Association of Epicardial, Visceral, and Subcutaneous Fat With Cardiometabolic Diseases

Abstract

Background: Excess of visceral fat is a central factor in the pathogenesis of metabolic syndrome (MetS) and atherosclerosis. However, little is known about how much epicardial fat affects cardiometabolic disorders in comparison with visceral or subcutaneous fat.

Methods and Results: Participants suspected as having angina pectoris underwent cardiac computed tomography (CT) imaging. Of them, 374 subjects were analyzed the association of clinical characteristics and CT-based fat distribution measured as epicardial fat volume (EFV), visceral fat area (VFA), and subcutaneous fat area (SFA). EFV was highly associated with VFA (R=0.58). Serum adiponectin was significantly decreased in high VFA subjects (VFA ≥100 cm²) and was also reduced in the high EFV group (EFV ≥80 cm³). Among the low VFA groups, the numbers of subjects with diabetes and coronary atherosclerosis were increased in high EFV group. Among the low EFV groups, the numbers of subjects with diabetes, hyperuricemia, and coronary atherosclerosis were increased among the high VFA subjects. In an age-, sex-, and body mass index (BMI)-adjusted model, EFV was associated with dyslipidemia and MetS, and VFA was significantly associated with hypertension, dyslipidemia, MetS, and coronary atherosclerosis, while SFA was not related with coronary risks and atherosclerosis.

Conclusions: Epicardial fat accumulation may be a risk for coronary atherosclerosis in subjects without visceral fat accumulation. Visceral fat is the strongest risk for cardiometabolic diseases among the 3 types of fat depot.

Visceral fat accumulation is located upstream in the pathogenesis and development of metabolic syndrome (MetS), a clustering of diabetes (DM), dyslipidemia (DL), and hypertension (HT).¹ Importantly, excessive visceral fat causes atherosclerotic cardiovascular events through metabolic complications and dysregulation of adipocytokines (e.g., an increase in the level of plasminogen activator inhibitor type-1 (PAI-1) and a decrease in that of adiponectin).^2–5 Visceral fat has been shown to be a significant player in MetS and atherosclerosis, compared with subcutaneous fat,^6–8 suggesting that fat distribution should be more important than body mass index (BMI).

Epicardial fat tissue is anatomically located on and around coronary arteries and the myocardium. Epicardial fat volume (EFV) can now be measured, thanks to technical advances in computed tomography (CT), and its clinical associations, especially with cardiovascular diseases, have been studied. Increasing evidence indicates a close association between EFV and atherosclerotic coronary artery disease (CAD).⁹ However, little is known about the extent to which epicardial fat is related to cardiometabolic disorders compared with visceral and subcutaneous fat.

Methods

The clinical significance of epicardial, visceral, and subcutaneous fat tissue accumulation was investigated in 374 subjects who underwent cardiac CT.

Subjects

The present study was a physician-initiated observational study entitled “Correlation between adiponectin, coronary atherosclerosis, and volume of epicardial fat detected by cardiac CT (CACAO)” and a non-company sponsored single-center registry. From September 2013 to March 2016, patients admitted to KKR Otemae Hospital because of symptoms suspicious for angina pectoris and/or abnormality on ECG or ultrasonic cardiography, and who were examined by cardiac CT imaging comprised the study group. After excluding patients undergoing percutaneous coronary intervention/coronary artery bypass grafting, implantation with a permanent pacemaker, undergoing hemodialysis, treatment with pioglitazone, or contraindicated for contrast agents, 374 subjects (229 males, 145 females) were finally enrolled. Written informed consent was given by all participants after an explanation of the purpose of study. The study protocol complied with the guidelines for epidemiologic studies issued by the Ministry of Health, Labour and Welfare of Japan, was approved by the human ethics committees of KKR Otemae Hospital and Osaka University Hospital, and was also registered with the University Hospital Medical Information Network (No. UMIN000014419).

Clinical Parameters

Obesity was defined as BMI >25 kg/m² according to the criteria of the Japan Society for the Study of Obesity.¹⁰ Waist circumference was measured at the umbilical level with an inelastic tape while the patient was standing.

DM was defined according to the criteria of the Japan Diabetes Society¹¹ (i.e., HbA1c ≥6.5%, fasting glucose ≥126 mg/dL, casual glucose ≥200 mg/dL, or treatment for diabetes). HT was defined as systolic blood pressure (SBP) ≥140 mmHg, diastolic BP (DBP) ≥90 mmHg, or treatment with antihypertensive agents. DL was defined as fasting triglycerides (TG) ≥150 mg/dL, total cholesterol (T-Cho) ≥220 mg/dL, low-density lipoprotein cholesterol (LDL-C) ≥140 mg/dL, high-density lipoprotein cholesterol (HDL-C) <40 mg/dL, or treatment with lipid-lowering agents. Hyperuricemia was diagnosed as serum uric acid ≥7 mg/dL or treatment with uric acid-lowering agents, according to the Japanese criteria.¹² Smoking habit was evaluated as tobacco smoking during the past year and drinking habit was assessed as alcohol drinking at least twice weekly. Estimated glomerular filtration rate (eGFR) was calculated by the following formula: [eGFR=194×(serum creatinine^−1.094)×(age^−0.287)×F (male, F=1; female, F=0.739)].¹³ Serum adiponectin concentration was measured by enzyme-linked immunosorbent assay kit (Otsuka Pharmaceutical Co., Ltd., Tokushima, Japan).

MetS was defined as VFA ≥100 cm² and >2 risk components of the following: (1) DL: fasting TG ≥150 mg/dL, and/or HDL-C <40 mg/dL, and/or treatment with lipid-lowering agents; (2) HT: SBP ≥130 mmHg, and/or DBP ≥85 mmHg, and/or treatment with antihypertensive agents; (3) hyperglycemia: fasting glucose ≥110 mg/dL and/or treatment with glucose-lowering agents.¹⁴ Risk factors for CAD were assessed as DM, DL, HT, and smoking habit.

Multidetector CT Imaging

While positioned supine within the gantry of the MDCT scanner, the subjects underwent imaging with a 64-slice multidetector CT (MDCT) (TOSHIBA Aquilion64, Toshiba Medical Systems Corporation, Tochigi, Japan) and iopamidol as contrast agent after sublingual administration of nitroglycerine. Subjects with tachycardia were pretreated with 0.125 mg/kg of rangiolol to decrease their heart rate to <80beats/min. The MDCT scan parameters were 64×0.5 mm collimation, 180–220 mm field of view (manually adjusted), 0.35-s rotation time, 0.23-s scan time per table position, 120 kVp, and 35–210 mAs (automatically decided depending on the physique). Scan duration was ∼10 s, depending on heart rate and the patient’s size. The whole volume was reconstructed from the raw data with an intermediate reconstruction algorithm in overlapping data sets of 0.5-mm thick sections.

Agatston score,¹⁵ an index of coronary artery calcification, was semi-automatically quantified by Ziostation (Ziosoft Inc., Tokyo, Japan). Stenosis of the coronary artery was scored as follows: 0, 0–25% stenosis; 1, 25–50% stenosis; 2, 50–75% stenosis; 3, 75–100% stenosis. The presence of coronary atherosclerosis was defined as >25% stenosis. The numbers of diseased vessels and sites were counted as >25% stenosis. Plaque was classified as calcified, fibrous, mixed (calcified and fibrous), or none.

Measurements of Fat Tissue

Epicardial fat was quantified as a fat volume by Ziostation. Heart tissue and epicardium were manually traced on 3D images and then the epicardial sac was semi-automatically extracted by subtracting the myocardium and cavity. Within the region of interest, fat was defined as pixels within a window of −115 to −25 Hounsfield units. EFV was defined as adipose tissue located within the epicardial sac. Visceral fat area (VFA) and subcutaneous fat area (SFA) were semi-automatically measured in the umbilical portion by FAT-SCAN (East Japan Institute of Technology Co., Ltd., Ibaragi, Japan).¹⁶

Statistical Analysis

Continuous variables are presented as mean±standard deviation, and categorical variables are shown as counts and percentages. Fisher’s exact test was used to compare categorical variables between groups. Student’s t-test was used to compare continuous variables. The Wilcoxon rank-sum test and chi-square approximation were used to compare continuous variables that were not normally distributed (e.g., TG, adiponectin, VFA, SFA, EFV, Agatston score, numbers of diseased vessels and sites, and coronary atherosclerosis). Pearson’s chi-square test was used to compare plaque properties. The significance level was set at P<0.05. The software program JMP pro11 (SAS Institute Inc., Cary, NC, USA) was used to analyze all data.

Results

Baseline Characteristics

Clinical characteristics of the enrolled subjects are shown in Table 1. Mean age was 65.6 years, 61.2% were male, and mean BMI was 24.4 kg/m². As for coronary risk factors, prevalence of smokers, DM, HT, DL, and MetS were 25%, 28%, 58%, 68%, and 37%, respectively. Mean serum adiponectin level was 8.7±5.0 μg/mL. Mean number of coronary risk factors, including DM, HT, DL, and smoking, was 1.8±1.0. Mean VFA, SFA, and EFV were 118 cm² (male, 133 cm²; female, 93 cm²), 169 cm² (male, 160 cm²; female, 182 cm²), and 86 cm³ (male, 94 cm³; female, 74 cm³), respectively. Mean numbers of diseased vessels and sites were 1.4±1.2 and 3.0±3.1, respectively. Among the participants, the number of subjects without coronary atherosclerosis was 120 and those of patients with coronary atherosclerosis were as follows: single vessel, n=81; double vessel, n=74; triple vessel, n=99.

Table 1. Characteristics of Participants Categorized by VFA and EFV

	All	Category				P value
		I (low VFA, low EFV)	II (low VFA, high EFV)	III (high VFA, low EFV)	IV (high VFA, high EFV)	I vs. II	I vs. III	II vs. IV	III vs. IV
No. of subjects (M/F)	374 (229/145)	112 (44/68)	37 (48/24)	72 (48/24)	153 (120/33)	0.56	<0.001	<0.001	0.071
Age, years	65.6±11.4	65.7±12.1	67.2±12.1	65.0±11.2	65.5±11.2	0.49	0.72	0.42	0.76
Weight, kg	63.8±13.0	54.0±9.4	61.8±12.3	63.7±11.4	71.5±11.0	<0.001	<0.0001	<0.0001	<0.0001
BMI, kg/m2	24.4±3.7	21.6±2.5	24.4±3.9	24.2±3.4	26.5±3.2	<0.0001	<0.0001	<0.001	<0.0001
WC, cm
Males	90.0±10.0	78.8±8.7	88.9±8.4	88.7±7.6	94.6±7.9	<0.0001	<0.0001	<0.01	<0.0001
Females	84.2±10.6	79.4±8.5	83.8±9.5	84.7±11.3	93.6±8.2	0.077	<0.05	<0.001	<0.001
Hip circumference, cm
Males	96.5±6.8	90.0±5.5	96.3±6.3	96.2±6.1	98.9±6.1	<0.001	<0.0001	0.12	<0.05
Females	93.0±7.1	89.8±5.9	94.4±8.1	93.7±8.0	97.8±4.8	<0.05	<0.05	0.086	<0.05
VFA, cm2	117.7±51.5	66.6±17.9	78.7±12.9	135.3±38.7	155.7±40.6	<0.001	<0.0001	<0.0001	<0.001
SFA, cm2	168.7±70.8	132.8±60.5	184.3±67.9	162.4±65.2	194.2±69.7	<0.0001	<0.01	0.44	<0.01
EFV, cm3	86.4±40.9	49.9±17.5	98.1±18.1	59.2±15.8	122.6±31.7	<0.0001	<0.001	<0.0001	<0.0001
Smoking, n (%)	94 (25)	21 (19)	6 (24)	17 (24)	50 (33)	0.81	0.46	0.07	0.21
Diabetes, n (%)	103 (28)	14 (13)	11 (30)	21 (29)	57 (37)	<0.05	<0.01	0.45	0.29
HT, n (%)	217 (58)	54 (48)	19 (51)	45 (63)	99 (65)	0.85	0.07	0.19	0.77
DL, n (%)	254 (68)	69 (62)	21 (57)	43 (60)	121 (79)	0.70	0.88	<0.05	<0.01
MetS, n (%)	138 (37)	0 (0)	0 (0)	38 (53)	100 (65)	–	<0.0001	<0.0001	0.079
Hyperuremia, n (%)	68 (18)	9 (8)	5 (14)	14 (19)	40 (26)	0.34	<0.05	0.13	0.32
Alcohol, n (%)	185 (49)	38 (34)	42 (58)	42 (58)	91 (59)	0.69	<0.01	<0.05	0.89
Systolic BP, mmHg	135.0±20.4	134.6±20.0	136.4±20.8	133.4±21.5	135.6±20.3	0.65	0.72	0.84	0.46
Diastolic BP, mmHg	77.9±13.7	76.2±13.4	78.9±11.2	75.7±14.2	79.9±14	0.27	0.83	0.67	<0.05
Glucose, mg/dL	121.1±42.0	107.1±39.6	116.6±35.9	126.4±39.8	129.8±43.5	0.20	<0.01	0.09	0.58
HbA1c, %	6.2±0.9	5.9±0.9	6.0±0.8	6.2±1.0	6.3±0.9	0.67	0.07	0.06	<0.05
T-Cho, mg/dL	202.8±38.7	207.8±45.6	195.6±32.2	197±37.9	203.4±34.9	<0.05	0.11	0.24	0.23
TG, mg/dL	162.9±128.5	125.1±106.5	139.4±69.7	162.3±170.0	195.3±124.4	0.07	<0.05	<0.01	<0.001
LDL-C, mg/dL	119.3±29.5	120.4±31.3	115.9±26.3	115.2±24.8	121.2±30.9	0.46	0.26	0.36	0.16
HDL-C, mg/dL	56.8±14.9	65.2±14.9	56.0±14.0	55.6±13.5	51.5±13.1	<0.01	<0.0001	0.07	<0.05
UA, mg/dL	5.6±1.5	5.0±1.2	5.3±1.8	5.6±1.5	6.1±1.4	0.25	<0.01	<0.01	<0.05
eGFR, mL/min/1.73 m2	73.1±18.1	75.4±18.5	74.8±19.7	71.9±16.3	71.7±18.1	0.86	0.20	0.36	0.92
BNP, pg/mL	63.3±151.3	56.8±102.9	73.7±133.8	99.4±204.6	49.8±156.0	0.44	0.08	0.40	0.06
CRP, mg/dL	0.37±1.43	0.24±0.83	0.32±0.71	0.50±1.56	0.42±1.79	0.06	0.16	0.73	0.78
Adiponectin, μg/mL	8.7±5.0	11.6±5.5	10.1±5.2	8.3±4.5	6.4±3.5	0.14	<0.0001	<0.0001	<0.001
No. of coronary risks	1.8±1.0	1.4±0.8	1.5±1.0	1.8±1.0	2.1±0.9	0.45	<0.05	<0.001	<0.01
Agatston score	249.2±523.6	196.6±434.7	373.9±715.3	296.0±594.5	234.8±489.4	<0.05	0.20	0.17	0.42
No. of diseased vessels	1.4±1.2	1.2±1.2	1.6±1.2	1.6±1.1	1.5±1.2	<0.05	<0.05	0.47	0.59
No. of diseased sites	3.0±3.1	2.4±2.9	3.5±3.0	3.3±3.2	3.2±3.6	<0.05	0.05	0.44	0.62
Coronary atherosclerosis, n (%)	254 (68)	63 (56)	29 (78)	55 (76)	107 (70)	<0.05	<0.01	0.31	0.31
Plaque property: mix/fibrous/calc/ none, n (%)	138/51/66/119 (37/13/18/32)	38/10/16/48 (34/9/14/43)	13/6/10/8 (35/16/27/21)	35/8/12/17 (49/11/17/24)	52/27/28/46 (34/18/18/30)	0.06	0.06	0.58	0.18

BMI, body mass index; BNP, B-type natriuretic peptide; BP, blood pressure; CRP, C-reactive protein; DL, dyslipidemia; EFV, epicardial fat volume; eGFR, estimated glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; HT, hypertension; LDL-C, low-density lipoprotein cholesterol; MetS, metabolic syndrome; SFA, subcutaneous fat area; T-Chol, total cholesterol; TG, triglycerides; UA, uric acid; VFA, visceral fat area; WC, waist circumference.

Correlations of VFA, SFA, and EFV

Correlations of the distributed fat tissues were firstly examined (Figure 1). EFV was significantly correlated with VFA (P<0.0001, R=0.58) and SFA (P<0.0001, R=0.44) (Figure 1A,B). There was also a significant correlation between VFA and SFA (P<0.0001, R=0.36) (Figure 1C).

Figure 1.

Correlations between VFA, SFA, and EFV. The P-values in (A–C) are <0.0001 and the R values are 0.58 (A), 0.44 (B), and 0.36 (C), respectively. EFV, epicardial fat volume; SFA, subcutaneous fat area; VFA, visceral fat area.

Effect of Visceral and Epicardial Fat

The data were next assessed after division of the subjects into 4 groups to understand the effects of VFA and EFV on clinical features. The median value of EFV was 81.9 cm³ (range 11.4–235.7 cm³) and thus subjects were divided at EFV 80 cm³. The cutoff value of VFA was adopted as 100 cm², which is a definite criteria for MetS in Japan. As shown in Figure 2, the enrolled subjects were divided as follows: Category I: VFA <100 cm² and EFV <80 cm³; Category II: VFA <100 cm² and EFV ≥80 cm³; Category III: VFA ≥100 cm² and EFV <80 cm³; Category IV: VFA ≥100 cm² and EFV ≥80 cm³.

Figure 2.

Categorization by VFA and EFV. Subjects were divided into 4 groups (categories I–IV) according to the accumulation of visceral and epicardial fat. Cutoff values were set at 100 cm² for visceral fat area (VFA), according to Japanese definite criteria for metabolic syndrome, and 80 cm³ for epicardial fat volume (EFV), based on a median value of EFV (81.9 cm³) in the present study.

Table 1 also shows the clinical characteristics of the categorized subjects. Of the coronary risk factors, smoking and HT were not associated among these categories. The number of DM subjects was significantly higher in categories II and III than in category I, and the number of DL subjects was largest in category IV, suggesting that not only visceral fat but also epicardial fat was associated with DM and DL. Serum TG level was significantly high in visceral fat-accumulated subjects (categories I vs. III and II vs. IV). Serum LDL-C level was not influenced by epicardial or visceral fat, although statins was highly used in categories II–IV (statin use: I, 15%; II, 60%; III, 50%; IV, 42%). Subjects with epicardial fat accumulation showed low levels of serum HDL-C (categories I vs. II and III vs. IV), but visceral fat accumulation was strongly associated with low HDL-C in the low EFV subjects (category I vs. III). The number of coronary risks was significantly high in the visceral fat-accumulation groups (categories I vs. III and II vs. IV). Interestingly, coronary risks were even increased with epicardial fat accumulation among high VFA subjects (category III vs. IV). As shown in Table 1 and Figure 3, the serum adiponectin level was significantly low in visceral fat-accumulated subjects (categories I vs. III and II vs. IV) and also decreased in epicardial fat accumulation (category III vs. IV).

Figure 3.

Serum adiponectin concentrations by the 4 categories in Figure 2. Box shows the interquartile range and bar shows the 5th–95th percentile. **P<0.001, ***P<0.0001.

Among the atherosclerotic parameters, Agatston score, numbers of diseased vessels and sites, and patients with coronary atherosclerosis were high for epicardial fat accumulation among subjects with VFA <100 cm² (category I vs. II). No significant changes were observed for plaque lesion property and the degree of coronary stenosis among these categories.

Association of Fat Depots With Cardiometabolic Disease

Table 2 shows the odds ratios (ORs) of cardiometabolic disease by epicardial, visceral, and subcutaneous fat accumulations with an increase in EFV, VFA, and SFA per 10 cm³, 10 cm², and 10 cm², respectively. In an age- and sex-adjusted model, accumulation of each fat type was significantly associated with DM, DL, and MetS, and visceral fat accumulation was also related to HT. Visceral fat accumulation tended to associate with coronary atherosclerosis (P=0.0639), whereas epicardial and subcutaneous fat was not statistically associated with coronary atherosclerosis (P=0.3058 and P=0.9891, respectively). After further adjustment for BMI, epicardial fat accumulation was associated with DL and MetS (P=0.0002 and P<0.0001, respectively). For subcutaneous fat, there were no significant associations with DM, HT, DL, and coronary atherosclerosis. In addition, subcutaneous fat accumulation was a negative risk for MetS (OR=0.926, P=0.0076). However, visceral fat accumulation was significantly associated with HT, DL, MetS, and coronary atherosclerosis (P=0.0085, P<0.0001, P<0.0001, and P=0.0294, respectively).

Table 2. Multivariable ORs of Cardiometabolic Disease According to Fat Distribution

	EFV		VFA		SFA
	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value
Age and sex adjusted
DM	1.107 (1.045–1.174)	0.0005	1.049 (1.007–1.099)	0.013	1.054 (1.020–1.089)	0.0015
HT	1.057 (1.002–1.117)	0.0405	1.082 (1.033–1.135)	0.0004	1.042 (1.012–1.075)	0.0061
DL	1.129 (1.063–1.204)	<0.0001	1.135 (1.077–1.200)	<0.0001	1.018 (0.987–1.052)	0.2596
MetS	1.211 (1.141–1.291)	<0.0001	1.384 (1.292–1.492)	<0.0001	1.061 (1.029–1.096)	0.0002
Coronary atherosclerosis	1.031 (0.972–1.096)	0.3058	1.043 (0.998–1.098)	0.0639	1.000 (0.969–1.032)	0.9891
Age, sex and BMI adjusted
DM	1.045 (0.973–1.121)	0.2252	1.013 (0.985–1.052)	0.3435	0.960 (0.906–1.016)	0.1564
HT	1.025 (0.961–1.095)	0.4543	1.070 (1.014–1.133)	0.0085	1.033 (0.981–1.088)	0.2195
DL	1.147 (1.065–1.241)	0.0002	1.160 (1.089–1.241)	<0.0001	0.989 (0.935–1.046)	0.7062
MetS	1.130 (1.053–1.216)	<0.0001	1.361 (1.261–1.477)	<0.0001	0.926 (0.872–0.980)	0.0076
Coronary atherosclerosis	1.042 (0.970–1.122)	0.2615	1.064 (1.005–1.132)	0.0294	1.002 (0.948–1.059)	0.9297

CI, confidence interval; DM, diabetes mellitus; OR, odds ratio. Other abbreviations as in Table 1.

Discussion

As shown in Table 2, VFA had a significantly effect on the occurrence of cardiometabolic disease under age-, sex-, and BMI-adjusted multivariate analysis. EFV was only associated with DL and MetS, and SFA had no effect on cardiometabolic disease. Similar results were obtained even when MetS was defined by waist circumstance (data not shown). Several clinical investigations have been performed to clarify the significance of cardiac fat. The Framingham Heart Study Offspring cohort showed a significant association between cardiac fat tissue and CAD including coronary artery calcification.^17,18 However, similar to the present results, visceral fat accumulation was the stronger correlate of most cardiometabolic risk factors.^17,18 Those reports also demonstrated no significant association of intrathoracic fat and CAD after adjustment for age and sex, but did not assess the clinical effect of subcutaneous fat accumulation.¹⁸ The Jackson Heart Study also demonstrated a significant association between cardiac fat accumulation and MetS, HT, and DM, but such associations were reduced after adjustment for visceral fat volume, suggesting that visceral fat was a stronger correlate of cardiometabolic risk than cardiac fat.¹⁹ Those results were consistent with the present study. Excessive visceral fat in the whole body may largely affect cardiometabolic disease compared with cardiac fat accumulation. Visceral fat accumulation causes various metabolic changes such as insulin resistance, HT, and DL, and finally leads to atherosclerosis partly but directly through dysregulation of adipocytokines as represented by hypoadiponectinemia.^4,5

VFA was weakly but significantly associated with coronary atherosclerosis, but EFV was not statistically related (Table 2). However, as shown in Table 1, among the low VFA groups (categories I and II), diabetes, calcification of the coronary artery, the numbers of diseased vessels and sites, and coronary atherosclerosis were higher in high EFV subjects (category II) than low EFV subjects (category I). These results suggested that EFV could be a risk factor for coronary atherosclerosis in subjects without visceral fat accumulation. Several studies have suggested a significant association of cardiac fat and coronary artery calcification and/or CAD.^20–23 Greif et al showed that pericardial fat volume ≥300 cm³ was the strongest independent risk for CAD after adjustment for age and sex, and serum adiponectin was negatively correlated with pericardial fat volume, but they did not show an association between CAD and accumulation of visceral and subcutaneous fat.²⁰ The present study also found that the serum adiponectin level was significantly lower in the high EFV group (category IV) than in the low EFV group (category III) among high VFA subjects. Such hypoadiponectinemia may affect the CAD risk.²⁴ However, the contribution of epicardial fat to the circulating adiponectin level has not been fully clarified and the mechanism for hypoadiponectinemia in epicardial fat accumulation remains to be elucidated.

Increasing evidence indicates there is chronic low-grade inflammation in obese-fat tissues, especially in visceral fat, and it reduces adiponectin production.¹ Several cytokines, such as tumor necrosis factor-α (TNF-α), also suppress adiponectin production.²⁵ Interestingly, the adiponectin protein level was significantly decreased in epicardial fat tissue isolated from patients with CAD compared with those without CAD,²⁶ suggesting that local production of adiponectin derived from epicardial fat is related to the development and prognosis of CAD. Recently, our group demonstrated that adiponectin accumulates in the endothelial cells and synthetic vascular smooth muscle cells of atherosclerotic lesions through the action of T-cadherin and this suppressed the development of atherosclerosis in apolipoprotein E (ApoE)-deficient mice fed a high-cholesterol diet.^27–29 Myocardial damage in myocardial infarction and myocarditis of a rodent model was actually reduced by transplantation of an adipocyte cell-sheet producing adiponectin into the heart tissue.^30,31 These results indicate that adiponectin acts locally as a cardiovascular protector.

Shimabukuro et al found that both the number of CD68⁺ cells (macrophages) and the mRNA level of interleukin-1β (IL-1β) in epicardial fat tissue was positively associated with EFV, and the epicardial adiponectin mRNA level was negatively related to EFV, and they also demonstrated that EFV was a strong determinant for CAD in combination with these 3 inflammatory and anti-inflammatory factors.³² Taken together, the evidence suggest that low-grade chronic inflammation in epicardial fat may influence coronary atherosclerosis, although the precise mechanism needs to be clarified in the future.

As shown in Table 2, SFA was a negative risk factor for MetS after adjustment for age, sex, and BMI. VFA is evidently connected to MetS and CAD, while the role of SFA in the development of cardiometabolic complications needs to be elucidated. Generally, the effect of SFA on cardiometabolic disease is weaker than that of VFA.^33–35 Similar to the present results, there are studies indicating that SFA has a negative association with cardiometabolic parameters, including MetS.^36–38 Jung et al interestingly showed that SFA was inversely and significantly related to carotid atherosclerosis in male diabetic patients.³⁶

Study Limitations

Several should be taken into consideration. First, the number of subjects was relatively small. Second, 10–30% of patients were on medication for DM, HT, or DL, so there is a possibility that the severity of coronary atherosclerosis, fat distribution, and serum adiponectin concentration were influenced by some medicines. Third, coronary atherosclerosis was evaluated only by MDCT, not by coronary angiography. Fourth, the inclusion and exclusion criteria may have affected the results. Fifth, because it was a cross-sectional study, the results do not imply causality between fat deposition and cardiometabolic risk.

Conclusions

Epicardial fat accumulation may be a risk factor for coronary atherosclerosis in subjects without visceral fat accumulation. Importantly, visceral fat was the strongest risk for cardiometabolic disease compared with epicardial and subcutaneous fat, although further investigation will be needed in future.

Acknowledgments

We thank Kayoko Ohashi for excellent technical assistance, especially in the measurement of adiponectin, and all the members of the Third Laboratory (Adiposcience Laboratory), Department of Metabolic Medicine, Graduate School of Medicine, Osaka University, and Department of Cardiology, KKR Otemae Hospital, for their helpful discussion of the project.

Ethics Approval and Consent to Participate

Written informed consent was obtained from each patient after explaining the purpose of study. The study protocol was approved by the human ethics committees of KKR Otemae Hospital and Osaka University, and was also registered with the University hospital Medical Information Network (Number: UMIN 000014419).

Consent for Publication

All authors read and approved the final manuscript.

Availability of Data and Material

Not applicable.

Competing Interests

The authors declare that they have no competing interests.

Funding

This work was supported in part by JSPS KAKENHI Grant Number JP25461386 (to N.M.) and JP26293221 (to T.F.), Takeda Science Foundation (to N.M.), and Japan Foundation for Applied Enzymology (to Y.F.). The funding agencies had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Authors’ Contributions

F.S. acquired and analyzed data, and wrote the manuscript. N.M. conceived the study design, analyzed data, and wrote the manuscript. T.Y. acquired data and participated in the discussion and interpretation of data. H. Namazui acquired and analyzed data. S.F., T.N., H. Nagao, J.M., S.M., Y.T., Y.O., Y.F., H. Nishizawa, and T.F. participated in the discussion and interpretation of data. I.S. participated in the discussion and interpretation of data, and reviewed the manuscript. All authors read and approved the final version of the manuscript.

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