Subclinical vascular inflammation in subjects with normal weight obesity and its association with body Fat: an ¹⁸ F-FDG-PET/CT study

This cross-sectional study was designed to evaluate the effect of BF on vascular inflammation of the carotid arteries in subjects with a normal BMI. Asymptomatic subjects self-referred for ¹⁸ F-FDG-PET/CT examination from March 2010 to February 2013 in a health checkup program at the Health Promotion Center, Gangnam Severance Hospital, were consecutively registered (N = 1003; Men: n = 602; Women: n = 401). All subjects underwent a medical examination, including clinical history, physical examination, blood analysis, abdominal ultrasound, and ¹⁸ F-FDG-PET/CT.

We divided the whole population by gender-specific BF% tertiles and defined NWO subjects as those with a normal BMI (18.5–24.9 kg/m²) and the highest tertile of BF% (Men, ≥23.5%, Women, ≥29.2%) in line with a previous study¹⁵, thus yielding 89 NWO subjects (Men: N = 38; Women: N = 51). Subjects who were previously diagnosed with diabetes mellitus and/or taking anti-diabetic medication were excluded. Moreover, subjects with previously diagnosed malignancy within 5 years of PET/CT examination, chronic inflammatory disease, or other previous disease of the carotid artery were excluded. Finally, 82 NWO subjects were included in the present study. Moreover, 82 control normal weight lean (NWL) subjects (Men, <23.5%; Women, <29.2%)—i.e., normal BMI subjects who were in the lower two tertiles for gender-specific BF%—were randomly selected from sex-matched subjects using random numbers uniformly distributed between 0 and 1 (Figure 1). In addition, we constructed another database comprising 63 subjects each in the NWL and NWO groups who were matched for sex and BMI values using greedy matching techniques. The exclusion criteria of the NWL subjects were identical to those for the NWO subjects. The protocol of this study was approved by the institutional review board of Gangnam Severance Hospital, and all subjects provided written informed consent for the ¹⁸ F-FDG-PET/CT examination.

The current and past medical history of disease, medication, presence of CVD risk factors (smoking, alcohol, and family history of premature CVD), and other information on medico-social history were self-reported via a routine questionnaire before the health checkup.

All subjects were requested to fast for more than 8 hours before all biochemical and anthropometric examinations. Body weight was measured by electronic load to the nearest 0.01 kg, with the parents wearing a light gown without shoes for the health examination. Height was measured to the nearest 0.1 cm. BMI was calculated as the weight in kilograms divided by the square of height in meters (kg/m²). The BF%, total body fat, visceral fat, subcutaneous fat, and muscle mass were measured using the bioelectrical impedance (BI) body composition analyzer X-scan plusII (Jawon Medical, Seoul, Korea) [27]. In brief, the tetra-polar electrode method with 8 touch electrodes placed on both hands and feet facilitated the estimation of the BI value in the abdominal area, which was evaluated by the current intercrossing between each hand and foot. By using the waist-to-hip ratio, body weight, height, age, sex, and the BI value of the abdominal area, the Jawon Medical Company created a formula specific for Korean individuals to calculate the visceral fat amount. The subcutaneous fat amount was estimated by excluding the visceral fat from the total fat amount [28, 29]. Systolic and diastolic blood pressure was measured using BP203RV II (Colin Corp., Aichi, Japan) after resting for more than 15 min in the sitting position. The presence of fatty liver was assessed using a Philips IU-22 Ultrasound system (Philips Healthcare, Andover, MA) by an expert radiologist.

Glucose was measured by the glucose oxidase method using a 747 Automatic Analyzer (Hitachi, Tokyo, Japan). Glycated hemoglobin A1c (HbA1c) level was measured by high-performance liquid chromatography (Cobas Integra 800, Roche, Mannheim, Germany). The levels of total cholesterol, high-density lipoprotein cholesterol (HDL-cholesterol), triglyceride, C-reactive protein (CRP), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were measured by an enzymatic colorimetric method (Daiichi, Hitachi). Low-density lipoprotein cholesterol (LDL-cholesterol) content was calculated according to the Friedewald formula.

All patients fasted at least 8 h before the injection of ¹⁸ F-FDG, after ensuring that serum glucose levels at this time point did not exceed 150 mg/dL. The injection dose of ¹⁸ F-FDG was 5.18 MBq/kg (0.14 mCi/kg). ¹⁸ F-FDG-PET images were obtained using a standard PET/CT scanner (Biograph TruePoint 40, Siemens Healthcare, Erlangen, Germany) and all data were acquired in the 3D mode with a 1.5-min scan time per bed. Tomographic PET images were reconstructed by using an iterative method involving ordered subset expectation maximization, under the condition of 2 iterations and 21 subsets. The matrix of reconstructed PET images using this method was 128 × 128, and the slice thickness was 5 mm. Low-dose CT scans for attenuation correction and identification of anatomical landmarks were obtained immediately before the PET scan.

Image analysis was conducted using a dedicated PET/CT workstation (Syngo 2009A, Siemens Healthcare) according to previous reports [20, 24‐26]. In detail, for exact measurement of the carotid artery and jugular vein, the overall diameter, course, and variation of cervical vasculature were first reviewed using CT images, after which the metabolic activity of the artery and vein was estimated by using PET/CT fusion images prior to region of interest (ROI) measurements. A circular ROI was used in most slices of the carotid arteries, whereas an oval or circular ROI was used for the jugular vein depending on its contour. Each ROI was intended to include the entire wall of the artery and vein. The measurement of the uptake value (SUV) was started from the highest level of the common carotid artery before bifurcation to the external and internal carotid branches (mostly around the level of the hyoid bone), and 10 ROIs were consecutively measured from the inferior level up to the origin of the carotid artery from the aortic arch. Eight ROIs were used to measure the jugular vein SUV, and their locations were similar to those of the carotid artery. The maximal (SUVmax) and mean SUV (SUVmean) were measured in the carotid artery and the jugular vein, respectively, after which the target-to-background ratio (TBR) was calculated using the following equations: Mean TBR (TBRmean) = (mean SUV of carotid artery)/(mean SUV of jugular vein); Maximum TBR (TBRmax) = (maximum SUV of carotid artery)/(mean SUV of jugular vein) [20, 24‐26].

Anthropometric, clinical, and biochemical data are presented as the mean ± standard deviation (SD) for continuous variables and absolute numbers (percentage) for categorical variables. An independent two-sample t-test or paired sample t-test was used to evaluate the differences in the continuous variables between NWL and NWO subjects after testing each variable for normality with the Shapiro-Wilk test. The χ² test or Fisher’s exact test was used to compare categorical variables between the NWL and NWO groups, as appropriate. The degree of a relationship between putative CVD risk factors and TBRmean or TBRmax was expressed by Pearson’s correlation coefficient (r). Multiple stepwise linear regression analysis was used to determine the independent predictors of TBRmean and TBRmax. Logistic regression models were analyzed to evaluate the odds ratio (OR) for TBRmax elevation in the NWO group compared to the NWL group. All statistical analyses were performed using adequate software (SPSS version 20.0, Chicago, IL). A p value of <0.05 was considered to be statistically significant.

The mean age of the subjects was 54 years, and 18% of the subjects had hypertension. The NWO subjects had a higher BMI, larger waist-to-hip ratio, and greater amount of visceral and subcutaneous fat. There was no difference in total muscle mass between the groups. NWO subjects had significantly higher systolic and diastolic BP than NWL subjects. Although there was no difference in HbA1c levels, the fasting plasma glucose level was significantly higher in the NWO group. In addition, NWO subjects had higher serum triglyceride and lower HDL-cholesterol levels. No differences in current anti-hypertensive drug, statin, and anti-platelet use were noted between the groups. Detailed comparisons of each parameter are summarized in Table 1. Moreover, we analyzed these clinical and biochemical parameters after dividing the study population based on gender. The difference in the metabolic profile tended to be significant between the female subjects in the NWO and NWL groups, whereas certain parameters such as blood pressure and CRP were not significantly different in the male subjects between the NWO and NWL groups (Table 2).

Compared to the NWL group, the NWO group had a significantly higher SUVmean and SUVmax at the carotid artery (SUVmean: 1.53 ± 0.31 versus 1.64 ± 0.31, p = 0.024; SUVmean: 1.75 ± 0.36 versus 1.90 ± 0.38, p = 0.009) (Table 3, Figures 2A and B, Figure 3). However, there was no difference in the SUVmean at the jugular vein between the two groups. TBRmean and TBRmax—the corrected values of carotid SUVmean and SUVmax divided by the SUVmean of the jugular vein in each individual, respectively—were also higher in the NWO population (TBRmean: 1.33 ± 0.16 versus 1.45 ± 0.19, p < 0.001; TBRmax: 1.52 ± 0.23 versus 1.67 ± 0.25, p < 0.001) (Table 3, Figures 2C and D). As the degree of vascular inflammation may be affected by the coexistence of hypertension or statin use, we also analyzed the degree of carotid inflammation after excluding subjects with these factors. However, the difference was consistently significant even in patients without anti-hypertensive or statin use (TBRmean: 1.33 ± 0.16 versus 1.44 ± 0.21, p < 0.001; TBRmax: 1.52 ± 0.24 versus 1.67 ± 0.03, p < 0.001) (NWL: n = 67; NWO: n = 64). We also analyzed the difference in vascular inflammation between NWL and NWO subjects from the total population who were equally matched by sex and BMI. We observed a significant difference in the degree of carotid inflammation after matching for BMI (TBRmean: 1.24 ± 0.25 versus 1.44 ± 0.21, p < 0.001; TBRmax: 1.42 ± 0.29 versus 1.68 ± 0.32, p < 0.001) (n = 63 in each group). Moreover, we analyzed the vascular inflammation according to sex. We observed a significant difference in vascular inflammation in male subjects between the NWL and NWO groups (TBRmean: 1.33 ± 0.15 versus 1.47 ± 0.16, p = 0.001; TBRmax: 1.50 ± 0.18 versus 1.71 ± 0.22, p < 0.001) and in female subjects between the NWL and NWO groups (TBRmean: 1.33 ± 0.20 versus 1.43 ± 0.22, p = 0.015; TBRmax: 1.54 ± 0.26 versus 1.65 ± 0.27, p = 0.038) (Table 4).

The correlation between vascular inflammation and various CVD risk factors was analyzed. Age, BMI, and the fasting plasma glucose level were significantly associated with both TBRmean and TBRmax (Table 5 and Figures 4A-C, 4E-G). We also analyzed the correlation between vascular inflammation and fat mass. Total, visceral, and subcutaneous fat mass were all significantly correlated with the degree of vascular inflammation; this degree of correlation was better than that observed for the traditional CVD risk factors of age, BMI, and fasting plasma glucose level (Table 5 and Figure 4D and H). However, none of the other anthropometric or biochemical characteristics correlated with TBRmean or TBRmax.

Univariate linear regression analysis followed by multivariate linear regression analysis was performed to determine the independent predictors of vascular inflammation. For multivariate linear regression analysis, only the total fat among other fat parameters was tested together with other significant parameters because of the multicollinearity. Among the significant parameters identified by univariate linear regression analysis (age, BMI, fasting plasma glucose level, and total fat amount), the total body fat amount was the only significant independent predictor of both TBRmean and TBRmax (TBRmean: regression coefficient = 0.020, p = 0.008; TBRmax: regression coefficient = 0.028, p = 0.005) (Table 6).

To assess the risk of subclinical atherosclerosis in the subjects between the NWO and NWL groups, we performed multiple logistic regression analysis using a TBRmax value equal to or greater than the highest quartile as the endpoint. After adjusting for basic clinical factors such as age, fasting plasma glucose level, systolic BP, HDL-cholesterol level, LDL-cholesterol level, and triglyceride level, NWO subjects were 3.1-fold more likely to display subclinical vascular inflammation (OR = 3.071, 95% confidence interval (CI) = 1.292–7.297, p = 0.011). Moreover, the NWO subjects were 2.9-fold more likely to exhibit subclinical vascular inflammation, even after adjusting for age, fasting plasma glucose level, systolic BP, HDL-cholesterol level, LDL-cholesterol level, triglyceride level, and all medication history concerning CVD (OR = 2.887, 95% CI = 1.206–6.914, p = 0.017); no other variables significantly contributed to the vascular inflammation, except for NWO in these models (Table 7).