysis of potential genetic biomarkers using machine learning methods and immune infiltration regulatory mechanisms underlying atrial fibrillation

ObjectiveWe aimed to screen out biomarkers for atrial fibrillation (AF) based on machine learning methods and evaluate the degree of immune infiltration in AF patients in detail.MethodsTwo datasets (GSE41177 and GSE79768) related to AF were downloaded from Gene expression omnibus (GEO) database and merged for further analysis. Differentially expressed genes (DEGs) were screened out using “limma” package in R software. Candidate biomarkers for AF were identified using machine learning methods of the LASSO regression algorithm and SVM-RFE algorithm. Receiver operating characteristic (ROC) curve was employed to assess the diagnostic effectiveness of biomarkers, which was further validated in another independent validation dataset of GSE14975. Moreover, we used CIBERSORT to study the proportion of infiltrating immune cells in each sample, and the Spearman method was used to explore the correlation between biomarkers and immune cells.Results129 DEGs were identified, and CYBB, CXCR2, and S100A4 were identified as key biomarkers of AF using LASSO regression and SVM-RFE algorithm. Both in the training dataset and the validation dataset, CYBB, CXCR2, and S100A4 showed favorable diagnostic effectiveness. Immune infiltration analysis indicated that, compared with sinus rhythm (SR), the atrial samples of patients with AF contained a higher T cells gamma delta, neutrophils and mast cells resting, whereas T cells follicular helper were relatively lower. Correlation analysis demonstrated that CYBB, CXCR2, and S100A4 were significantly correlated with the infiltrating immune cells.ConclusionsIn conclusion, this study suggested that CYBB, CXCR2, and S100A4 are key biomarkers of AF correlated with infiltrating immune cells, and infiltrating immune cells play pivotal roles in AF.

Pericardial Fluid Annexin A1 Is a Marker of Atrial Fibrillation in Aortic Stenosis: A Proteomics Analysis.

Atrial fibrillation (AF) is the most common arrhythmia with adverse clinical outcomes. Pericardial fluid (PF) mirrors the heart’s pathophysiological status due to its proximity. This study aimed to characterise the PF proteome to identify new biomarkers of disease. Eighty-three patients submitted to aortic valve replacement surgery with severe aortic stenosis were selected, and their baseline echocardiographic and clinical variables were documented. Thirteen samples were selected blindly for proteome characterisation following a shotgun (GeLC–MS/MS) and a label-free quantification approach (LFQ). According to previous AF history, a partial least squares discriminant analysis (PLS-DA) was conducted, and the top 15 variables important in projection were identified. To inquire potential biomarkers, ROC curves were designed using LFQ data. Target proteins were further validated by ELISA, in both pericardial fluid and serum. Proteome analysis uncovered nine proteins up- and downregulated ≥2-fold. Annexin A1, annexin A2, and vimentin were among the top 15 most important variables for group discrimination in PLS-DA. Protein—protein interaction and gene ontology enrichment analysis presented functional interaction among identified proteins, which were all part of focal adhesion sites. Annexin A1 was increased in the pericardial fluid of AF patients but not in serum when quantified by ELISA. Annexin A1 is a novel pericardial fluid biomarker of AF in patients with severe aortic stenosis.

Identification of a Novel 4-gene Diagnostic Model for Atrial Fibrillation Risk Based on Integrated Analysis Across Independent Data Sets.

Atrial fibrillation (AF) is the most common persistent arrhythmia and an important factor leading to cardiovascular morbidity and mortality. Several key genes and diagnostic markers have been discovered with the development of advanced modern molecular biology techniques, but the etiology and pathogenesis of AF remained unknown. In this study, three-chip-seq data sets and an RNA-seq data set were integrated as a comprehensive network for pathway analysis of the biological functions of related genes in AF, hoping to provide a better understanding of the etiology and pathogenesis of AF. Differential co-expression analysis identified 360 genes with specific expression in AF, and functional enrichment analysis further revealed that these genes were significantly correlated with focal expression (p <0.01), autophagy (p <0.01), and thyroid cancer. In addition, Af-specific proteinprotein interaction (PPI) networks were constructed based on AF-specific expression genes. Network topology analysis identified PLEKHA7, YWHAQ, PPP1CB, WDR1, AKT1, IGF1R, CANX, MAPK1, SRPK2 and SRSF10 genes as hub genes of the networks, and they were considered as potential biomarkers of AF because they were found to participate in the development of AF through Oocyte meiosis and focal expression. Finally, a diagnostic model for AF established with a support vector machine (SVM) demonstrated excellent predictive performance in internal and external data sets (AUC>0.9) and different platform data sets (mean AUC>0.75). Finally, a diagnostic model for AF was established, thus showing its potential in the early identification and prediction of AF.

Galectin-3 enhances atrial remodelling and arrhythmogenesis through CD98 signalling.

Galectin-3 (Gal-3) is a biomarker of atrial fibrillation (AF) that mediates atrial inflammation. CD98 is the membrane surface receptor for Gal-3. Nevertheless, the role of the Gal-3/CD98 axis in atrial arrhythmogenesis is unclear. In this study, we investigated the effects of Gal-3/CD98 signalling on atrial pathogenesis. Whole cell patch clamp and western blotting were used to analyse calcium/potassium homeostasis and calcium-related signalling in Gal-3-administrated HL-1 atrial cardiomyocytes with/without CD98 neutralized antibodies. Telemetry electrocardiographic recording, Masson's trichrome staining and immunohistochemistry staining of atrium were obtained from mice having received tail-vein injections with Gal-3. Gal-3-treated HL-1 myocytes had a shorter action potential duration, smaller L-type calcium current, increased sarcoplasmic reticulum (SR) calcium content, Na+ /Ca2+ exchanger (NCX) current, transient outward potassium current, and ultrarapid delayed rectifier potassium current than control cells had. Gal-3-treated HL-1 myocytes had greater levels of SR Ca2+ ATPase, NCX, Nav1.5, and NLR family pyrin domain containing 3 (NLRP3) expression and increased calcium/calmodulin-dependent protein kinase II (CaMKII), ryanodine receptor 2 (RyR2), and nuclear factor kappa B (NF-κB) phosphorylation than control cells had. Gal-3-mediated activation of CaMKII/RyR2 pathway was diminished in the cotreatment of anti-CD98 antibodies. Mice that were injected with Gal-3 had more atrial ectopic beats, increased atrial fibrosis, and activated NF-κB/NLRP3 signalling than did control mice (nonspecific immunoglobulin) or mice treated with Gal-3 and anti-CD98 antibodies. Gal-3 recombinant protein administration increases atrial fibrosis and arrhythmogenesis through CD98 signalling. Targeting Gal-3/CD98 axis might be a novel therapeutic strategy for patients with AF and high Gal-3 levels.

Left Ventricular Flow Distribution as a Novel Flow Biomarker in Atrial Fibrillation.

Introduction: Four-dimensional (4-D) flow cardiac magnetic resonance imaging can be used to elegantly describe the hemodynamic efficiency of left ventricular (LV) flow throughout the cardiac cycle. Patients with nonvalvular paroxysmal atrial fibrillation (PAF) may have occult LV disease. Flow distribution analysis, based on 4-D flow, may unmask the presence of LV disease by assessing flow components: direct flow, retained flow, delayed ejection, and residual volume. This study aimed to identify LV hemodynamic inefficiencies in patients with PAF and normal systolic function. We hypothesized that the fraction of direct flow to the total end-diastolic volume would be reduced in patients with PAF compared with controls. Methods: We used 4-D LV flow component analysis to compare hemodynamics in 30 healthy controls and 50 PAF patients in sinus rhythm. Results: PAF subjects and healthy controls had similar LV mass, volume, and ejection fraction. Direct flow was lower in the PAF group than in the controls (44.5 ± 11.2% vs. 50.0 ± 12.2%, p = 0.042) while delayed ejection was higher in the PAF group (21.6 ± 5.6% vs. 18.6 ± 5.7%, p = 0.022). Conclusion: PAF patients demonstrated a relative reduction in direct flow and elevation in delayed ejection.

Abstract 11416: The Prognostic Impact of Myocardial Fibrosis Biomarkers for Atrial Fibrillation in a Heart Failure Population

Introduction: Several studies suggest that circulating biomarkers of myocardial fibrosis are associated with worse prognosis of atrial fibrillation (AF). Hypothesis: Here, we aimed to evaluate the prognostic impact of myocardial fibrosis biomarkers for atrial fibrillation in a heart failure (HF) population Methods: Three-hundred-and-twenty-one patients hospitalized for HF (mean age 75 years; 32% women) were screened for co-existing AF and a proximity extension assay including estimation of 7 proteins associated with myocardial fibrosis; Metalloproteinase inhibitor 4 (TIMP-4), Soluble interleukin 1 receptor-like 1 (ST-2), Galectin 3 (Gal-3), Growth/differentiation factor 15 (GDF-15) and Matrix metalloproteinase 2, 3 and 9 (MMP-3, MMP-3 and MMP-9 respectively). Associations between AF and proteins were cross-sectionally studied in multivariable logistic regression models. Furthermore, associations between protein plasma levels, mortality and re-hospitalization risk were analyzed using multivariable Cox regression analysis adjusted for age sex, prevalent diabetes, smoking, body mass index (BMI), systolic blood pressure (SBP) and New York heart association classification (NYHA-class). Results: One-hundred-and-ninety-seven patients (61%) had prevalent AF at hospitalization. In multivariate logistic regression models, the prevalence of atrial fibrillation was significantly associated with increased plasma levels of TIMP-4, GDF-15, ST-2, MMP-2 and MMP-9. In the fully adjusted Cox regression model, increased plasma levels of 5 proteins yielded significant associations with mortality; TIMP4 (p=0,022 HR;1,46 CI95%1,06-2,01), GDF 15 (p=0,028; HR1,29; CI95% 1,03-1,63), Gal-3 (p=0,017; HR1,64;CI95% 1,09-2,47), ST2 (p=0,002; HR;1,43; CI95%1,14-1,80) and MMP3 (p=0,011; HR;1,29; CI95% 1,06-1,58). Further, increased levels of TIMP4 was significantly associated with rehospitalization (p=0,001; HR 1,58; C95% 1,19-2,08). Conclusions: We have demonstrated that increased plasma levels of plasma proteins related to myocardial fibrosis are associated with the risk of mortality in hospitalized HF patients, independently of traditional risk factors.

Biomarkers for atrial fibrillation and chronic kidney disease: what is the evidence?

Biomarkers for atrial fibrillation and chronic kidney disease: what is the evidence?

Microrna: the role in the pathophysiology of atrial fibrillation and potential use as a biomarker

The aim of the study was to analyze medical literature on the role of microRNA in the pathophysiology of atrial fibrillation and the possibilities of using microRNAs as biomarkers.The analysis of modern medical literature was carried out using the PubMed – NCBI database.Atrial fibrillation (AF) is a common and serious cardiovascular disease. The pathophysiological mechanisms underlying the development of atrial fibrillation are not entirely clear. In addition, there are no optimal biomarkers for early detection and assessment of the prognosis for patients with atrial fibrillation. Recently, the attention of researchers has been directed to the molecules of microRNA. There is a lot of evidence that they are involved in the pathogenesis of neurological, oncological, and cardiovascular diseases. This review examines the role of microRNAs in the pathophysiology of atrial fibrillation. The possibility of using microRNA as a biomarker for the diagnosis and prediction of atrial fibrillation is also discussed.MicroRNAs play a crucial role in the pathophysiology of atrial fibrillation, regulating the mechanisms of atrial remodeling, such as electrical remodeling, structural remodeling, remodeling of the autonomic nervous system, and impaired regulation of calcium levels. The stability of microRNAs and the possibility to study them in various biological fluids and tissues, including blood, make these molecules a promising diagnostic biomarker for various cardiovascular diseases. The presented data clearly indicate that AF is associated with changes in the expression level of various microRNAs, which can be quantified using a polymerase chain reaction. Further research is required to assess the role of microRNAs as biomarkers for atrial fibrillation, in particular to establish precise reference limits.

Utility of miR-155, miR-21 and miR-16 in plasma as biomarkers of atrial fibrillation

Abstract Background Atrial fibrillation (AF) is associated with increased morbidity and mortality. MicroRNAs (miRs) are post-transcriptional regulators that could be useful in the study of AF. Purpose To investigate whether miR-16, miR-21 and miR-155 may differentiate between AF and sinus rhythm. Methods 29 controls and 42 AF (June 2019-May 2020). Lipid profile, hsCRP were measured. Serum RNA extraction was performed. Hsa-miR-21, hsa-miR-16, hsa-miR-155, and cel-miR-39 were amplified RT-PCR. Quantitative results for miR levels were generated according to the 2-ΔCt method using cel-miR-39 for normalization. Correlations were assessed by Spearman rank test. Logistic regression analysis was adjusted by age, sex, and BMI vs miR's. A p&amp;lt;0.05 was set for significance. Results (controls vs AF): age (56 [52–63] vs 60 [64–67] years, p=0.122), BMI (30.52 [27.69–32.67] vs 29.65 [26.3–32.9] kg/m2 p=0.779), female 17 (58.6%) vs 19 (45.2%), p=0.268; total cholesterol (198.4 [17.2–215] vs 171.3 [150.3–216.8] mg/dL, p=0.066), LDL (126.6 [114.7–141.6] vs 99.2 [80.7–124] mg/dL, p=0.005) HDL (40.4 [36.8–45.8] vs 43.8 [36.9–48.5] p=0.326) and CRP (2.69 [1.22–4.72] vs 2.92 [1.4–4.76] mg/L p=0.835). The CHA2DS2VASC score in AF was &amp;lt;2=11 (45.2%) and ≥2= 26 (54.8%). MicroRNA levels (controls vs AF): miR-21 0.0195 (0.0095–0.0275) vs 0.042 (0.028–0.098) p&amp;lt;0.001; miR-155 0.0178 (0.0108–0.0309) vs 0.01 (0.0056–0.0169) p&amp;lt;0.001, and miR-16 0.5238 (0.2618–1.992) vs 0.1652 (0.0765–0.3816) p&amp;lt;0.001. In the logistic regression miR-21 had a positive correlation with AF, c=0.851 p=0.002, Wald=9.89. miR-16 and miR-155 a negative relation (c=0.76,0.72; p=0.036, 0.043, Wald=4.39, 4.085; respectively) (Fig. 1A, B, C). For multivariable analysis we used miR-16, miR-21, and miR-155 as previous analysis demonstrated significance with an overall model c=0.90 p=0.028 (Wald=14.2) and significance was seen in the miR-21 Wald= 9.33 (p=0.002); and miR-155 Wald=4.7 (p=0.03); miR-16 was not significant (Wald=2.7, p=0.1). A ternary plot was performed using the predicted outputs of the model. (Fig. 2) Conclusion miR-16, miR-21 and miR-155 are useful for the discrimination of AF vs sinus rhythm and may be part of important physiopathological pathways in AF. Funding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Instituto Nacional de Cardiología Ignacio Chávez Figure 1. Logistic regression curvesFigure 2. Multivariate ternary plot of miRs

MicroRNAs sequencing of plasma exosomes derived from patients with atrial fibrillation: miR-124-3p promotes cardiac fibroblast activation and proliferation by regulating AXIN1.

MicroRNAs (miRNAs) play an important role in the pathogenesis of atrial fibrillation (AF). Exosomal miRNAs may develop as promising biomarkers for AF. To explore significant exosomal miRNAs in AF, plasma exosomes were extracted from 3 patients with AF and 3 patients with sinus rhythm (SR), respectively. Differential expression of exosomal miRNAs were screened by high-throughput sequencing analysis and verified by qRT-PCR from 40 patients with AF and 40 patients with SR. The target genes prediction, biological function, and signaling pathways analysis were conducted by miRanda software, gene ontology (GO), and KEGG analysis. The results showed that there were 40 differently expressed exosomal miRNAs from AF patients compared with SR patients, of which 13 miRNAs were upregulated and 27 miRNAs were downregulated. qRT-PCR validation demonstrated that miR-124-3p, miR-378d, miR-2110, and miR-3180-3p were remarkably upregulated, while miR-223-5p, miR-574-3p, miR-125a-3p, and miR-1299 were downregulated. To explore the function of miR-124-3p associated with AF, plasma exosomes derived from AF patients were co-incubated with rat myocardial fibroblasts. The expression of miR-124-3p was upregulated in myocardial fibroblasts. The viability and proliferation of myocardial fibroblasts were elevated by transfecting with miR-124-3p overexpression plasmids using CCK8 and immunofluorescence-staining methods. AXIN1 was verified to be the target of miR-124-3p by luciferase assay in vitro. Expression of AXIN1 was reduced, while β-catenin, Collagen 1, and α-SMA were increased in myocardial fibroblasts with miR-124-3p overexpression. In conclusion, these findings suggested that circulating exosomal miRNAs may serve as novel biomarkers for AF, and miR-124-3p promotes fibroblast activation and proliferation through regulating WNT/β-catenin signaling pathway via AXIN1.

Pericardial NT-Pro-BNP and GDF-15 as Biomarkers of Atrial Fibrillation and Atrial Matrix Remodeling in Aortic Stenosis.

Aims: This study aimed to evaluate the association of GDF-15 and NT-pro-BNP in two different biological matrices with AF in severe aortic stenosis patients undergoing aortic valve replacement surgery (AVR), its association with atrial matrix remodeling, as well as with 30-day postoperative outcomes. Main Methods: One hundred and twenty-six patients between 2009 and 2019 with severe aortic stenosis undergoing AVR surgery in a tertiary hospital were assessed. Key Findings: pericardial fluid GDF-15 and pericardial fluid and serum NT-pro-BNP were increased in AF patients with aortic stenosis. COL1A1 and COL3A1 gene expression increased when pericardial fluid NT-pro-BNP values were higher. TIMP4 was positively correlated with pericardial fluid GDF-15. Significance: GDF-15 and NT-pro-BNP in the pericardial fluid are biomarkers of atrial fibrillation in aortic stenosis and correlate with atrial matrix remodeling. AKI is predicted by both serum and pericardial fluid GDF-15.

Exosomes in atrial fibrillation: therapeutic potential and role as clinical biomarkers.

Atrial fibrillation (AF), the most common cardiac arrhythmia, is a global epidemic. AF can cause heart failure and myocardial infarction and increase the risk of stroke, disability, and thromboembolic events. AF is becoming increasingly ubiquitous and is associated with increased morbidity and mortality at higher ages, resulting in an increasing threat to human health as well as substantial medical and social costs. Currently, treatment strategies for AF focus on controlling heart rate and rhythm with medications to restore and maintain sinus rhythm, but this approach has limitations. Catheter ablation is not entirely satisfactory and does not address the issues underlying AF. Research exploring the mechanisms causing AF is urgently needed for improved prevention, diagnosis, and treatment of AF. Exosomes are small vesicles (30-150nm) released by cells that transmit information between cells. MicroRNAs in exosomes play an important role in the pathogenesis of AF and are established as a biomarker for AF. In this review, a summary of the role of exosomes in AF is presented. The role of exosomes and microRNAs in AF occurrence, their therapeutic potential, and their potential role as clinical biomarkers is considered. A better understanding of exosomes has the potential to improve the prognosis of AF patients worldwide, reducing the global medical burden of this disease.