Background
Diabetes mellitus (DM) is one of the most common metabolic diseases worldwide and is characterized as a metabolic disorder of carbohydrates, proteins and lipids [
1]. In recent years, the incidence of DM has gradually increased, becoming a serious public health threat [
2,
3]. DM can be divided into type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), gestational diabetes mellitus (GDM) and other types of diabetes. Abnormally accumulated visceral fat is a risk factor for insulin resistance, which can reduce insulin sensitivity, increase the expression and secretion of proinflammatory cytokines in adipose tissue and promote the development of DM and cardiovascular diseases [
4‐
7].
Epicardial fat tissue (EFT) is a visceral adipose tissue that surrounds the myocardium and pericardium. It is one of the visceral fat stores in the body. Previous studies have suggested that measurements of EFT are a substitute for visceral fat [
8,
9] EFT can secrete inflammatory factors, such as TNF-alpha, IL-6, adipocytokines, and leptin, via paracrine or endocrine activities [
9,
10] to locally regulate the myocardium and coronary artery function and regulate lipid and energy homeostasis in vivo. EFT has the ability to release and uptake free fatty acids and to affect low glucose utilization, which plays an important role in metabolic syndrome and coronary artery disease [
11‐
16]. EFT can be measured by echocardiography, cardiac magnetic resonance imaging, and computed tomography (CT) [
17]. Recent studies have confirmed that EFT is associated with obesity, fasting blood glucose levels, insulin resistance, and adiponectin in patients with T2DM, and an increase in EFT was observed in patients with T1DM and T2DM [
18‐
22].
In the past few years, several studies have reported that EFT is abnormally increased in DM patients. However, small sample sizes and potential confounders (such as differences in EFT measurements and DM typing) can affect the strength of previous evidence. Therefore, in this study, we conducted a meta-analysis to evaluate the effect of DM on EFT volume to provide a comprehensive overview of this issue.
Methods
We conducted this meta-analysis in strict accordance with the PRISMA reporting specifications.
Search strategy
According to the PRISMA guidelines [
23], we developed a detailed search strategy. We systematically searched online databases (PubMed, EMBASE, Cochrane Library, and Web of Science) up to 30 September 2018 and included all possible combinations of the following search terms: (diabetes mellitus OR Diabetes mellitus, type 2 OR diabetes mellitus, type 1) AND (epicardial fat tissue OR epicardial adipose tissue OR subepicardial adipose tissue OR subepicardial fat tissue). This study was limited to human studies published in English studies.
Inclusion criteria
Identified studies were enrolled based on the following inclusion criteria: (1) DM patients were an experimental group and non-DM subjects were a control group; (2) quantitative measurement of EFT volume or thickness by echocardiography, cardiac magnetic resonance imaging or CT; (3) study of differences in EFT between DM patients and non–DM subjects; (4) the study reported a mean, standard deviation (SD), and sample size for DM patients and non-DM subjects; and (5) observational studies.
Exclusion criteria
During the literature screening process, studies containing the following items were excluded: (1) experimental animal studies, reviews, or non-English literature; (2) the study did not provide sufficient information about the dataset (mean, SD and sample sizes).
Data extraction and quality assessment
Two reviewers (Yingrui Li and Bin Liu) independently extracted data and assessed the quality of each study. If there was disagreement on a specific study, the two reviewers negotiated to reach a consensus. The data extracted from each study included the sample size and EFT of the experimental and control groups. Then, the Newcastle Ottawa scale (NOS) was used to assess the quality of the study. The scoring system consisted of three parts (population selection, comparability between groups, and exposure factors), and the results ranged from 0 to 9, with higher scores representing better methodology quality (Table
1).
Table 1
Characteristics of included studies
| China | Diabetes | II | 167 | 43.7 ± 10.9 | 22.6 ± 2.1 | 4.0 ± 1.5 mm | Echocardiography (end-diastole parasternal long axis) | 7 |
Non-diabetes | | 82 | 42.4 ± 10.2 | 22.0 ± 2.1 | 2.0 ± 1.5 mm | | |
| Turkey | Diabetes | I | 36 | 30.8 ± 7.7 | 24.7 ± 3.8 | 3.3 ± 1.1 mm | Echocardiography (end-diastole parasternal average axis) | 7 |
Non-diabetes | | 43 | 29.9 ± 4.9 | 24.6 ± 3.0 | 2.3 ± 0.3 mm | | |
| American | Diabetes | I | 15 | 52.8 ± 12.0 | 27.8 ± 5.2 | 7.2 ± 2.1 mm | Echocardiography (end-systole parasternal average axis) | 7 |
Non-diabetes | | 15 | 53.0 ± 9.0 | 27.4 ± 4.1 | 4.9 ± 2.5 mm | | |
| Turkey | Diabetes | II | 139 | 54.3 ± 9.2 | 27.6 ± 3.1 | 6.0 ± 1.5 mm | Echocardiography (end-diastole parasternal average axis) | 7 |
Non-diabetes | | 40 | 52.1 ± 7.3 | 29.1 ± 4.2 | 4.4 ± 1.0 mm | | |
| Turkey | Diabetes | II | 186 | 62.5 ± 9.6 | 28.6 ± 4.4 | 6.5 ± 0.7 mm | Echocardiography (End-systole parasternal average axis) | 7 |
Non-diabetes | | 268 | 61.2 ± 10.9 | 27.6 ± 4.2 | 5.3 ± 1.0 mm | | |
| Turkey | Diabetes | I | 76 | 30.6 ± 10.3 | 23.3 ± 2.7 | 3.6 ± 0.5 mm | Echocardiography (end-diastole parasternal average axis) | 7 |
Non-diabetes | | 36 | 32.4 ± 8.5 | 24.2 ± 2.7 | 3.0 ± 0.5 mm | | |
| China | Diabetes | II | 68 | 59.5 ± 9.9 | 26.9 ± 5.9 | 5.0 ± 1.2 mm | Echocardiography (end-diastole parasternal long axis) | 7 |
Non-diabetes | | 32 | 58.1 ± 9.2 | 23.7 ± 5.5 | 3.1 ± 0.8 mm | | |
| Brazil | Diabetes | II | 31 | 45.0 ± 6.0 | 36.0 ± 4.7 | 1.0 ± 0.3 mm | Echocardiography (end-systole parasternal average axis) | 7 |
Non-diabetes | | 37 | 36.0 ± 11.0 | 27.9 ± 7.4 | 0.7 ± 0.2 mm | | |
| China | Diabetes | II | 49 | 56.8 ± 9.5 | 27.2 ± 3.6 | 166.1 ± 60.6 cm3 | CT | 8 |
Non-diabetes | | 78 | 54.1 ± 6.5 | 25.4 ± 3.4 | 123.4 ± 41.8 cm3 | | |
| Turkey | Diabetes | I | 45 | 34 ± 7.7 | 24.1 ± 3.4 | 7.0 ± 2.3 mm | Echocardiography (end-diastole parasternal long axis) | 6 |
Non-diabetes | | 35 | 32 ± 7.3 | 26.7 ± 6.5 | 6.0 ± 1.5 mm | | |
| Turkey | Diabetes | II | 156 | 53.62 ± 9.33 | 31.21 ± 5.87 | 4.7 ± 1.6 mm | Echocardiography (end-diastole parasternal average axis) | 7 |
Non-diabetes | | 50 | 51.06 ± 8.74 | 32.86 ± 7.52 | 3.9 ± 1.6 mm | | |
| Turkey | Diabetes | II | 90 | 57.7 ± 11.4 | 28.9 ± 4.4 | 172.8 ± 64.9 cm3 | CT | 7 |
Non-diabetes | | 62 | 55.6 ± 10.7 | 26.5 ± 2.9 | 68.9 ± 37.7 cm3 | | |
| American | Diabetes | II | 44 | 56.0 ± 6.0 | 26.9 ± 3.2 | 6.4 ± 1.7 mm | Echocardiography (end-systole parasternal average axis) | 6 |
Non-diabetes | | 35 | 52.0 ± 7.0 | 24.2 ± 3.6 | 3.3 ± 1.1 mm | | |
Data analysis
All statistical analyses were performed using Stata 12.0 using a fixed effect model or a random effects model to calculate the pooled standard mean difference (SMD) or weighted mean difference (WMD) for a 95% CI. All reported
P values are two-sided with a significance level set at
P < 0.05. The heterogeneity of each study was assessed by calculating the
χ2 and I
2 statistics. If
P < 0.1 and I
2 > 30%, a random effects model was applied; otherwise, a fixed effects model was applied [
24]. Considering the potential impact of DM confounding factors on the results of the study, we performed a subgroup analysis of DM typing and EFT measurements. At the same time, we applied a sensitivity analysis to examine the impact of individual studies on the total merged effects to assess the reliability of the conclusions. We analyzed the symmetry of a funnel plot to evaluate possible small sample effects, and we used Begg’s test as well as Egger’s test to evaluate publication bias in the included studies. Statistical significance was considered at P < 0.10 [
25]. If publication bias was detected, the Duval and Tweedie’s trim and fill method was applied using the random effects model to evaluate the adjusted effect scale [
26]. Taking into account the differences between the studies, all our analyses used a random effects model.
Meta-regression is often used to explore the source and size of heterogeneity in a study and to further explain the impact of heterogeneity in a meta-analysis. We hypothesized that the included studies may have shown differences in cardiovascular disease risk factors (BMI, dyslipidemia, waist hip rate) in DM patients. To assess the possible effects of these variables on the different outcomes observed in the meta-analysis, we established a regression model with the EFT value as the dependent variable (y) and the abovementioned covariate as the independent variable (x).
In a conventional meta-analysis, repeated significance testing of cumulative data increases the overall risk of type I error; however, TSA can reduce the risk of type I error and estimate the required information size (RIS) needed to achieve a preset power level, draw benefit boundaries and harm boundaries, and calculate futility. An RIS used with boundaries can infer whether further studies are needed [
28]. We conducted the TSA with a 5% risk of a type I error and a power of 80% as well as an a-spending adjusted 95% CI for repetitive significance testing.
Availability of data and materials
All the data were extracted from public sources.
Discussion
This meta-analysis included 13 studies that contained 1102 patients with DM and 813 healthy subjects. Our analysis confirmed that DM is associated with an increase in EFT. Furthermore, our TSA results indicated that the available samples were sufficient and confirmed that firm evidence was reached; the sensitivity analysis further confirmed these findings. Regression analysis indicated that TC and TG levels significantly affected our results, and a subgroup analysis suggested that there were more abnormal EFTs in DM patients with different DM types and EFT measurements than in non-DM patients.
In recent years, research on the relationship between EFT and DM has gradually increased, but the reasons for the increase in EFT observed in DM patients has not been studied. Possible causes include decreased physical activity and an increased food supply, which lead to adipose tissue deposition in T2DM patients [
38]. Additionally, genes associated with lipid metabolism have been shown to be missing, dislocated and mutated in DM patients [
39]. Finally, T2DM patients regulate the distribution of sex steroids in body fat tissue (such as androgen) abnormally [
40]. Previous studies have shown that EFT is closely related to insulin levels in serum in addition to Resistin mRNA levels and may be involved in the formation of insulin resistance. A significant increase in EFT has also been observed in chronic systemic inflammation, such as obesity and hyperlipidemia. It has been suggested that it is also involved in abnormal lipid metabolism in the body [
41,
42].
To better understand the relationship between EFT and DM, a meta-analysis was conducted to explore the amounts of EFT in DM patients and non-DM patients. The results showed that the volume of EFT was significantly higher in DM patients with significant heterogeneity. To explore the source of heterogeneity, we conducted a subgroup analyses of different DM typing and EFT measurement methods. The heterogeneity in T1DM and the subgroup measuring EFT thickness during the systolic period decreased significantly, suggesting that different DM typing and different EFT measurement methods may be potential sources of heterogeneity.
T1DM and T2DM have very different pathogenesis and pathological processes, and EFT plays a specific role in both types of DM. Under pathological conditions, EFT can secrete a variety of bioactive adipokines and pro-inflammatory factors, such as TNF-alpha, IL-6, resistin, visfatin, omentin, and leptin [
43‐
47]. Previous studies have suggested that abnormal increases in visceral fat may play a major role in the development of insulin resistance and may therefore further promote DM [
48,
49]. In a study by Galletti et al. leptin inhibited insulin synthesis and secretion and increased insulin sensitivity [
50]. It has also been suggested that changes in leptin secretion or sensitivity may be related to the pathogenesis of T1DM, although these findings remain controversial [
50,
51]. The results of our subgroup analysis suggest that EFT is increased in both T1DM and T2DM, indicating that in the diagnosis and treatment of DM, EFT could be used as a new research target to promote the study of DM and provide new ideas for the clinical treatment of T1DM and T2DM.
EFT can be detected by ultrasound, CT and CMR, and EFT thickness measured by ultrasound has recently become a simple practical tool for cardiovascular risk stratification [
9]. Previous studies have suggested that magnetic resonance imaging is the gold standard for estimating systemic adipose tissue [
52,
53]. CMR and CT are not limited by the position and direction of the imaging plane, and it is therefore more accurate to evaluate the absolute amount of EFT compared with the ultrasound, which uses a single point measurement of EFT to assess the absolute amount of EFT. However, in the study by Iacobellis et al. EFT assessment of the right ventricular free wall by echocardiography showed an excellent correlation with the EFT measurements obtained by CMR [
8]. The results of our subgroup analysis showed that the volume of EFT was higher in DM patients than in non-DM patients regardless of the method of EFT measurement, suggesting that there was no significant difference among ultrasound, CT and CMR in the measurement of abnormal EFT increases in DM patients in clinical practice.
Epicardial adipose tissue is an extremely active adipose tissue with unique biological molecular and anatomical characteristics. It is not only a passive lipid storage unit but also an active participant in lipid and energy homeostasis in the myocardium. One of the biggest differences between EFT and other visceral fat is its greater ability to release and synthesize free fatty acids (FFA) [
12,
54]. Under physiological conditions, EFT exerts a cardioprotective effect through its anti-atherosclerosis/anti-inflammatory properties as well as its high FFA release and uptake rates [
55]. However, abnormally increased EFT can secrete a variety of bioactive substances and excessive fatty acids, which can lead to systemic inflammation, insulin resistance, abnormal blood lipid indexes, such as TC and TG, and ultimately lead to DM, metabolic syndrome and atherosclerosis [
56,
57]. Therefore, a meta-regression analysis was performed to evaluate other factors (BMI, LDL, HDL, TC, TG, and systolic blood pressure) that might have had an impact on the results. The results suggested that TC and TG affected the results of this study, while other risk factors did not.
Our study indicates that compared with non-DM patients, in DM patients, the amount of EFT is significantly increased, and this has considerable clinical significance for providing new ideas for the diagnosis and treatment of DM. In a study by Kang et al. 321 CAD patients who received high-dose statins were retrospectively studied, and the results showed that EFT thickness during the systolic period was an independent predictor of new DM in patients with coronary heart disease treated with high-intensity statins [
58]. At the same time, Chun et al. found that there was a significant correlation between left ventricular EFT thickness and the prevalence of diabetes in Korean men [
59]. In the studies by Bouchi et al. and Sato et al., the SGLT-2 inhibitors Dapagliflozin and Luseogliflozin both improved systemic inflammation and were used for EFT, thereby reducing the EFT volume of DM patients and thus reducing the risk of cardiovascular disease [
60,
61]. However, the clinical efficacy of these new therapies has not yet been confirmed, and further studies are needed [
62]. Previous research results are consistent with our meta-analysis results, but previous studies did not consider the impact of other confounding factors on the results. Our results suggest that even among different types of DM or different EFT measurement techniques, patients with DM always have an abnormal increase in EFT compared with patients without DM, suggesting that the abnormal increase of EFT can be used as an independent predictor of new DM and a new target for DM drug therapy.
Authors’ contributions
Study design: YRL, BL; Data collection and analysis: YRL, BL, YL; Article drafting: YRL, XDJ, SBD, YLY, SQ. All authors read and approved the final manuscript.