Recent studies have suggested that body size phenotype may contribute to atherosclerosis and cardiovascular disease. 18 F-fluorodeoxyglucose (FDG) positron emission tomography is a useful imaging technique for detecting vascular inflammation that may reflect plaque vulnerability. Therefore, we analyzed which body size phenotypes cause the increased vascular inflammation using FDG positron emission tomography. We compared 18 F-FDG uptake, measured using the blood-normalized standardized uptake value, known as the target-to-background ratio (TBR), along with various cardiometabolic risk parameters in 250 participants without a history of cardiovascular disease. Body size phenotypes were classified according to body mass index and the presence/absence of metabolic syndrome. Cardiometabolic risk factors were significantly different among the body size phenotype groups. In particular, the maximum TBR (maxTBR) values in the metabolically abnormal but normal-weight, metabolically healthy obese (MHO), and metabolically abnormal obese groups were significantly greater than those of the metabolically healthy normal-weight (MHNW) group. Components of metabolic syndrome, insulin resistance, high-sensitivity C-reactive protein, and Framingham Risk Score were associated with maxTBR value. Interestingly, although the Framingham Risk Score of the MHO group was almost similar to that of the MHNW group, maxTBR value of MHO subjects was significantly higher than that of MHNW subjects (1.38 [1.20, 1.50] vs 1.22 [1.12, 1.37], p = 0.006). In conclusion, the present study suggests that unique subsets of body size phenotype, such as MHO or metabolically abnormal but normal weight, may have distinct effects on vascular inflammation.
Metabolic disorders and clinical consequences related to obesity are diverse among obese individuals. Recently, increased interest has focused on individuals with unique body size phenotypes, such as metabolically healthy obese (MHO) and metabolically abnormal but normal weight (MANW). Inflammation is the crucial pathologic mechanism of atherosclerosis, from plaque initiation to rupture. The current screening imaging tool and conventional risk scoring systems for cardiovascular disease (CVD), such as carotid intima-media thickness, coronary artery calcium score, and Framingham Risk Score (FRS), have limitations in assessing inflammatory status and plaque vulnerability in vessels. Recently, positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) has been established as a useful imaging technique to identify vascular inflammation. 18 F-FDG uptake in the vessel wall is strongly correlated with macrophage infiltration, which reflects increased vascular vulnerability. However, to the best of our knowledge, there have been no clinical studies to explore the relation of body size phenotype with vascular inflammation. Therefore, the present study examined the degree of vascular inflammation among metabolically healthy normal weight (MHNW), MANW, MHO, and metabolically abnormal obese (MAO) subjects. Furthermore, we compared different clinical implications of the relations of body size phenotype with FRS and vascular inflammation measured by 18 F-FDG-PET/computed tomography (CT).
Methods
Participants were prospectively recruited based on inclusion and exclusion criteria from individuals who self-referred for a routine health checkup at the Health Promotion Center of Korea, University Guro Hospital, from March 2008 to March 2011. Participants were apparently healthy Korean men and women aged 20 to 80 years and residing in Seoul, South Korea. Subjects were excluded from this study if they met any of the following criteria: history of CVD (myocardial infarction, unstable angina, stroke, or cardiovascular [CV] revascularization); diabetes (defined as a fasting plasma glucose value ≥7.0 mmol/L or a previous diagnosis of type 1 or type 2 diabetes); stage 2 hypertension (blood pressure at rest of ≥160/100 mm Hg); any lipid-lowering therapies and postmenopausal hormone replacement therapy for at least the 6-month period before enrollment; history of inflammatory conditions that would affect the study results; taking medications that might affect inflammatory status, including steroid and nonsteroidal anti-inflammatory drugs within 6 months; or current malignancy or severe renal or hepatic diseases (serum creatinine, alanine aminotransferase, or aspartate aminotransferase levels greater than twice the upper limit of the laboratory reference range). All participants provided written informed consent, and the Korea University Institutional Review Board approved this study protocol in accordance with the Declaration of Helsinki of the World Medical Association.
Study subjects were classified according to body mass index (BMI) and the presence/absence of metabolic syndrome (MS). Obesity was defined according to criteria recommended by the Korean Society for the Study of Obesity, which defines “normal” as a BMI ≥18.5 and <25.0 kg/m 2 and “obese” as a BMI ≥25.0 kg/m 2 . MS was defined according to criteria established by the National Cholesterol Education Program Adult Treatment Panel III using the adjusted waist circumference for Asians. By combining the BMI and MS groups, all study subjects were classified into 4 groups: (1) normal weight without MS (MHNW), (2) normal weight with MS (MANW), (3) obese without MS (MHO), and (4) obese with MS (MAO).
PET/CT was performed using a GEMINI TF 16-slice PET/CT scanner (Philips Medical Systems, Cleveland, Ohio). The TF scanner is a new, high-performance, time-of-flight-capable, fully 3-dimensional PET scanner using lutetium-yttrium oxyorthosilicate crystals. The right carotid FDG uptake was measured along the length of the right carotid vessel, starting at the bifurcation and extending inferiorly and superiorly every 4 mm. The standardized uptake value (SUV) is the decay-corrected tissue concentration of FDG (in kBq/mL) divided by the injected dose per body weight (kBq/g). The arterial SUV was divided by the blood pool SUV measured from the jugular vein for normalization, thereby a maximum value of the target-to-background ratio (TBR) was acquired for each subject.
Differences among the groups were tested using analysis of variance for normally distributed variables or the Kruskal-Wallis H test for skewed variables, and subsequent comparisons were performed by Tukey’s HSD post hoc analysis or Mann-Whitney U test. Spearman correlation coefficient and partial Spearman correlation coefficient were used to evaluate the correlation between maximum TBR and metabolic risk factors. Differences of log-transformed maximum TBR and FRS values among the 4 groups were tested using an analysis of covariance after adjusting for age and gender. Differences of metabolic risk profiles according to the lower or the upper maximum TBR values in each MANW or MHO group were tested using the Student t test, Mann-Whitney U test, or Pearson chi-square test. All statistical results were based on 2-sided tests. Data were analyzed using SAS 9.2 (SAS Institute, Cary, North Carolina). p Values <0.05 were considered statistically significant.
Results
Among groups with different body size phenotypes, significant differences were found in blood pressures and high-density lipoprotein cholesterol, triglyceride, and fasting glucose levels ( Table 1 ). Waist circumference values in particular showed significant gradual increase across the MHNW, MANW, MHO, and MAO groups. However, there was no significant difference in the waist-to-hip ratio (WHR) between the MANW and MHO groups. Instead, the WHR of the MANW group was significantly higher than that of the MHNW group and lower than that of the MAO group. In contrast, the homeostasis model assessment insulin resistance (HOMA-IR) values of the MHNW, MANW, MHO, and MAO groups showed a progressively increasing trend, whereas there was no linear increase in circulating high-sensitivity C-reactive protein (hsCRP) levels. Serum hsCRP levels of the MANW group were significantly higher than those of the MHNW group and tended to be higher than those of MHO group, although the difference was not statistically significant. Interestingly, serum low-density lipoprotein (LDL) cholesterol levels showed no significant differences among the groups.
| Variables | MHNW | MANW | MHO | MAO | P-value |
|---|---|---|---|---|---|
| (N=108) | (N=30) | (N=59) | (N=53) | ||
| Age (years) | 53.56±9.18 a | 53.77±8.10 ab | 49.41±8.78 b | 49.51±10.04 b | 0.006 |
| Male | 46(42.59%) a | 15(50.00%) a | 16(27.12%) b | 16(30.19%) ab | 0.068 |
| Weight (kg) | 59.52±8.67 a | 63.42±8.37 a | 73.09±7.35 b | 78.23±10.04 c | <0.001 |
| Body mass index (kg/m 2 ) | 22.84(20.69,23.70) a | 23.65(22.49,24.00) b | 25.93(25.40,27.20) c | 27.64(26.23,29.76) d | <0.001 |
| Waist circumference (cm) | 79(75,84) a | 85.5(82,89) b | 88(86,91) c | 93(90,97) d | <0.001 |
| Waist to hip ratio | 0.86(0.84,0.90) a | 0.91(0.88,0.95) bc | 0.91(0.88,0.93) b | 0.93(0.90,0.95) c | <0.001 |
| Systolic blood pressure (mmHg) | 120(113.5,127.5) a | 132.5(123,143) b | 121(114,129) a | 132(127,139) b | <0.001 |
| Diastolic blood pressure (mmHg) | 80.5(73.0,85.5) a | 86(82,93) b | 81(76,86) a | 90(85,94) b | <0.001 |
| Total cholesterol (mg/dL) | 169.76±43.70 a | 179.81±37.51 ab | 177.49±147.18 ab | 189.87±40.60 b | 0.054 |
| HDL cholesterol (mg/dL) | 47.95(37.90,59.55) a | 34.03(30.94,42.92) b | 44.08(35.96,49.88) c | 39.06(32.10,44.08) b | <0.001 |
| Triglyceride (mg/dL) | 83.26(60.23,118.69) a | 172.72(113.37,209.03) b | 108.06(76.17,129.32) c | 169.18(108.95,218.78) b | <0.001 |
| LDL cholesterol (mg/dL) | 97.83(78.50,124.90) | 116.01(80.05,138.05) | 119.10(81.21,146.17) | 112.92(87.01,146.17) | 0.178 |
| FPG (mg/dL) | 81.07(72.06,90.97) a | 92.96(83.05,105.03) bc | 87.91(76.92,94.94) b | 99.98(85.93,108.09) c | <0.001 |
| hsCRP (mg/dL) | 0.42(0.20,1.06) a | 0.91(0.36,3.06) bc | 0.71(0.37,2.2) b | 1.55(0.72,3.15) c | <0.001 |
| HOMA-IR | 0.80(0.34,1.27) a | 1.04(0.44,1.88) ab | 1.44(0.60,1.85) b | 1.90(1.20,2.89) c | <0.001 |
Vascular inflammation, represented as maximum TBR value, had significant positive correlations with BMI, waist circumference, WHR, systolic and diastolic blood pressure, triglyceride, fasting glucose, hsCRP, HOMA-IR values, and FRS and a significant negative correlation with high-density lipoprotein cholesterol, even after adjusting for age and gender ( Table 2 ). In particular, the maximum TBR value of the high-risk FRS group was significantly greater than that of the low- and intermediate-risk FRS groups (p <0.001 and p = 0.001, respectively; Figure 1 ).
| Variables | Unadjusted | Age, gender adjusted | ||
|---|---|---|---|---|
| r | P-value | r | P-value | |
| Age | -0.032 | 0.615 | ||
| Gender | -0.232 | <0.001 | ||
| Weight | 0.301 | <0.001 | 0.230 | <0.001 |
| Body mass index | 0.283 | <0.001 | 0.258 | <0.001 |
| Waist circumference | 0.317 | <0.001 | 0.252 | <0.001 |
| Waist to hip ratio | 0.255 | <0.001 | 0.177 | 0.005 |
| Systolic blood pressure | 0.144 | 0.023 | 0.143 | 0.025 |
| Diastolic blood pressure | 0.215 | 0.001 | 0.188 | 0.003 |
| Total cholesterol | 0.105 | 0.096 | 0.123 | 0.053 |
| HDL cholesterol | -0.184 | 0.004 | -0.155 | 0.015 |
| Triglyceride | 0.261 | <0.001 | 0.222 | <0.001 |
| LDL cholesterol | 0.110 | 0.083 | 0.136 | 0.033 |
| Fasting plasma glucose | 0.179 | 0.005 | 0.169 | 0.008 |
| high-sensitivity C-reactive protein | 0.321 | <0.001 | 0.341 | <0.001 |
| HOMA-IR | 0.342 | <0.001 | 0.314 | <0.001 |
| Framingham risk scores | 0.262 | <0.001 | 0.187 | 0.003 |
Although the maximum TBR values of the MANW, MHO, and MAO groups were significantly higher than that of MHNW group (all p <0.01), there were no significant differences among the maximum TBR values of the MANW, MHO, and MAO groups. However, FRS fluctuated greatly according to body size phenotype ( Figure 2 ). The FRS of the MANW group was significantly higher than that of the MHNW group and similar to that of the MAO group. Although the maximum TBR value of MHO subjects was significantly greater than that of the MHNW subjects (1.38 [1.20, 1.50] vs 1.22 [1.12, 1.37], p = 0.006), the FRS of the MHO group was similar to that of the MHNW group. Furthermore, the FRS of the MHO subjects was significantly lower than those of the MANW and MAO groups (4 [2, 7] vs 6.5 [3, 13], p = 0.003 and 4 [2, 7] vs 7 [2, 11], p = 0.002, respectively), suggesting the differential capabilities of FRS and maximum TBR value to stratify the CV risk ( Figure 2 ).
When MANW or MHO groups were classified into upper and lower maximum TBR (cut-off criteria: median value in each group), the MANW subjects with upper maximum TBR values showed significant increases in LDL cholesterol and HOMA-IR levels, compared with those with lower maximum TBR values, and showed the trend of increase in the hsCRP level ( Table 3 ). Likewise, the MHO subjects with upper maximum TBR values exhibited significant increases in waist circumference and hsCRP than those with lower maximum TBR values and showed the trend of increase in the HOMA-IR level ( Table 3 ).
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