Association between miR-146a and tumor necrosis factor alpha (TNF-α) in stable coronary artery disease

medicina Article Association between miR-146a and Tumor Necrosis Factor Alpha (TNF-α) in Stable Coronary Artery Disease Tiago Pereira-da-Silva 1,2,* , Patrícia Napoleão3, Marina C. Costa 3,4 , AndréF. Gabriel 3,4 , Mafalda Selas 1, Filipa Silva 1, Francisco J. Enguita 3,4 , Rui Cruz Ferreira 1and Miguel Mota Carmo 5   Citation: Pereira-da-Silva, T.; Napoleão, P.; Costa, M.C.; Gabriel, A.F.; Selas, M.; Silva, F.; Enguita, F.J.; Cruz Ferreira, R.; Mota Carmo, M. Association between miR-146a and Tumor Necrosis Factor Alpha (TNF-α) in Stable Coronary Artery Disease. Medicina 2021,57, 575. https://doi.org/10.3390/ medicina57060575 Academic Editor: Tomasz Zieli´nski Received: 22 May 2021 Accepted: 2 June 2021 Published: 4 June 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Department of Cardiology, Hospital de Santa Marta, Centro Hospitalar Universitário de Lisboa Central, 1169-024 Lisbon, Portugal; [email protected] (M.S.); [email protected] (F.S.); cruzferr[email protected] (R.C.F.) 2NOVA Doctoral School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal 3Instituto de Medicina Molecular João Lobo Antunes, Universidade de Lisboa, 1649-028 Lisbon, Portugal; [email protected] (P.N.); [email protected] (M.C.C.); [email protected] (A.F.G.); [email protected] (F.J.E.) 4Cardiomics Unit, Centro Cardiovascular da Universidade de Lisboa, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisbon, Portugal 5Chronic Diseases Research Center (CEDOC), NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal; [email protected] *Correspondence: [email protected]; Tel.: +351-919908505 Abstract: Background and Objectives: Tumor necrosis factor alpha (TNFα ) is proatherogenic and associated with the risk of acute ischemic events, although the mechanisms that regulate TNFα expression in stable coronary artery disease (SCAD) are not fully understood. We investigated whether metabolic, inflammatory, and epigenetic (microRNA (miRNA)) markers are associated with TNFα expression in SCAD. Materials and Methods: Patients with SCAD were prospectively recruited and their metabolic and inflammatory profiles were assessed. TNFα levels were assessed using an enzyme-linked immunosorbent assay. The relative expression of six circulating miRNAs associated with the regulation of inflammation and/or atherosclerosis was determined. Results: Of the 24 included patients with the mean age of 65 (9) years, 88% were male, and 54% were diabetic. The TNFα levels were (median (interquartile range)) 1.0 (0.7–1.1) pg/mL. The percentage of glycosylated hemoglobin (r= 0.418, p= 0.042), serum triglyceride levels ( r= 0.429, p= 0.037), and C-reactive protein levels (r= 0.407, p= 0.048) were positively correlated with TNFα levels. Of the candidate miRNAs, miR-146a expression levels were negatively correlated with TNFα levels (as indicated by r= 0.500, p= 0.035 for correlation between delta cycle threshold ( ∆ C t ) miR-146a and TNFα levels). In multivariate analysis, serum triglyceride levels and miR-146a expression levels were independently associated with TNFα levels. miR-146 expression levels were not associated with metabolic or other inflammatory parameters and were negatively correlated with the number of coronary vessels with obstructive disease (as indicated by r= 0.556, p= 0.017 for correlation between ∆ C t miR-146a and number of diseased vessels). Conclusions: miR-146a expression levels were negatively correlated with TNFα levels in patients with SCAD, irrespective of other metabolic or inflammatory markers, and with the severity of coronary artery disease. The results add to the knowledge on the role of miR-146a in TNFα -based inflammation in SCAD and support future research on the potential therapeutic use of miR-146a in such a clinical scenario. Keywords: inflammation; microRNA; miR-146a; stable coronary artery disease; tumor necrosis factor alpha 1. Introduction Stable coronary artery disease (SCAD) is accountable for substantial cardiovascular morbidity and mortality worldwide [ 1 ]. It is a chronic inflammatory syndrome characterMedicina 2021,57, 575. https://doi.org/10.3390/medicina57060575 https://www.mdpi.com/journal/medicina Medicina 2021,57, 575 2 of 10 ized by the activation of proinflammatory pathways, including those of tumor necrosis factor alpha (TNFα ), soluble CD40 ligand, and C-reactive protein [ 2 – 4 ]. Specifically, TNFα is a strong proinflammatory mediator that induces atherogenesis [ 2 , 5 ]. Moreover, TNFα is closely associated with cardiovascular prognosis and increased TNFα levels are associated with a higher risk of ischemic events [ 6 , 7 ]. Therefore, TNFα has been studied as a therapeutic target in patients with documented atherosclerosis [8–10]. Despite the acknowledged role of TNFα in atherosclerosis development and progression, the mechanisms that regulate TNFα expression in patients with SCAD are not fully understood [ 5 ]. Metabolic dysregulation, including hyperglycemia, dyslipidemia, and adiposity, increases TNFα levels [ 11 – 16 ]. Such metabolic abnormalities interact with each other and often coexist in patients with SCAD, and the independent role of each on TNFα expression is not entirely known [ 5 , 17 ]. On the other hand, epigenetic modulators, including microRNAs (miRNAs), may influence TNFα expression in vitro [ 18 ]. miRNAs are small noncoding RNA molecules that are involved in distinct biological roles, including the regulation of inflammation and atherosclerosis [ 19 ]. Whether an interaction between circulating miRNAs and TNFα expression exists in patients with SCAD and whether such potential association is influenced by metabolic abnormalities or coexistent inflammatory dysregulation is unknown. The knowledge on the expression of inflammatory mediators, including TNFα , and their regulators in SCAD may provide insights into its pathophysiology. Such research area has regained interest after the clinical results of a pure anti-inflammatory agent in patients with stable atherosclerosis [20]. We investigated whether metabolic, inflammatory, and epigenetic (miRNA) markers are associated with TNF-αexpression in SCAD. 2. Materials and Methods This study is a part of a project aimed at assessing inflammatory and epigenetic signatures associated with the clinical expression of stable atherosclerosis. The study protocol was approved by the ethics committees of the involved institutions (Centro Hospitalar Universitário de Lisboa Central, Nr. 245/2015, 1 October 2015; and NOVA Medical School | Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Nr. 000176, 11 November 2015). The investigation conformed to the principles outlined in the Helsinki Declaration. All the participants signed informed consent forms. 2.1. Recruitment of Participants Patients with SCAD from our center were prospectively recruited. The inclusion criteria were the presence of coronary artery disease, defined as luminal stenosis of at least 50% for the left main artery or at least 70% for other epicardial vessels on invasive coronary angiography, and absence of symptoms worsening in the prior six months. Patients with acute ischemic events within 12 months in any arterial territory, those with coronary artery bypass grafting performed within 12 months, those with prior percutaneous arterial treatment, those with heart failure, hemodynamically significant valvular heart disease, hematological disorders, active infection, history of malignancy, chronic kidney disease (stage 4 or 5), or severe hepatic dysfunction, those under 18 years of age, and those unable or unwilling to consent to participate in the study were excluded. 2.2. Data Collection and Blood Sampling Data were collected prospectively after patient inclusion. A standardized record including clinical, demographic, laboratory, echocardiographic, and angiographic data was obtained from each participant. Peripheral blood was collected early in the morning under fasting conditions before any coronary intervention. Serum was separated by centrifugation (500 × gfor 10 min) within 15 min of sampling. Aliquots were stored at − 80 ◦ C and samples were thawed only once. Medicina 2021,57, 575 3 of 10 2.3. Measurements of Inflammatory Markers Levels of TNFα , soluble CD40 ligand, and C-reactive protein were measured in serum by an enzyme-linked immunosorbent assay (R&D Systems, Minneapolis, MN, USA ). Measurements were performed in duplicates. The intra-assay variation among the duplicates for all samples was less than 10%. 2.4. Quantification of Expression Levels of Candidate miRNAs Six candidate miRNAs (miR-21, miR-27b, miR-29a, miR-126, miR-146a, and miR-218) were selected based on the following criteria: miRNAs are associated with the regulation of inflammation and/or atherosclerosis in experimental models [ 19 , 21 , 22 ]; each of the miRNAs regulates distinct pathways and/or has distinct mechanisms of action [ 19 , 21 , 22 ]; and miRNAs were reported to be dysregulated in patients with stable atherosclerosis [ 23 – 29 ]. Among other functions, miR-21 regulates vascular smooth cell and endothelial cell functions; miR-27b regulates lipid metabolism and development of lipid-induced atherosclerotic lesions, and modulates the production of proinflammatory factors; miR-29a regulates fibrosis and extracellular matrix composition; miR-126 regulates endothelial function in response to shear stress; miR-146a regulates endothelial and monocyte-macrophage inflammatory response; and miR-218 regulates endothelial cell migration [18,19,21,22]. Total RNA was extracted from serum samples using the miRCURY ™ RNA Isolation Kit (Qiagen, Hilden, Germany). Complementary DNA was synthesized from total RNA using the Universal cDNA synthesis kit from miRCURY ™ LNA miRNA system (Qiagen, Hilden, Germany). miRNA amplification was performed using quantitative reverse-transcription polymerase chain reaction (using the miRCURY ™ LNA SYBR Green PCR Kit and LNA ™ PCR primers, Qiagen, Hilden, Germany), and the melting curve was determined according to the following conditions: 95 ◦C for 10 min followed by 45 cycles of 95 ◦ C for 10 s and 60 ◦ C for 60 s. All the reactions were performed in triplicates. The amplification data were assessed using DataAssist ™ Software v3.01 (Thermo Fisher Scientific, Waltham, MA, USA). Cycle threshold (C t ) values greater than 40 were considered undetermined [ 25 , 30 – 32 ]. The relative expression levels of the six candidate miRNAs were calculated using the delta cycle threshold ( ∆ C t ) method, normalizing for the UniSp6 RNA spike-in control [ 25 , 33 – 35 ]. Higher ∆ C t values represent lower circulating levels of the candidate miRNAs [25,33–35]. 2.5. Statistical Analysis Discrete variables are presented as frequencies (percentages) and continuous variables are presented as the mean (standard deviation) in normally distributed data or median (interquartile range) in variables without a normal distribution (Shapiro–Wilk test). Categorical variables were analyzed using the chi-squared or Fisher’s exact tests. Continuous variables were analyzed using Student’s t-test or the Mann–Whitney test when normality was not verified. Pearson’s correlation was used to test correlations between continuous variables. A multivariate linear regression analysis was performed using TNFα as the dependent variable and the metabolic, inflammatory, and epigenetic (miRNA) parameters associated with TNFα in the univariate analysis as the independent variables. Variables with a p-value < 0.10 in the univariate analysis were tested in the multivariate model. A correction for collinearity was performed. The level of significance was set at α = 0.05. Analyses were conducted using SPSS software, version 26.0 (IBM Corp, Armonk, NY, USA). 3. Results 3.1. Clinical Characteristics and Laboratory Data Of Patients A total of 24 participants were recruited with a mean age of 65 (9) years, of which 21 (88%) were male and 13 (54%) were diabetic (Table 1). All patients were using single antiplatelet therapy and lipid-lowering (mostly statin) therapy. No modifications in antithrombotic or lipid-lowering therapy were made within the two months prior to blood sampling. The median (interquartile range) TNF-αlevels were 1.0 (0.7–1.1) pg/mL. Medicina 2021,57, 575 4 of 10 Table 1. Clinical characteristics and laboratory data. Clinical Characteristics Age, years 65 (9) Male, n(%) 21 (88) Hypertension, n(%) 22 (92) Dyslipidemia, n(%) 22 (92) Diabetes mellitus, n(%) 13 (54) Active smoking, n(%) 4 (17) Body mass index, kg/m226.7 (3.1) Number of coronary vessels with obstructive disease 13 (2–4) Prior coronary artery bypass grafting, n(%) 3 (13) Left ventricular ejection fraction > 50%, n(%) 24 (100) Antiplatelet therapy, n(%) 224 (100) Oral anticoagulation, n(%) 0 (0) Statin therapy, n(%) 22 (92) High-intensity statin therapy, n(%) 17 (71) Ezetimibe, n(%) 4 (17) ACE inhibitor or ARB, n(%) 21 (88) Betablocker, n(%) 15 (63) Other antianginal agent, n(%) 12 (50) Oral antidiabetic agent, n(%) 13 (54) Insulin therapy, n(%) 6 (25) Laboratory Data Hemoglobin, g/dL 13.6 (1.6) Leukocyte count, 109/L 8.0 (1.5) Neutrophil count, 109/L 4.7 (1.5) Lymphocyte count, 109/L 2.2 (1.7–2.7) Platelet count, 109/L 236 (41) Fasting glycaemia, mg/dL 99 (85–166) Percentage of glycosylated hemoglobin 6.1 (5.6–7.9) Creatinine, mg/dL 0.9 (0.8–1.3) Total cholesterol, mg/dL 158 (40) LDL-cholesterol, mg/dL 92 (29) HDL-cholesterol, mg/dL 35 (29–43) Triglycerides, mg/dL 117 (87–162) Soluble CD40 ligand, ng/mL 8.4 (2.5) C-reactive protein, mg/L 4.0 (3.6–4.7) ∆CtmiRNA miR-21 17.6 (3.2) miR-27b 23.4 (20.9–24.4) miR-29a 22.9 (2.8) miR-126 23.1 (16.9–24.9) miR-146a 22.5 (2.5) miR-218 20.9 (19.5–24.3) 1 The left main artery, left anterior descending artery, circumflex artery, and right coronary artery were scored individually. Categorical variables are expressed as frequency (percentage) and continuous variables as the mean (standard deviation) or median (interquartile range); 2 all patients were using single antiplatelet therapy. ACE—angiotensin-converting enzyme; ARB—angiotensin II receptor blocker; HDL—high-density lipoproteins; LDL—low-density lipoproteins; miRNA—microRNA; ∆Ct—delta cycle threshold. 3.2. Parameters Associated with TNF-αLevels in Univariate Analysis The parameters associated with TNFα levels in the univariate analysis are presented in Table 2. The percentage of glycosylated hemoglobin, serum triglyceride levels, and C-reactive protein levels were positively correlated with TNFα levels, and there was a trend for a positive correlation between fasting glycemia and TNFα levels. No associations were found between other clinical parameters (including pharmacological therapy) or other laboratory data (including soluble CD40 ligand levels) and TNF-αlevels. Regarding the candidate miRNAs, ∆ C t miR-146a showed a positive correlation with TNFα levels (r= 0.500, p= 0.035; Table 2), indicating an inverse correlation between Medicina 2021,57, 575 5 of 10 miR-146a expression levels and TNFα levels. The expression levels of other miRNAs were not associated with TNF-αlevels. 3.3. Parameters Associated with TNF-αLevels in Multivariate Analysis In the multivariate analysis, serum triglyceride levels and miR-146a expression levels were independently associated with TNFα levels. Lower miR-146a expression levels and higher serum triglyceride levels were associated with increased TNF-αlevels (Table 3). Table 2. Parameters associated with TNF-αlevels in univariate analysis. Clinical Characteristics TNF-α, pg/mL p-Value Age, years 1r=−0.145 0.500 Sex 2Male 0.9 (0.7–1.1) 1.000 Female 1.0 (0.5–1.0) Hypertension 2No 1.5 (1.1–1.5) 0.145 Yes 0.9 (0.7–1.1) Dyslipidemia 2No 1.5 (1.1–1.5) 0.181 Yes 0.9 (0.7–1.1) Diabetes mellitus 2No 0.9 (0.8–1.2) 0.820 Yes 1.0 (0.6–1.3) Active smoking 2No 0.9 (0.6–1.1) 0.347 Yes 1.1 (0.8–1.3) Body mass index, kg/m2 1 r= 0.229 0.281 Number of coronary vessels with obstructive disease 1,3 r= 0.097 0.651 Prior CABG 2No 1.0 (0.7–1.2) 0.742 Yes 0.8 (0.6–0.8) Left ventricular ejection fraction 2≤50% – – >50% 1.0 (0.7–1.1) Antiplatelet therapy 2No – – Yes 1.0 (0.7–1.1) Oral anticoagulation 2No 1.0 (0.7–1.1) – Yes – Statin therapy 2No 0.8 (0.7–0.8) 0.587 Yes 1.0 (0.7–1.2) High-intensity statin therapy 2No 1.0 (0.8–1.2) 0.486 Yes 0.9 (0.7–1.1) Ezetimibe 2No 0.9 (0.7–1.1) 0.261 Yes 1.1 (1.1–1.2) ACE inhibitor or ARB 2No 0.8 (0.7–1.0) 0.431 Yes 1.0 (0.7–1.3) Betablocker 2No 0.9 (0.7–1.3) 0.861 Yes 1.0 (0.7–1.1) Other antianginal agent 2No 0.9 (0.6–1.1) 0.514 Yes 1.0 (0.7–1.3) Oral antidiabetic agent 2No 0.9 (0.8–1.2) 0.820 Yes 1.0 (0.6–1.3) Insulin therapy 2No 0.9 (0.7–1.0) 0.119 Yes 1.3 (0.8–2.4) Medicina 2021,57, 575 6 of 10 Table 2. Cont. Clinical Characteristics TNF-α, pg/mL p-Value Laboratory data 1 Hemoglobin, g/dL r=−0.343 0.101 Leukocyte count, 109/L r= 0.167 0.436 Neutrophil count, 109/L r= 0.186 0.385 Lymphocyte count, 109/L r=−0.352 0.870 Platelet count, 109/L r= 0.195 0.360 Fasting glycaemia, mg/dL r= 0.395 0.056 Percentage of glycosylated hemoglobin r= 0.418 0.042 Creatinine, mg/dL r= 0.362 0.082 Total cholesterol, mg/dL r= 0.129 0.549 LDL-cholesterol, mg/dL r=−0.094 0.662 HDL-cholesterol, mg/dL r=−0.271 0.201 Triglycerides, mg/dL r= 0.429 0.037 Soluble CD40 ligand, ng/mL r= 0.170 0.427 C-reactive protein, mg/L r= 0.407 0.048 ∆CtmiRNA 1 miR-21 r= 0.278 0.199 miR-27b r= 0.328 0.198 miR-29a r= 0.189 0.627 miR-126 r= 0.374 0.139 miR-146a r= 0.500 0.035 miR-218 r= 0.408 0.423 1 Correlations between TNFα levels and continuous variables were tested and the correlation coefficient (r) is presented for each; 2TNF-αlevels were compared between groups for categorical variables and are expressed as the mean (standard deviation) or median (interquartile range); 3 the left main artery, left anterior descending artery, circumflex artery, and right coronary artery were scored individually. ACE—angiotensin-converting enzyme; ARB—angiotensin II receptor blocker; CABG—coronary artery bypass grafting; HDL—high-density lipoproteins; LDL—low-density lipoproteins; TNF-α—tumor necrosis factor alpha; ∆Ct—delta cycle threshold. Table 3. Parameters associated with TNF-αlevels in multivariate analysis. Parameters Associated with TNF-αLevels β95% CI p-Value Serum triglyceride levels 0.003 0.001–0.004 0.008 ∆CtmiR-146a 0.111 0.026–0.196 0.014 95% CI—95% confidence interval; TNF-α—tumor necrosis factor alpha; ∆Ct—delta cycle threshold. 3.4. MiR-146a Expression in Patients with Stable Coronary Artery Disease miR-146a expression levels were not associated with other metabolic or inflammatory parameters, including the percentage of glycosylated hemoglobin, serum triglyceride levels, or C-reactive protein levels (Supplementary Material, Table S1). There was a positive correlation between ∆ C t miR-146a and the number of coronary vessels with obstructive disease (r= 0.556, p= 0.017), indicating lower expression levels of miR-146a in association with a higher severity of coronary artery disease. 4. Discussion In this prospective study, three main findings were noted: in patients with SCAD, metabolic and epigenetic (miRNA) mediators were associated with TNFα expression; miR-146a expression levels were negatively correlated with TNFα levels, irrespective of other metabolic and inflammatory parameters; and miR-146a expression levels were negatively correlated with the severity of coronary artery disease. Identifying major inflammatory regulators in SCAD is relevant for providing insights into its pathophysiology as well as for clinical practice, since such regulators may be useful as biomarkers and possible therapeutic targets [ 20 , 36 ]. TNFα is a proinflammatory agent with a distinct mechanism of action compared with other inflammatory mediators, which reinforces the relevance of clinical investigation addressing TNFα regulation in Medicina 2021,57, 575 7 of 10 atherosclerosis [ 5 ]. Moreover, TNFα is a proatherogenic agent and closely associated with prognosis in patients with coronary artery disease [ 2 , 6 , 7 ]. Different anti-TNFα therapies have been studied in patients with documented atherosclerosis, although the clinical results were not entirely consistent [ 8 – 10 ] and further insights are warranted regarding the regulation of TNF-αin patients with SCAD. In this study, metabolic dysregulation, characterized by a higher percentage of glycosylated hemoglobin or higher serum triglyceride levels, was associated with higher TNFα levels, which is consistent with the reports from preclinical models [ 11 – 16 ]. Of note, TNFα may itself promote hyperglycemia and dyslipidemia, thereby further increasing cardiovascular risk [ 37 , 38 ]. Data on the association between epigenetic mediators and TNFα expression are scarce. miR-146a was reported to suppress the inflammatory response, including TNFα expression, by dampening the NFκ B pathway through interleukin 1 receptor-associated kinase, in experimental models [ 18 , 39 ]. In humans, a negative correlation between miR-146a expression levels and TNFα levels has been described in patients with noncardiac inflammatory diseases, although such an association has not been described in patients with SCAD [ 40 , 41 ]. Consistently, we observed a negative correlation between miR-146a expression levels and TNFα levels. Of note, such association was independent of other metabolic and inflammatory parameters, which are frequently abnormal in SCAD and influence TNFα expression [ 11 – 17 ]. Moreover, the association between miR-146a expression levels and TNFα levels was independent of other clinical parameters, including the pharmacological therapy, as demonstrated in uniand multivariate analyses. These results support an independent role of miR-146a in the regulation of TNFα -induced inflammation in SCAD. We observed that miR-146a was negatively correlated with the severity of coronary artery disease. These results are consistent with data previously reported by our research group regarding the association between lower miR-146a expression levels and the extent of atherosclerosis to multiple arterial territories and higher severity of atherosclerosis in different territories [ 42 ]. Complementary atheroprotective and anti-inflammatory effects of miR-146 have been reported in experimental studies [ 19 , 21 , 43 – 45 ], which support the association between miR-146a expression levels and severity of coronary artery disease observed in this study. miR-146 is induced in endothelial cells in response to proinflammatory cytokines and acts as a negative feedback regulator of inflammatory signaling in endothelial cells by dampening the activation of proinflammatory transcriptional programs, including the NFκ B (as aforementioned), AP-1, and MAPK/EGR pathways, and by promoting eNOS expression [ 19 , 21 , 43 ]. The enhancement of miR-146 levels in the monocyte-macrophage lineage was also shown to suppress the NFκ B pathway and thus reduce macrophage activity [ 44 ]. Moreover, miR-146 targets the Toll-like receptor 4, reducing the formation of foam cells [ 45 ]. Therefore, miR-146 contributes to reduce vascular inflammation and atherosclerosis by targeting endothelial cells and the monocyte–macrophage lineage. The interaction between miR-146a and TNFα [ 39 ] may be particularly relevant in such context. The results of this study support the role of miR-146a in inflammation and atherosclerosis. Our findings and reported experimental data [ 18 , 19 , 21 , 39 , 43 – 45 ] suggest that miR-146a may be further investigated as a therapeutic target, complementary to other diseasemodifying strategies, such as glycemic and lipid control. Specifically, the use of miR-146 mimics in patients with SCAD presenting enhanced inflammatory activation based on TNFα levels may be a potential field of research [ 46 ]. Interestingly, lower miR-146a expression levels were reported to be associated with no response to an anti-inflammatory therapy in patients with COVID-19 and worse adverse outcomes [ 47 ]. This reinforces miR-146 as a potential target in experimental models of SCAD, considering the key role of inflammation in the regulation of atherosclerosis, particularly the TNF-αpathway. There are strengths of this study that should be acknowledged. As far as we know, this is the first report describing the association between miR-146a expression levels and TNFα levels in patients with SCAD. On the other hand, the multivariate analysis carried out increased the consistency of results by pointing to an independent association Medicina 2021,57, 575 8 of 10 between miR-146a and TNFα , irrespective of other metabolic and inflammatory parameters, which are frequently dysregulated in SCAD and influence TNFα levels [ 11 – 17 ]. Moreover, the association between miR-146a and coronary artery disease severity added further to the consistency of the results. Finally, the results are in line with those from the experimental investigation [18]. Study Limitations The sample size was small and the results should be interpreted with caution. Nevertheless, the sample size allowed to detect a significant association between miR-146a expression levels and TNFα levels and to adjust for confounders, which supports the validity of the results. Furthermore, the results are consistent with the preclinical data [ 18 ]. Of note, the sample included mostly male patients and the results may not be applicable to female patients. Larger prospective studies including a higher proportion of females are warranted for performing an external validation. On the other hand, a causal effect between miR-146a and TNFα cannot be established based on the results of this study. Nevertheless, the adjustment for confounders in the multivariate analysis and the consistency of the results with the aforementioned experimental data [ 18 ] suggest that miR-146a is likely a regulator of TNF-αexpression in patients with SCAD. 5. Conclusions Metabolic and epigenetic (miR-146a) mediators were associated with TNFα expression in patients with SCAD. miR-146a expression levels were negatively correlated with TNFα levels, irrespective of other metabolic or inflammatory parameters, and with the severity of coronary artery disease. The results provide insights into the pathophysiology of inflammation in stable atherosclerosis, particularly the role of miR-146a in TNFα -based inflammation in SCAD, and support future research on the potential therapeutic use of miR-146a in such a clinical scenario. Supplementary Materials: The following are available online at https://www.mdpi.com/article/10 .3390/medicina57060575/s1, Table S1: Clinical and laboratory parameters associated with miR-146a expression levels. Author Contributions: Conceptualization, T.P.-d.-S., P.N. and M.M.C.; methodology, P.N., M.C.C. and A.F.G.; validation, P.N., M.C.C., A.F.G. and F.J.E.; formal analysis, T.P.-d.-S. and P.N.; investigation, T.P.-d.-S., P.N., M.C.C., A.F.G., M.S. and F.S.; resources, M.S. and F.S.; data curation, T.P.-d.-S., M.S. and F.S.; writing—original draft preparation, T.P.-d.-S. and P.N.; writing—review and editing, T.P.-d.-S., P.N., M.C.C., A.F.G., M.S., F.S., F.J.E., R.C.F. and M.M.C.; visualization, T.P.-d.-S.; supervision, P.N., R.C.F. and M.M.C.; project administration, P.N. and M.M.C. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the ethics committees of the involved institutions (Centro Hospitalar Universitário de Lisboa Central, Nr. 245/2015, in 1 October 2015, and NOVA Medical School | Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Nr. 000176, in 11 November 2015). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available due to personal data protection. Acknowledgments: This study is part of the Ph.D. thesis program of one of the authors (T.P.-d.-S.), supervised (M.M.C.) and co-supervised (P.N.) by the other two, conducted at NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Lisbon, Portugal. 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