Association between sRAGE, esRAGE levels and vascular inflammation: Analysis with 18F-fluorodeoxyglucose positron emission tomography

Atherosclerosis 220 (2012) 402–406

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Association between sRAGE, esRAGE levels and vascular inflammation: Analysis with 18 F-fluorodeoxyglucose positron emission tomography夽 Sae Jeong Yang a,1 , Sungeun Kim b,1 , Soon Young Hwang c , Tae Nyun Kim d , Hae Yoon Choi a , Hye Jin Yoo a , Ji A Seo a , Sin Gon Kim a , Nan Hee Kim a , Sei Hyun Baik a , Dong Seop Choi a , Kyung Mook Choi a,∗ a

From the Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea Department of Nuclear Medicine, Korea University College of Medicine, Seoul, Republic of Korea c Department of Biostatistics, College of Medicine, Korea University, Seoul, Republic of Korea d Department of Internal Medicine, Cardiovascular and Metabolic Disease Center, Inje University, Busan, Republic of Korea b

a r t i c l e

i n f o

Article history: Received 11 July 2011 Received in revised form 4 October 2011 Accepted 9 November 2011 Available online 16 November 2011 Keywords: Atherosclerosis Inflammation RAGE Positron emission tomography Type 2 diabetes

a b s t r a c t Background: The receptor for advanced glycation end-products (RAGE) and its diverse ligands play a pivotal role in the development of cardiovascular disease. Soluble forms of RAGE (sRAGE), including the splice variant endogenous secretory RAGE (esRAGE), may neutralize AGE-RAGE mediated vascular damage by acting as a decoy. 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a novel imaging technique for detecting vascular inflammation. Methods: We examined vascular inflammation measured using FDG-PET in 41 type 2 diabetes patients and 41 healthy control subjects in the right carotid artery. Vascular 18 F-FDG uptake was measured as the blood-normalized standardized uptake value (SUV), known as the target-to-background ratio (TBR). In addition, their relationship with carotid intima-media thickness (CIMT), estimated GFR (eGFR), and other cardiovascular risk factors was evaluated. Results: Both mean and maximum TBR values were significantly higher in patients with type 2 diabetes compared to healthy subjects. After adjusting for age and gender, sRAGE levels were significantly correlated with both mean and maximum TBR values, but not with CIMT values. Multiple linear regression analysis showed that maximum TBR values were independently associated with sRAGE levels in addition to HbA1c and eGFR. Conclusions: Circulating sRAGE showed significant association with TBR values measured using FDG-PET, which reflect vascular inflammation. © 2011 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Atherosclerosis is now commonly described as an inflammatory disease. Atherosclerotic plaques contain many inflammatory cells such as macrophages, which secrete several cytokines that make weakening of fibrous plaque cap [1]. Vascular inflammation is a major contributing factor to the development of vulnerable plaques that are prone to rupture and plaque rupture results in fatal complications, such as acute myocardial infarction or cerebrovascular infarction. Therefore, effective techniques to detect inflamed vulnerable plaques are urgently demanded. Recently, positron emission tomography (PET) with fluorodeoxyglucose (FDG) has emerged as one of the best imaging

夽 Clinicaltrials. gov.: NCT01021514. ∗ Corresponding author. Tel.: +82 2 2626 3043; fax: +82 2 2626 1096. E-mail address: [email protected] (K.M. Choi). 1 These authors equally contributed to this article. 0021-9150/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.atherosclerosis.2011.11.008

techniques for the detection of inflammatory atherosclerotic plaques. Rudd et al. have shown that atherosclerotic plaque inflammation can be imaged with 18 F-FDG-PET, and that symptomatic, unstable plaques accumulate more 18 F-FDG than asymptomatic lesions [2]. Tahara et al. reported that FDG uptake in carotid atherosclerosis was higher in proportion to number of components of the metabolic syndrome [3] and simvastatin treatment for three months attenuated plaque inflammation visualized using FDG-PET [4]. Recently, we found that patients with impaired glucose tolerance (IGT) or type 2 diabetes showed significantly increased maximum target-to-background ratio (TBR) values measured using FDG-PET, compared to the healthy subjects [5]. Furthermore, we observed the associations between TBR values and circulating biomarkers related with subclinical inflammation including high sensitivity C-reactive protein (hsCRP), adiponectin, resistin, and adipocyte fatty acid binding protein (A-FABP) in various subjects [6–8]. RAGE [receptor for AGEs (advanced glycation end products)] is a multi-ligand member of the immunoglobulin superfamily of

S.J. Yang et al. / Atherosclerosis 220 (2012) 402–406

cell-surface molecules. Ligand engagement of RAGE provokes cellspecific signaling, resulting in intensified generation of reactive oxygen species (ROS), and the stimulation of transcription factor NF-␬B. This induces sustained upregulation of pro-inflammatory cytokines and, adhesion molecules, and leads to endothelial dysfunction [9]. As a result, the ligand-RAGE axis plays a critical role in the development and progression of atherosclerotic cardiovascular diseases [10]. Circulating soluble forms of RAGE (sRAGE), which arise from receptor ectodomain shedding and splice variant [endogenous secretory RAGE (esRAGE)] secretion, might act as an endogenous competitive inhibitor of RAGE, thus playing a crucial role in modulating the ligand-RAGE axis [11]. Several studies suggest that decreased levels of sRAGE and/or esRAGE may be useful as a biomarker of ligand-RAGE pathway hyperactivity and inadequate endogenous protective response not only in diabetes but also in euglycemic vascular disease [12]. Recently, we reported that circulating esRAGE levels were significantly lower in patients with type 2 diabetes compared to ageand gender-matched control subjects and those were negatively correlated with circulating inflammatory markers and arterial stiffness [13]. In this study, we examined the association between serum sRAGE, esRAGE levels and vascular inflammation in the right carotid artery measured using FDG-PET in patients with type 2 diabetes and healthy control subjects. Moreover, we evaluated their relationship with carotid intima-media thickness (CIMT), estimated glomerular filtration rate (eGFR), and other conventional cardiovascular risk factors. 2. Materials and methods 2.1. Study subjects We enrolled 41 patients with type 2 diabetes treated with diet or medical therapy using pre-defined inclusion and exclusion criteria at the Korea University Guro Hospital Diabetes Center, Seoul, Korea. The diagnosis of diabetes was defined according to the criteria of the American Diabetes Association [14]. Their mean hemoglobin A1c (HbA1c) level was 6.9% [6.5–7.4]. These patients were compared with 41 non-diabetic, healthy controls that underwent routine health checkups at Korea University Guro Hospital. Patients with type 1 DM or gestational diabetes were not included. Other exclusion criteria this study adopted were: a history of cardiovascular disease (myocardial infarction, unstable angina, stroke or cardiovascular revascularization), active inflammatory disease, recent active infection, stage 2 hypertension (resting blood pressure, ≥160/100 mm Hg), uncontrolled diabetes mellitus (HbA1c > 9%), systemic disorders such as severe hepatic, renal, and hematologic diseases, or taking drugs known to interfere with vascular inflammation measured by FDG-PET such as statin or insulin medication. All participants provided written informed consent and the Korea University Institutional Review Board, in accordance with the Declaration of Helsinki of the World Medical Association, approved this study protocol. 2.2. Laboratory measurements The body mass indexes (BMI) of study subjects were calculated as weight/height2 (kg/m2 ) and the waist circumferences were measured at the midpoint between the lower border of the rib cage and the iliac crest. Blood samples were drawn after a 12-h overnight fast and were kept at −80 ◦ C for laboratory assay. A glucose oxidase method was used to determine plasma glucose, and an electrochemiluminescence immunoassay (Roche Diagnostics, Indianapolis, USA) was used to measure insulin

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levels. Insulin resistance (IR) was calculated by Homeostasis Model Assessment (HOMA-IR) [15]. HbA1c was measured using high performance liquid chromatography (Bio-Rad Variant II). Serum triglycerides and HDL-cholesterol were analyzed enzymatically using a chemistry analyzer (Hitachi 747, Tokyo, Japan). Estimated glomerular filtration rate (eGFR) was calculated using Modification of Diet in Renal Disease (MDRD) formula: 186 × [serum creatine (mg/dL)]−1.154 × (age)−0.203 (*0.742, if female). Serum sRAGE was measured using a commercially available Quantikine ELISA kits (R&D System, Inc., Minneapolis, MN) with an intra-assay CV of 4.7%, and esRAGE was measured with ELISA kits (B-Bridge International, Sunnyvale, CA) with an intra-assay CV of 4.9%. 2.3. Intima-medial thickness (IMT) and pulse wave velocity (PWV) measurement The IMT of the common carotid artery was assessed by highresolution ultrasound scanning (EnVisor, Philips Medical Systems, Andover, MA, USA) with a 10-MHz transducer. The scanning and reading protocols were identical to those used in the Cardiovascular Health Study; longitudinal B-mode images at the diastolic phase of the cardiac cycle were recorded by a single trained technician who was blinded to the subject’s background. Measurements of CIMT were made by the same technician using intimascope software (Media Cross Co., Tokyo, Japan) at three levels of the lateral and medial walls, 1–3 cm proximal to the carotid bifurcation. The average IMT was the mean value of 99 computer-based points in the region, and the maximal IMT was the IMT value at the maximal point of the region. Extremity blood pressure and mean brachial–ankle pulse wave velocity (baPWV) were measured using an oscillometric method (VP-1000; Colin, Komaki, Japan). The reproducibility of this method was reported in our previous study [16]. 2.4. [18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) FDG-PET/CT was performed using the Gemini TF 16 Slice PET/CT scanner (Philips Medical Systems, Cleveland, USA), with an 18 cm field of view. The TF scanner is a new high-performance, timeof-flight (TOF) capable, fully 3-dimensional (3D) PET scanner using lutetium-yttrium oxyorthosilicate (LYSO) crystals. After the patients had fasted 12 hours, 18 F-FDG (370–550 MBq) was injected intravenously, and patients rested in a quiet room for 60 min. Whole body PET images (below cerebellum to inguinal) were acquired for 10 min (1 min per bed). PET image analysis was performed on a dedicated workstation (Extended Brilliance Workspace 3.5 with PET/CT viewer for automated image registration, Philips). 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. Arterial FDG uptake was quantified by drawing a region of interest (ROI) around each artery on every slice of the coregistered transaxial PET/CT images. The ROI was fitted to the artery wall on each axial slice, and coronal and sagittal views were used to ensure that the FDG uptake was from the artery. 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). On each image slice, the mean and maximum SUVs of the ROI were measured as the mean and maximum pixel activity. The SUVs for all 10 slices within the right carotid artery were averaged to calculate the mean and maximum SUVs for each subject. Next, the arterial SUV value was divided by the blood-pool SUV value measured from the jugular vein (standardized circular ROIs; the right carotid artery, area = 77.9 ± 3.42 mm2 , 9 pixels and the right jugular vein, area = 95.0 ± 12.7 mm2 , 9 pixels)

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Table 1 Clinical and laboratory characteristics of the study subjects.

Age (years) Gender (M/F)† Smoker (n/%) Weight (kg) Body mass index (kg/m2 ) Waist circumference (cm) Waist-to-hip ratio Systolic blood pressure (mmHg)‡ Diastolic blood pressure (mmHg)‡ Total cholesterol (mmol/l) HDL-cholesterol (mmol/l)‡ LDL-cholesterol (mmol/l)‡ Triglyceride (mmol/l)‡ FBG (mmol/l) Insulin (uU/l)‡ HbA1c (%)‡ HOMA-IR‡ sRAGE (pg/ml) esRAGE (pg/ml)‡ BUN (mg/dL) Creatinine (mg/dL)‡ eGFR (ml/min/1.73 m2 )‡ Mean baPWV‡ Mean CIMT‡ Maximum CIMT‡ Mean TBR‡ Maximum TBR‡

Healthy Control

T2DM

P

53.3 ± 9.2 20/21 8(19.5%) 61.7 ± 12.3 22.8 ± 3.5 80.4 ± 8.5 0.86 ± 0.05 124.0(117.0–128.0) 81.0(73.0–85.0) 3.9 ± 0.9 0.5(0.4–0.6) 2.2(1.9–2.6) 2.4(1.9–2.7) 4.3 ± 0.9 1.7(0.7–2.7) 5.5(5.3–5.7) 0.27(0.12–0.48) 561.9 ± 194.7 234.5(173.9–322.0) 14.2 ± 3.7 0.6(0.4–0.7) 136.6(113.1–196.9) 1299.5(1203.5–1413.0) 0.62(0.57–0.76) 0.74(0.68–0.92) 1.08(1.04–1.12) 1.15(1.09–1.28)

56.8 ± 9.2 20/21 9(22.0%) 63.5 ± 11.9 24.4 ± 3.4 83.7 ± 7.8 0.90 ± 0.05 124.5(115.0–139.0) 79.0(71.0–83.5) 4.0 ± 1.0 0.5(0.4–0.7) 2.1(1.6–2.5) 2.3(1.9–3.0) 6.5 ± 2.0 5.4(3.5–10.3) 6.9(6.5–7.4) 1.50(0.89–2.71) 475.5 ± 217.7 195.3(146.5–331.1) 14.6 ± 4.0 0.7(0.6–0.9) 115.5(91.6–129.2) 1452.3(1272.5–1717.0) 0.70(0.62–0.77) 0.86(0.78–0.95) 1.76(1.60–1.99) 2.23(2.14–2.38)

0.090 1.000 1.000 0.501 0.041 0.070 0.003 0.325 0.963 0.648 0.856 0.880 0.959 <0.001 <0.001 <0.001 <0.001 0.063 0.069 0.638 0.061 0.010 0.004 0.099 0.017 <0.001 <0.001

FBG, fasting blood glucose; HOMA-IR, homeostasis model assessment insulin resistance; sRAGE, soluble receptor for advanced glycation end products; esRAGE, endogenous secretory RAGE; BUN, blood urea nitrogen; eGFR, estimated glomerular filtration rate; baPWV, brachial-ankle pulse wave velocity; CIMT, carotid intima-media thickness; TBR, target-to-background ratios. Data are presented as mean ± SD or median (inter-quartile range). † Pearson’s chi-squared test for categorical variables. ‡ P values represent differences between groups as determined by the independent two-sample t-test or Mann–Whitney test for continuous variables.

for normalization; afterward, mean and maximum values of targetto-background ratio (TBR) were calculated for each patient [17]. To determine the variability of the mean and maximum TBR measurements, images from 20 subjects were analyzed twice, several weeks apart, by two readers. The intra- and inter-observer correlation coefficient values of mean and maximum TBR measurements were greater than 0.8. 2.5. Statistical analysis Data are expressed as mean ± SD or median (inter-quartile range). Differences between groups were tested using the independent two-sample t-test, Mann–Whitney U test, or 2 test. Spearman’s partial correlation tests were performed to determine the relations between serum sRAGE and esRAGE levels, CIMT values, average or maximum SUV/TBR levels, and other cardiovascular risk variables. Multiple regression analysis was conducted using maximum TBR as a dependent variable. Age, gender, weight, waist-to-hip ratio (WHR), systolic blood pressure, total cholesterol, HDL-cholesterol, triglyceride, HbA1c, eGFR, smoking status and sRAGE levels were adopted as independent variables and significant independent variables were chosen using the backward variable selection method. Data were analyzed using SPSS for Windows (version 12.0; SPSS Inc., Chicago, IL, USA) and SAS for windows (version 9.2, SAS Institute Inc., Cary, NC, USA). A P value <0.05 was accepted to indicate statistical significance.

had lower eGFR levels than the control group. Importantly, mean and maximum TBR values were significantly higher in patients with type 2 diabetes (mean TBR 1.08 [1.04–1.12] vs. 1.76 [1.60–1.99]; maximum TBR 1.15 [1.09–1.28] vs. 2.23 [2.14–2.38], all P < 0.001) compared to healthy subjects. Circulating sRAGE and esRAGE concentrations tended to be lower in the diabetic group, but did not reach statistical significant level in the present study subjects (P = 0.063, P = 0.069, respectively). In an age- and gender-adjusted Spearman’s simple correlation analysis, sRAGE levels were negatively correlated with BMI, waist circumference, WHR, systolic blood pressure (SBP), diastolic blood pressure (DBP), LDL-cholesterol, fasting blood glucose, insulin, HbA1c, and HOMA-IR. Moreover, sRAGE levels were

3. Results Table 1 shows the clinical and biochemical characteristics of the study subjects. Although there were no significant differences in age and gender between study groups, the diabetic group had significantly higher BMI, WHR, fasting blood glucose, insulin, HbA1c, HOMA-IR, mean baPWV, and maximum CIMT values but

Fig. 1. Spearman’s simple correlation between maximum TBR values and sRAGE concentrations in total subjects (r = −0.268, P = 0.015).

S.J. Yang et al. / Atherosclerosis 220 (2012) 402–406 Table 2 Age- and gender-adjusted Spearman’s simple correlation analysis of other variables associated with sRAGE and esRAGE levels. sRAGE

Body mass index Waist circumference Waist-to-hip ratio Systolic blood pressure Diastolic blood pressure Total cholesterol HDL-cholesterol LDL-cholesterol Triglyceride FBG Insulin HbA1c HOMA-IR eGFR sRAGE esRAGE Mean baPWV Mean CIMT Maximum CIMT Mean TBR Maximum TBR

esRAGE

r

P

r

P

−0.414 −0.417 −0.301 −0.359 −0.244 −0.199 0.126 −0.231 0.012 −0.271 −0.294 −0.234 −0.323 −0.115

<0.001 <0.001 0.007 0.001 0.029 0.077 0.266 0.040 0.918 0.015 0.009 0.039 0.003 0.310

−0.365 −0.356 −0.306 −0.313 −0.224 −0.272 0.082 −0.305 −0.052 −0.194 −0.204 −0.182 −0.229 −0.095 0.875

0.001 0.001 0.006 0.005 0.046 0.015 0.470 0.006 0.644 0.084 0.073 0.111 0.043 0.404 <0.001

0.875 −0.205 −0.070 −0.109 −0.246 −0.241

<0.001 0.080 0.560 0.364 0.028 0.031

−0.165 −0.005 −0.042 −0.217 −0.241

0.159 0.968 0.727 0.053 0.031

FBG, fasting blood glucose; HOMA-IR, homeostasis model assessment insulin resistance; BUN, blood urea nitrogen; eGFR, estimated glomerular filtration rate; baPWV, brachial-ankle pulse wave velocity; CIMT, carotid intima-media thickness; TBR, target-to-background ratios; sRAGE, soluble receptor for advanced glycation end products; esRAGE, endogenous secretory RAGE.

Table 3 Multiple linear stepwise regression analysis with the maximum TBR values as a dependent variable. Unstandardized

HbA1c eGFR sRAGE

Standarized

Coefficients

S.E.

ˇ

0.288 −0.002 −0.001

0.053 0.001 0.000

0.509 −0.195 −0.175

P

<0.001 0.035 0.062

eGFR, estimated glomerular filtration rate; sRAGE, soluble receptor for advanced glycation end products; S.E, standardized error R2 = 0.392.

significantly correlated with both mean and maximum TBR values (Table 2, Fig. 1). On the other hand, esRAGE levels positively correlated with sRAGE levels, but negatively correlated with BMI, waist circumference, WHR, SBP, DBP, total cholesterol, LDL-cholesterol, HOMA-IR, and maximum TBR. However, there were no significant correlations between sRAGE/esRAGE levels and CIMT values in the study subjects (Table 2). Multiple regression analysis using maximum TBR as a dependent variable has shown in Table 3. The maximum TBR values was significantly positively associated with HbA1c (P < 0.001), but negatively associated with eGFR (P = 0.035) and sRAGE levels (P = 0.062) after adjustment of other potential confounding factors (R2 = 0.392). 4. Discussion To the best of our knowledge, this study provides the first evidence showing the negative correlation of circulating sRAGE levels with vascular inflammation measured using FDG-PET. Moreover, there was an independent association between maximum TBR values and sRAGE levels as well as HbA1c and eGFR values after adjusting for other cardiovascular risk factors in multiple regression analysis. The ligand-RAGE axis has been known to be involved in the pathogenesis of a wide range of diseases including vascular

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complications of diabetes mellitus, atherosclerosis, aging, and immune/inflammatory conditions [11]. Circulating soluble RAGE (sRAGE) isoforms levels may inversely reflect RAGE activity, thus providing a useful biomarker of RAGE-mediated pathogenesis [18]. These isoforms of sRAGE consist of the products from ectodomain shedding of the membrane-associated receptor and alternative splicing of RAGE pre-mRNA transcripts known as endogenous secretory RAGE (esRAGE) [11]. The administration of recombinant sRAGE to apolipoprotein E-null mice with or without diabetes can suppress atherosclerosis and prevents progression of vascular lesions [19]. Falcone et al. reported that low levels of sRAGE in plasma are independently associated with the presence of CAD in non-diabetic men. Moreover, an inverse graded association was observed between sRAGE quartiles and coronary artery calcium scores in the population-based Dallas Heart Study [20]. In addition, plasma sRAGE levels are significantly lower in non-diabetic patients with peripheral artery disease (PAD) than age-matched control subjects [21]. High circulating AGEs and low esRAGE levels are associated with an increased prevalence of in-stent restenosis in patients with type 2 diabetes [22]. Furthermore, continuous low levels of circulating esRAGE and sRAGE were determinants of mean IMT progression, independent of conventional risk factors in Japanese patients with type 1 diabetes [23]. The present study firstly showed that sRAGE levels were significantly associated with mean and maximum TBR values measured using FDG-PET. However, there was no significant relationship between sRAGE levels and CIMT values in this study subjects. Although CIMT is known as a surrogate marker of general atherosclerotic burden, it did not provide information about plaque composition or inflammatory state. Silvera et al. reported that the TBR values was higher in the lipid-necrotic core group than collagen or calcium group in multimodality imaging of atherosclerotic plaque activity and composition using FDG-PET and MRI [24]. RAGE is expressed in all cell types relevant to the development of atherosclerotic plaque, including monocytes/macrophages, and activated inflammatory cells may release RAGE-ligands such as S100 proteins and amphoterin. Ogawa et al. reported that macrophages are responsible for the accumulation of FDG in atherosclerotic lesions by using FDG-PET in a rabbit model of atherosclerosis [25]. Furthermore, Tawakol et al. found that there was a significant correlation between the PET signal from human carotid plaques and macrophage staining from corresponding histological sections [26]. Therefore, FDG-PET has been proposed as a new imaging technique for non-invasive identification and quantification of inflammation of atherosclerotic plaques, especially macrophage-related vascular inflammation. This study showed significant relationship between circulating sRAGE levels, cardiovascular risk factors, and TBR values measured using FDG-PET. These results suggest that sRAGE may be an useful circulating biomarker for cardiovascular risk stratification and an important target of therapeutic interventions [11]. In this study, sRAGE levels were significantly correlated with waist circumference, SBP, fasting glucose, and insulin resistance. These results are compatible with several previous studies that report a relationship between sRAGE and/or esRAGE and components of the metabolic syndrome. Basta et al. reported lower plasma sRAGE in patients with type 2 diabetes compared to non-diabetic subjects [27]. Moreover, they found a significant inverse correlation between sRAGE levels and HbA1c, insulin resistance, S100A12, and C-reactive protein (CRP). In addition, significant lower esRAGE levels are also reported in patients with type 2 diabetes and in those with impaired glucose tolerance compared to subjects with normal glucose tolerance [28]. Furthermore, both sRAGE and esRAGE levels are inversely correlated with body mass index, systolic blood pressure, waist-to-hip ratio, triglycerides, and insulin resistance [29]. We observed similar results in our study subjects, although

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sRAGE levels showed a closer relationship with components of metabolic syndrome than esRAGE levels in our study’s subjects. Studies comparing sRAGE and esRAGE showed that esRAGE levels are two to five folds lower than sRAGE levels, and esRAGE only explains approximately one-third of the variation in sRAGE levels, suggesting isoform-specific kinetics [18], although the two isoforms are significantly inter-correlated, as shown in our study subjects (r = 0.873, P < 0.001). However, some studies have reported increased, rather than decreased levels, of total sRAGE in patients with type 2 diabetes. In one of these studies, circulating AGEs and sRAGE levels are associated with the severity of nephropathy in patients with type 2 diabetes [30]. However, the present study showed lower levels of sRAGE and esRAGE in patients with type 2 diabetes compare to control group, although their difference did not reach a significant level (P = 0.063, P = 0.069, respectively). Moreover, even after adjusting renal function using eGFR, independent association between sRAGE levels and TBR values was persisted. Because of the limitations of cross-sectional design in the present study, no causal relationship could be defined. However, the present study had the advantage of prospective recruitment of subjects with pre-defined inclusion and exclusion criteria, unlike several previous retrospective studies that enrolled patients who had taken FDG-PET for cancer follow-up care. In conclusion, TBR values measured using FDG-PET are significantly increased in patients with type 2 diabetes compared to age- and gender-matched subjects. Furthermore, maximum TBR values are independently associated with circulating sRAGE levels even after adjusting for other cardiovascular risk factors. The role of sRAGE in the pathobiology of atherosclerosis and its potential prognostic and therapeutic implications warrant further investigation. Competing interest None. Funding None. Acknowledgements Dr. K. M. Choi was supported by the Mid-Career Researcher Program through an NRF grant funded by the Ministry of Education, Science, and Technology, Republic of Korea (No. R01-2007000–20546-0). Dr. K. M. Choi and Dr. S. H. Baik were supported by the Brain Korea 21 Project of the Ministry of Education and Human Resources Development, Republic of Korea (A102065). References [1] Kume N. Molecular mechanisms of coronary atherosclerotic plaque formation and rupture. Nippon Rinsho 2010;68:637–41. [2] Rudd JH, Warburton EA, Fryer TD, et al. Imaging atherosclerotic plaque inflammation with [18 F]-fluorodeoxyglucose positron emission tomography. Circulation 2002;105:2708–11. [3] Tahara N, Kai H, Yamagishi S, et al. Vascular inflammation evaluated by [18 F]-fluorodeoxyglucose positron emission tomography is associated with the metabolic syndrome. J Am Coll Cardiol 2007;49:1533–9. [4] Tahara N, Kai H, Ishibashi M, et al. Simvastatin attenuates plaque inflammation: evaluation by fluorodeoxyglucose positron emission tomography. J Am Coll Cardiol 2006;48:1825–31. [5] Kim TN, Kim S, Yang SJ, et al. Vascular inflammation in patients with impaired glucose tolerance and type 2 diabetes: analysis with 18F-fluorodeoxyglucose positron emission tomography. Circ Cardiovasc Imaging 2010;3:142–8.

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