Increased small extracellular vesicle levels and decreased miR‐126 levels associated with atrial fibrillation and coexisting diabetes mellitus

Figures

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  Figure 1. A flowchart of the enrollment of the study cohort.

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  Figure 2. Characterization of small extracellular vesicles (sEVs). Plasma sEVs from atrial fibrillation (AF) patients with diabetes mellitus (DM) and without DM were characterized via nanoparticle tracking analysis (NTA), Western blot analysis, and transmission electron microscopy (TEM). (A) NTA showing the size and concentration of sEVs in the AF with and without DM groups. (B) NTA showing the total sEV count compared between AF patients with DM (n = 28) and without DM (n = 28). (C) NTA showing the total sEV count compared between groups and stratified by sEV size subcategory. (D) Western blot analysis showing the sEV markers CD63 and Alix and the contaminant lipoprotein marker apolipoprotein in sEV samples (30 µg protein per lane). (E) The morphologies of sEVs from both groups were visualized by TEM (scale bar: 100 nm, ×50 000 magnification). A p < .05 indicates statistical significance.

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  Figure 3. Absolute quantification by droplet digital polymerase chain reaction (ddPCR) of microribonucleic acid (miRNA) expression in small extracellular vesicles (sEVs). (A) miR‐126‐3p, (B) miR‐320a‐3p, (C) miR‐146a‐3p, and (D) miR‐30c‐5p in sEVs from and compared between atrial fibrillation (AF) patients with diabetes mellitus (DM) and without DM. Differences between groups were analyzed using Mann−Whitney U test for independent samples. Data shown as median and interquartile range, and a p < .05 indicates statistical significance.

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  Figure 4. Analysis for predictors of atrial fibrillation (AF) with diabetes mellitus (DM) or AF without DM, and a comparison among models for predicting AF with DM. (A) Univariate logistic regression analysis was performed to identify significant predictors/factors that favor either AF with DM or AF without DM. (B) To explore the discriminatory ability of total sEVs and sEV‐miR‐126‐3p levels to predict AF with DM, we analyzed five multivariate logistic regression models. The results of those analyses were used to generate receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) was calculated to determine the predictive sensitivity and specificity of each model. The AUC for all 5 models was 0.897 or higher, and the p‐value for all 5 models was p < .0001; however, model 5, which included clinical data, total sEVs, and sEV‐miR‐126 levels, had the highest AUC (0.968). Moreover, model 5 or the combination of model 1 with sEV and sEV‐miR‐126 showed a significant increase in AUC compared to model 1 alone (p = .038). A p‐value < .05 indicates statistical significance. (BMI, body mass index; CI, confidence interval; DBP, diastolic blood pressure; HDL‐C, high‐density…

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  Figure 5. The putative mechanisms involved in the relationship between small extracellular vesicle (sEV) generation, sEV‐miR‐126‐3p expression, and atrial fibrillation (AF) with diabetes mellitus (DM). The pathophysiologies of AF and DM stimulate sEV generation and downregulation of miR‐126‐3p, which influences the progression of both AF and DM, as well as cardiovascular complications, including thromboembolism leading to stroke and endothelial dysfunction leading to coronary artery disease.