Synergistic Effects of SGLT2 Inhibitors and GLP-1R Agonists on Inflammation-Associated Oxidative Stress in Atrial Fibrillation

Figure 1. Gene Expression Analysis of Atrial Remodeling Markers, SGLT2, and GLP1R in RAAs of Patients With and Without AF (A) Heatmap of target gene expression in 80 right atrial appendages (RAAs) from 18 patients with histories of atrial fibrillation (AF) and 62 with no AF, labeled as sinus rhythm (SR). Data are shown as relative abundance represented by color (green, lower abundance; red, higher abundance) as indicated in the scale. (B) Messenger RNA (mRNA) expression levels of target genes in SR patients compared with AF patients. (C) Pearson correlations between TNF-α, sodium-glucose cotransporter 2 (SGLT2), glucagon-like peptide 1 receptor (GLP-1R), and other target gene expression levels in the 80 RAA specimens. Data are shown as mean ± SEM. ∗∗∗P < 0.001 vs SR using multiple Student’s t-tests with Benjamini-Hochberg correction for false discovery rate.

Figure 2. Inflammation-Associated SGLT2 and GLP-1R Expression in Human RAAs and Cardiac Cell Types RAA samples were grouped according to TNF-α expression: low TNF-α (below median); high TNF-α, including only patients in SR; and high TNF-α, including only patients with histories of AF. (A) Protein expression of p-p65, SGLT2, GLP-1R, and NOX2 shown as representative immunoblots (n = 4 per group) with corresponding quantification (n = 8 per group). (B) RAA sections with low or high TNF-α expression costained for SGLT2 or GLP-1R (red), troponin T, CD31, or CD86 (yellow). Colocalization was quantified using the Pearson correlation coefficient. (C) SGLT2 and GLP-1R expression was evaluated in human coronary artery endothelial cells (ECs), cardiomyocytes (CMs) (AC16), and peripheral blood mononuclear cells (PBMCs) after 48 hours of small interfering RNA (siRNA)–mediated knockdown (vs scrambled siRNA control) followed by TNF-α stimulation (10 ng/mL, 24 hours) and western blot analysis. Data are presented as mean ± SEM. Statistical significance was determined using 1-way analysis of variance followed by Tukey’s post hoc test in (A) (∗P < 0.05 vs low TNF-α; #P < 0.05 vs high TNF-α-SR) and (C) (∗P <…

Figure 3. Antioxidant Effects of SGLT2 Inhibition in RAA Tissue From Patients With or Without AF (A) Pearson correlations between ROS and CD86, TNF-α, and SGLT2 gene expression in 80 RAA samples (r2 is the coefficient of determination). (B) Effect of empagliflozin on reactive oxygen species (ROS) formation in RAAs from AF vs SR patients, with the latter group also subcategorized into low- vs high-TNF-α-expressing groups. (C) ROS formation measured in low- vs high-TNF-α-expressing RAAs under basal conditions and after treatment with N-acetylcysteine (NAC; 1 mM, 2 hours), VAS-2870 (VAS; a nicotinamide adenine dinucleotide phosphate oxidase inhibitor, 1 μM), empagliflozin (EMPA; 100 nM), or infliximab (IFX; a TNF-α-neutralizing antibody, 30 ng/mL) for 30 minutes prior to dihydroethidium staining. (D) RAA sections exposed to TNF-α with or without inhibitors. Data are shown in arbitrary units (AU) as mean ± SEM. ∗P < 0.05 vs control (C) and SR control (A) and #P < 0.05 vs AF control B and TNF-α-stimulated sections (D), analyzed using 1-way or 2-way analysis of variance (B) followed by Tukey’s test. ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001, ##P < 0.01, and ###P < 0.001. Abbreviations as in Figure 1.

Figure 4. Antioxidant Effects of GLP-1R Agonists in RAA Tissue From Patients With or Without AF (A) Pearson correlation between ROS and GLP-1R gene expression in 80 RAA samples (r2 is the coefficient of determination). Effect of semaglutide (SEMA) on ROS formation in RAAs from AF vs SR patients, with the group also subcategorized into low- vs high-TNF-α-expressing groups. Dihydroethidium (DHE) staining was done 30 minutes after treatment. (B) High-TNF-α-expressing RAAs treated with exendin 9-39 (Exen 9-39; a GLP-1R antagonist), SQ22536 (SQ; an adenylyl cyclase inhibitor), PKI (14-22) (a protein kinase A inhibitor), forskolin (Forsk; an adenylyl cyclase activator), and SEMA or liraglutide (LIRA; 100 nM), with or without inhibitors, for 30 minutes before DHE staining. (C) Low TNF-α-expressing RAAs exposed to TNF-α in the absence or presence of inhibitors. ROS levels measured ECs, AC16 CMs, and PBMCs pretreated with SEMA (100 nM) with or without SQ22536 or PKI for 30 minutes prior to TNF-α stimulation (10 ng/mL, 24 hours). Data are presented as mean ± SEM (AU). ∗P < 0.05 vs respective control, #P < 0.05 vs AF control A or TNF-α-stimulated RAAs C or cells (D), $P < 0.05 vs SEMA SR A, †P < 0.05…

Figure 5. Synergistic Antioxidant and Anti-Inflammatory Effects of SGLT2 Inhibitors and GLP-1R Agonists in Human RAAs and Cardiac Cells (A) ROS formation assessed by DHE staining in high-TNF-α-expressing RAAs under basal conditions and after treatment with EMPA or SEMA (30 minutes) or NAC (2 hours). (B) In the upper quartile TNF-α-expressing RAAs, ROS levels measured after treatment with EMPA, SEMA, their combination, or NAC. Combined effect compared with the expected additive effect, and responses analyzed in SR vs AF patients. (C and D) ECs, CMs (AC16), and PBMCs pretreated with EMPA (10 nM), SEMA (10 nM), or their combination for 30 minutes or following 48 hours of gene knockdown using SGLT2 siRNAs. Scrambled siRNA (Scrbl) served as the negative control. Cells were subsequently stimulated with TNF-α (10 ng/mL) for 24 hours. ROS formation was measured by DHE staining C and target protein expression by western blot D Data are presented as mean ± SEM (AU). ∗P < 0.05 vs control, $P < 0.05 vs SR control, §P < 0.05 vs AF control, #P < 0.05 vs TNF-α-stimulated cells, †P < 0.05 vs EMPA, ‡P < 0.05 vs SEMA, and +P < 0.05 vs expected additive effect of EMPA plus SEMA, analyzed using 1-way analysis…