Metabolic syndrome is a heterogeneous condition characterized

Transcription

1 Elevated Interleukin-18 Levels Are Associated With the Metabolic Syndrome Independent of Obesity and Insulin Resistance Joseph Hung, Brendan M. McQuillan, Caroline M.L. Chapman, Peter L. Thompson, John P. Beilby Objective Activated innate immunity is thought to be involved in the pathogenesis of metabolic syndrome and type 2 diabetes. Interleukin-18 (IL-18) is a pleiotropic proinflammatory cytokine with important regulatory functions in the innate immune response. We sought to determine whether an elevated IL-18 concentration was a risk predictor for metabolic syndrome in a community population independent of obesity and hyperinsulinemia. Methods and Results A representative general population, aged 27 to 77 years, without clinical diabetes was studied for clinical and biochemical risk factors for metabolic syndrome. Serum IL-18 concentration measured in 955 subjects correlated with metabolic syndrome traits including body mass index (BMI), waist circumference, triglyceride, high-density lipoprotein (inversely), and fasting glucose and insulin levels (all P 0.001). Mean IL-18 levels rose progressively with the increasing number of metabolic risk factors (ANOVA P 0.001). After adjusting for age, gender, BMI, and insulin levels, increasing IL-18 tertiles were associated with an odds ratio for metabolic syndrome of 1.0, 1.42, and 2.28, respectively (P trend 0.007). The graded risk relation was even stronger in nonobese subjects and not attenuated when adjusted for C-reactive protein and IL-6 levels. Conclusion Our findings support the hypothesis that activation of IL-18 is involved in the pathogenesis of the metabolic syndrome. (Arterioscler Thromb Vasc Biol. 2005;25: ) Key Words: IL-18 metabolic syndrome obesity insulin resistance inflammatory mediators Metabolic syndrome is a heterogeneous condition characterized by visceral adiposity, dyslipidemia, hypertension, and insulin resistance. 1,2 The metabolic syndrome with its clustering of metabolic and atherosclerotic risk factors is a strong determinant of type 2 diabetes and cardiovascular disease (CVD). 3 5 Obesity and insulin resistance are considered central to the pathophysiology of this metabolic and cardiovascular syndrome. 6,7 Recently, activated innate immunity and chronic inflammation have also been causally implicated and may represent a potential link between metabolic syndrome, diabetes, and atherosclerosis Several cross-sectional studies have shown that acutephase reactants such as C-reactive protein (CRP) and cytokines such as interleukin-6 (IL-6) and tumor necrosis factor- associate with features of the metabolic syndrome such as body mass index (BMI)/waist circumference, measures of insulin resistance/plasma insulin concentration, hypertension, and dyslipidemia However, it is uncertain whether the association of inflammatory markers with metabolic syndrome is independent of measures of obesity and insulin resistance when they are included in a risk prediction model IL-18, a recently described member of the IL-1 cytokine superfamily, is now recognized as an important regulator of innate and acquired immune responses. 20,21 It is a potent proinflammatory cytokine, and a role in plaque destabilization has been suggested. 22 Prospective studies have shown an association of circulating IL-18 levels with cardiovascular death in patients with coronary artery disease and with coronary events in apparently healthy men. 23,24 There is some evidence that IL-18 levels may be linked with metabolic risk factors, although the role of IL-18 in the metabolic syndrome has not been specifically studied. IL-18 levels have been associated with adiposity and insulin resistance in obese premenopausal women. 25,26 IL-18 concentrations are increased by acute hyperglycemia in humans through an oxidative mechanism, 27 and patients with type 2 diabetes have higher IL-18 levels than matched nondiabetic subjects. 28,29 The purpose of this study was to determine whether circulating IL-18 levels were associated with features of the metabolic syndrome in a large cross-sectional communitybased population. In particular, we sought to establish whether circulating IL-18, as well as IL-6 and CRP, were risk Original received December 2, 2004; final version accepted February 13, From the Sir Charles Gairdner Hospital Campus of the Heart Research Institute of Western Australia, and School of Medicine and Pharmacology, University of Western Australia, Perth (J.H., B.M.M., P.L.T.); and Clinical Biochemistry, Western Australian Centre for Pathology and Medical Research (PathCentre), and School of Surgery and Pathology, University of Western Australia, Perth (C.M.L.C., J.P.B.). Correspondence to Joseph Hung, MB, BS, FRACP, Associate Professor of Medicine, School of Medicine and Pharmacology, G Block 4th Floor, Sir Charles Gairdner Hospital, Nedlands, Western Australia jhung@cyllene.uwa.edu.au 2005 American Heart Association, Inc. Arterioscler Thromb Vasc Biol. is available at DOI: /01.ATV

2 Hung et al IL-18 and Metabolic Syndrome 1269 TABLE 1. Clinical and Biochemical Characteristics of the Study Population According to NCEP ATP III Criteria for Metabolic Syndrome* No. of Metabolic Syndrome Risk Factors ANOVA Characteristic n 243 n 306 n 238 n 173 P Value Age, years 45.8 ( ) 54.5 ( ) 56.0 ( ) 57.1 ( ) Male, % 90 (37.0%) 138 (45.1%) 135 (56.7%) 105 (60.7%) BMI, kg/m ( ) 25.1 ( ) 27.3 ( ) 29.9 ( ) Waist circumference, cm 75.7 ( ) 81.6 ( ) 88.4 ( ) 96.4 ( ) Triglyceride, mmol/l 0.9 ( ) 1.0 ( ) 1.4 ( ) 2.1 ( ) HDL cholesterol, mmol/l 1.56 ( ) 1.43 ( ) 1.24 ( ) 1.03 ( ) Low-density lipoprotein cholesterol, mmol/l 3.4 ( ) 3.6 ( ) 3.8 ( ) 3.8 ( ) Systolic blood pressure, mm Hg 111 ( ) 130 ( ) 134 ( ) 139 ( ) Diastolic blood pressure, mm Hg 72 (71 73) 81 (80 82) 83 (81 84) 87 (85 88) Smoking, pack years 7.7 ( ) 10.4 ( ) 14.5 ( ) 18.1 ( ) Glucose, mmol/l 5.2 ( ) 5.5 ( ) 5.7 ( ) 6.2 ( ) Insulin, mu/l 4.2 ( ) 5.1 ( ) 7.0 ( ) 10.7 ( ) hs-crp, mg/l 1.14 ( ) 1.57 ( ) 2.23 ( ) 2.70 ( ) IL-6, g/l 3.08 ( ) 3.47 ( ) 3.93 ( ) 4.33 ( ) IL-18, g/l 255 ( ) 279 ( ) 315 ( ) 356 ( ) Data are mean or geometric mean and 95% CIs. *Criteria for metabolic syndrome according to NCEP ATPIII Report 2001 (see Methods). predictors of the metabolic syndrome independent of obesity and insulin resistance. Methods Study Population The selection criteria and study design of the community-based Carotid Ultrasound Disease Assessment Study (CUDAS) have been detailed previously In brief, this was a random electoral roll sample of 1111 subjects (558 men, 553 women) aged 27 to 77 years from Perth, Western Australia, who were assessed for cardiovascular risk factors and had carotid B-mode ultrasound performed. This present study sample was confined to the 960 subjects without a clinical history of diabetes and who had a fasting serum glucose measured. Subjects also had available measurements of fasting serum insulin (n 959), high-sensitive (hs) CRP (n 944), IL-6 (n 941), and IL-18 (n 955). A self-administered questionnaire was used to record a clinical history of smoking, hypertension, or diabetes. Anthropomorphic measurements and the lower of 2 resting blood pressures were recorded. BMI was calculated as weight (in kilograms)/height (in meters). 2 The study protocol was approved by the institutional ethics committee of the University of Western Australia. Written informed consent was obtained from all study participants. As detailed in the 2001 National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) report, 1 the metabolic syndrome was defined as 3 of the following characteristics: abdominal obesity as measured by waist circumference of 102 cm in men and 88 cm in women; hypertriglyceridemia 150 mg/dl ( 1.69 mmol/ L); low high-density lipoprotein (HDL) cholesterol 40 mg/dl ( 1.0 mmol/l) in men and 50 mg/dl ( 1.3 mmol/l) in women; high blood pressure 130 mm Hg systolic or 85 mm Hg diastolic or current use of antihypertensive drugs; and high fasting glucose 110 mg/dl ( 6.1 mmol/l). Biochemical Analysis A fasting blood sample was obtained from each subject. Serum IL-18 was measured by a commercially available ELISA method (MBL Co. Ltd.) as described previously. 24 The within-run coefficient of variation (CV) was 5.4% at a mean value of 400 g/l (28 samples); between-run CV was 8.2% at 298 g/l (9 samples) and 7.8% at 496 g/l (9 samples). Serum IL-6 was measured using an ELISA (Quantikine HS; R& DSystems), with an assay range of 0.38 to 10.0 ng/l. 32 Serum hs-crp was measured by a microparticle turbidity assay with a range of 0.1 to 21.0 mg/l. 32 Insulin was measured as mu/l on a Tosoh A1A-600 immunoassay analyzer using a 2-site immunoenzymometric assay. The within-run CV was 4.0% at a mean value of 13.8 mu/l (80 samples); between-run CV was 5.6% at 14.3 mu/l (6 samples) and 5.6% at 20.0 mu/l (6 samples). Total cholesterol, HDL cholesterol, and triglyceride levels were determined enzymatically with a Hitachi 747 autoanalyzer. Statistical Analysis Outcome variable of the association analyses was metabolic syndrome as defined by NCEP ATP III criteria. 1 The principal explanatory variables were the inflammatory markers IL-18, IL-6, and hs-crp. Covariates included in regression analyses were age, gender, BMI, fasting insulin, low-density lipoprotein cholesterol, and smoking history (pack years). Serum levels of IL-18, IL-6, and hs-crp were not normally distributed and therefore log (base e) transformed. Geometric means and 95% CIs are given for these variables. Continuous variables were then compared using ANOVA. Categorical variables were compared by 2 test. Statistical significance was taken as P Nonparametric Spearman rank correlations were used to describe the univariate association of inflammatory markers and metabolic risk factors. Forward and backward stepwise multiple logistic regression analysis was used to determine independent predictors of metabolic syndrome and calculate odds ratios and 95% CI for each risk variable. The best fit logistic regression model was found by exhaustive search of all univariate correlates of metabolic syndrome other than those variables that were used to define metabolic syndrome (Table 1). BMI, fasting insulin, IL-18, IL-6, and hs-crp levels were entered as tertile categories in the logistic model. As recommended, subjects with CRP 10 mg/l were excluded from analysis. 33 Subjects were defined as nonobese if they had a BMI 30 kg/m 2. Potential interaction effects on metabolic syndrome between the inflammatory markers and age, sex, or BMI were explored by

3 1270 Arterioscler Thromb Vasc Biol. June 2005 TABLE 2. Spearman Rank Correlation of Metabolic Syndrome Traits and Inflammatory Markers Age BMI Waist TG HDL SBP DBP Glucose Insulin hs-crp IL-6 IL-18 Age * BMI Waist TG HDL * * 0.31 SBP DBP Glucose Insulin hs-crp IL IL Data are Spearman rank correlation coefficients. *P 0.01; P TG indicates triglyceride; SBP, systolic blood pressure; DBP, diastolic blood pressure. including the interaction term, hs-crp, IL-6, or IL-18 by age, sex, or BMI in the multivariate analysis. SPSS version 10.1 for Windows was used in analysis. Results Clinical Characteristics Table 1 shows the clinical and biochemical characteristics of the study population according to the number of ATP III criteria for metabolic syndrome. On the basis of 3 criteria being present, 173 subjects (18% of the population) were defined as having the metabolic syndrome. The population was largely asymptomatic, with a history of coronary heart disease or stroke present in only 7.3% (n 70), use of cholesterol-lowering drugs in 6.1% (n 59), and antihypertensive drugs in 14.9% (n 143). As expected, there was a positive association of age, male gender, BMI, waist circumference, blood pressure, triglyceride, glucose, and insulin levels and an inverse association of HDL level with the number of metabolic risk traits (all ANOVA P 0.001). There was also a positive association of smoking exposure with metabolic syndrome. Geometric mean concentrations of hs-crp, IL-6, and IL-18 increased progressively with the escalating number of metabolic risk factors (all ANOVA P 0.001). Correlation Between Metabolic Syndrome Traits and Inflammatory Markers Table 2 shows Spearman s rank correlation coefficients (r s ) between individual metabolic syndrome traits and fasting insulin, hs-crp, IL-6, and IL-18 concentrations. Predictably, individual components of the metabolic syndrome were associated with each other (all P 0.001). In particular, BMI and waist circumference were highly correlated measures of obesity (r s 0.80). Fasting insulin showed moderate correlations with BMI, waist circumference, triglyceride, HDL (inversely), blood pressure, and glucose levels (all P 0.001) and showed a stronger association than fasting glucose with most of the metabolic traits (Table 2). Levels of IL-18 were correlated with hs-crp (r s 0.18) and IL-6 (r s 0.22; both P 0.001). On the whole, IL-18, IL-6, and hs-crp concentrations showed moderate associations with BMI, waist circumference, triglyceride, HDL (inversely), blood pressure, and insulin levels (Table 2). IL-18 correlated more strongly with waist circumference (r s 0.39) and HDL (r s 0.31) than with other metabolic traits and was weakly associated with age (r s 0.10). There was no significant difference between males and females in the association of IL-18 with metabolic traits. Predictors of Metabolic Syndrome Multivariate analysis established that age, male gender, BMI, and fasting insulin levels were independent predictors of the metabolic syndrome (Table 3). For example, subjects in the top compared with bottom tertiles of BMI and insulin level had an adjusted odds ratio for metabolic syndrome of 6.75 and 7.11, respectively (both P 0.001). TABLE 3. Multivariate Adjusted Odds Ratios for Metabolic Syndrome According to Age, Gender, BMI, and Fasting Insulin Levels for the Whole Population* Variable Odds Ratio 95% CI P Value Age, years Male Gender BMI tertiles, kg/m to Insulin tertiles, mu/l to *Age, gender, BMI, and fasting insulin were selected by multiple logistic regression analysis as the significant multivariate predictors of metabolic syndrome from the list of univariate correlates shown in Table 1, excluding the inflammatory markers.

4 Hung et al IL-18 and Metabolic Syndrome 1271 TABLE 4. Multivariate Adjusted Odds Ratios for Metabolic Syndrome According to Tertile Levels of CRP, IL-6, and IL-18 Age and Sex-Adjusted Age, Sex, BMI, and Insulin Adjusted Age, Sex and Insulin Adjusted in Nonobese Subjects* Variable Odds ratio (95% CI) P Value Odds ratio (95% CI) P Value Odds ratio (95% CI) P Value n 910 n 910 n 765 hs-crp, mg/l ( ) ( ) ( ) ( ) ( ) ( ) n 894 n 894 n 751 IL-6, g/l ( ) ( ) ( ) ( ) ( ) ( ) n 955 n 955 n 793 IL-18, g/l ( ) ( ) ( ) ( ) ( ) ( ) *Nonobese subjects were classified by BMI 30 kg/m 2 ; trend P values. Table 4 shows the multivariate odds ratios for metabolic syndrome associated with tertiles of hs-crp, IL-6, and IL-18. After adjusting for age and gender, the top compared with bottom tertiles of hs-crp and IL-6 were associated with a 2- to 3-fold increased odds ratio for metabolic syndrome (P 0.001). However, there was no longer a significant association after BMI and insulin were added to the model (Table 4). Further exploratory analysis indicated a significant interaction between hs-crp and BMI (P for interaction 0.007) but not between hs-crp and age or sex. When analysis was confined to nonobese subjects, the age, gender, and insulin-adjusted odds ratios for metabolic syndrome were 1.00, 1.55, and 2.32 for increasing tertiles of hs-crp (P trend 0.036) and 1.0, 1.31, and 2.03 for increasing tertiles of IL-6 (P trend 0.08). In comparison, IL-18 remained an independent risk predictor for metabolic syndrome even when adjusted for age, sex, BMI, and insulin level (Table 4). Increasing tertiles of IL-18 were associated with adjusted odds ratios for metabolic syndrome of 1.0, 1.42, and 2.38, respectively (P trend 0.007). A significant interaction between IL-18 and BMI was also indicated on exploratory analysis (P for interaction 0.03), and when the population was stratified by BMI, a 3-fold odds ratio for metabolic syndrome was found for nonobese subjects who had an IL-18 concentration in the top versus bottom tertile (P 0.001; Table 4). The addition of hs-crp and IL-6 in the multivariate model for the whole cohort did not attenuate the relationship between IL-18 levels and metabolic syndrome with odds ratios of 1.0, 1.46, and 2.47 for increasing tertiles of IL-18 (P trend 0.004). Discussion We report for the first time that elevated IL-18 levels were an independent risk predictor for the metabolic syndrome in the absence of diabetes history in a large community population sample. The association was independent of the major determinants of metabolic syndrome, namely obesity and insulin resistance. Further adjustment for hs-crp and IL-6 levels did not attenuate the relationship between IL-18 and metabolic syndrome. Obesity confounded the relationship between hs- CRP and IL-6 levels and metabolic syndrome. However, elevated hs-crp and IL-6 levels were independent risk predictors for the metabolic syndrome in nonobese subjects. Inflammation and activated innate immunity are thought to play an important role in the development of atherosclerosis and diabetes and may represent a unifying link between metabolic syndrome, type 2 diabetes, and CVD Consistent with previous cross-sectional studies, we found that inflammatory markers clustered with metabolic syndrome traits. We also demonstrated that circulating levels of IL-18, IL-6, and hs-crp increased progressively with the escalating number of metabolic traits. The inflammatory markers also showed a positive association with fasting insulin level, a reasonable surrogate measure of insulin resistance. 34,35 Although elevated levels of these inflammatory markers may indicate that chronic inflammation is causally involved in the pathway of metabolic syndrome, they may also simply be markers of associated obesity, insulin resistance, or other metabolic risk traits. In particular, IL-6 and hs-crp are associated with visceral adiposity, 36 because 30% of circulating IL-6 is derived from human adipose tissue, and hepatic synthesis of CRP is largely regulated by IL In the present study, their risk relation to metabolic syndrome was largely attenuated after adjustment for BMI in the multivariate model (Table 4). Others have found that CRP concentrations can be related to insulin resistance independent of obesity, but because insulin resistance is considered a primary defect of metabolic syndrome, we also included insulin level as a covariate in the multivariate model (Tables 3 and 4). Exploratory analysis in this study did suggest an interaction between BMI and CRP on the likelihood of metabolic syndrome. Stratification of the population sample by BMI

5 1272 Arterioscler Thromb Vasc Biol. June 2005 level indicated that nonobese subjects with elevated hs-crp and IL-6 concentrations had an increased likelihood of metabolic syndrome independent of insulin resistance. This suggests that IL-6 induced acute phase responses are likely involved in the pathway of metabolic syndrome and not purely a manifestation of visceral obesity. Our novel finding with IL-18 further enhances the argument that inflammation and activated immunity are involved in the cluster of metabolic and cardiovascular risk factors. Although its regulation is still poorly understood, IL-18 is now recognized as a central regulator of innate and acquired immune responses. 20,21 It appears that IL-18 functions as a pleiotropic proinflammatory cytokine, playing an early role in the inflammatory cascade. IL-18 is able to stimulate the production of tumor necrosis factor- and secondarily IL It may form a link between metabolic syndrome and atherosclerosis because IL-18 is highly expressed in atherosclerotic plaques, and a role in plaque destabilization has been suggested. 22 Prospective studies have shown an association of circulating IL-18 levels with cardiovascular death among patients with coronary artery disease 23 and with coronary events in apparently healthy men. 24 Until now, IL-18 has not been studied specifically in relation to the metabolic syndrome. However, Esposito et al found that IL-18 levels were raised by acute hyperglycemia in humans through an oxidative mechanism. 27 Plasma IL-18 levels have also been found to be increased in patients with diabetes compared with nondiabetic controls. 28,29 In relatively small samples of obese premenopausal women, IL-18 levels were found to positively associate with visceral obesity and insulin resistance. 25,26 In contrast, in the Prospective Epidemiological Study of Myocardial Infarction (PRIME) of apparently healthy European men aged 50 to 69 years, IL-18 levels did not associate with BMI and only weakly with HDL and triglycerides. 24 In our population sample, we found that IL-18 concentrations in both men and women were significantly associated with a range of metabolic risk traits, including BMI, waist circumference, triglycerides, HDL, blood pressure, and fasting insulin levels (Table 2). The strength of our study lies in that a broad cross-section of the general population was represented with males and females across an age range of 27 to 77 years. Despite associating with individual metabolic traits, IL-18 remained an independent predictor of metabolic syndrome, even after adjustment for obesity and insulin resistance as major determinants of metabolic syndrome. We found a consistent graded relationship between IL-18 concentrations and odds ratios for metabolic syndrome that was independent of age, gender, BMI, and insulin levels. Subjects in the top compared with bottom tertile of IL-18 concentrations had a 2-fold increased odds ratio for metabolic syndrome and a 3-fold odds ratio in nonobese subjects (Table 4). Importantly, the risk relationship between IL-18 and metabolic syndrome was not attenuated after adjustment for hs-crp and IL-6 in the model. Several study limitations are acknowledged. Because this is a cross-sectional study, the direction of the association between IL-18, IL-6, and hs-crp levels and the metabolic syndrome cannot be established. It is possible that metabolic risk traits lead to a heightened inflammatory state rather than being a consequence of chronic inflammation. Nevertheless, our results with IL-18 indicate that the elevated IL-18 levels in patients with the metabolic syndrome are not just a marker of visceral obesity and hyperinsulinemia. It is also possible that a few of our subjects had unrecognized diabetes, but the same immune mechanisms are likely to be involved in the metabolic syndrome and diabetes. 9 There is now a consistent body of prospective cohort data showing that a variety of inflammatory markers, including hs-crp and IL-6, predict the development of type 2 diabetes and the incidence of myocardial infarction and cardiovascular death IL-18 concentrations have already been shown to relate to future CVD, 23,24 and further prospective studies relating IL-18 concentrations to incident metabolic syndrome, type 2 diabetes, and CVD would be informative. Nevertheless, our current findings with IL-18 support the hypothesis that this pleiotropic proinflammatory cytokine may well be involved in the pathway of metabolic syndrome and form a link between metabolic risk factors, diabetes, and CVD. It may also represent a novel therapeutic target. Acknowledgments This study was supported by a grant-in-aid from the National Health and Medical Research Council (211980) and HeartSearch, Perth, Western Australia (C.C., J.B.). References 1. Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). J Am Med Assoc. 2001;285: Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C; American Heart Association; National Heart, Lung, and Blood Institute. Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation. 2004;109: Laaksonen DE, Lakka HM, Niskanen LK, Kaplan GA, Salonen JT, Lakka TA. Metabolic syndrome and development of diabetes mellitus: application and validation of recently suggested definitions of the metabolic syndrome in a prospective cohort study. Am J Epidemiol. 2002;156: Lakka H-M, Laaksonen DE, Lakka TA, Niskanen LK, Kumpusalo E, Tuomilehto J, Salonen JT. The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. J Am Med Assoc. 2002; 288: Sattar N, Gaw A, Scherbakova O, Ford I, O Reilly DS, Haffner SM, Isles C, Macfarlane PW, Packard CJ, Cobbe SM, Shepherd J. Metabolic syndrome with and without C-reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study. Circulation. 2003;108: Reaven GM. Role of insulin resistance in human disease. Diabetes. 1988;37: Haffner S, Taegtmeyer H. Epidemic obesity and the metabolic syndrome. Circulation. 2003;108: Pickup JC, Mattock MB, Chusney GD, Burt D. NIDDM as a disease of the innate immune system: association of acute-phase reactants and IL-6 with metabolic syndrome X. Diabetologia. 1997;40: Pickup JC. Inflammation and activated innate immunity in the pathogenesis of type 2 diabetes. Diabetes Care. 2004;27: Biondi-Zoccai GG, Abbate A, Liuzzo G, Biasucci LM. Atherothrombosis, inflammation, and diabetes. J Am Coll Cardiol. 2003;41: Yudkin JS, Stehouwer CDA, Emeis JJ, Coppack SW. C-Reactive protein in healthy subjects: associations with obesity, insulin resistance, and

6 Hung et al IL-18 and Metabolic Syndrome 1273 endothelial dysfunction: A potential role for cytokines originating from adipose tissue? Arterioscler Thromb Vasc Biol. 1999;19: Visser M, Bouter LM, McQuillan GM, Wener MH, Harris TB. Elevated C-reactive protein levels in overweight and obese adults. JAmMed Assoc. 1999;282: Frohlich M, Imhof A, Berg G, Hutchinson WL, Pepys MB, Boeing H, Muche R, Brenner H, Koenig W. Association between C-reactive protein and features of the metabolic syndrome: a population-based study. Diabetes Care. 2000;23: Festa A, D Agostino R Jr, Howard G, Mykkanen L, Tracy RP, Haffner SM. Chronic subclinical inflammation as part of the insulin resistance syndrome: the Insulin Resistance Atherosclerosis Study (IRAS). Circulation. 2000;102: Sakkinen PA, Wahl P, Cushman M, Lewis MR, Tracy RP. Clustering of procoagulation, inflammation, and fibrinolysis variables with metabolic factors in insulin resistance syndrome. Am J Epidemiol. 2000;152: Hak AE, Pols HA, Stehouwer CD, Meijer J, Kiliaan AJ, Hofman A, Breteler MM, Witteman JC. Markers of inflammation and cellular adhesion molecules in relation to insulin resistance in nondiabetic elderly: the Rotterdam study. J Clin Endocrinol Metabol. 2001;86: McLaughlin T, Abbasi F, Lamendola C, Liang L, Reaven G, Schaaf P, Reaven P. Differentiation between obesity and insulin resistance in the association with C-reactive protein. Circulation. 2002;106: Pradhan AD, Cook NR, Buring JE, Manson JE, Ridker PM. C-reactive protein is independently associated with fasting insulin in nondiabetic women. Arterioscler Thromb Vasc Biol. 2003;23: Escobar-Morreale HF, Villuendas G, Botella-Carretero JI, Sancho J, San Millán JL. Obesity, and not insulin resistance, is the major determinant of serum inflammatory cardiovascular risk markers in premenopausal women. Diabetologia. 2003;46: Okamura H, Tsutsui H, Kashiwamura S, Yoshimoto T, Nakanishi K. Interleukin-18: a novel cytokine that augments both acquired and innate immunity. Adv Immunol. 1998;70: Gracie JA, Robertson SE, McInnes IB. Interleukin-18. J Leukoc Biol. 2003;73: Mallat Z, Corbaz A, Scoazec A, Besnard S, Leseche G, Chvatchko Y, Tedgui A. Expression of IL-18 in human atherosclerotic plaques and relation to plaque instability. Circulation. 2001;104: Blankenberg S, Tiret L, Bickel C, Peetz D, Cambien F, Meyer J, Rupprecht HJ; AtheroGene Investigators. Interleukin-18 is a strong predictor of cardiovascular death in stable and unstable angina. Circulation. 2002;106: Blankenberg S, Luc G, Ducimetiere P, Arveiler D, Ferrieres J, Amouyel P, Evans A, Cambien F, Tiret L; PRIME Study Group. IL-18 and the risk of coronary heart disease in European men: the Prospective Epidemiological Study of Myocardial Infarction (PRIME). Circulation. 2003;108: Esposito K, Pontillo A, Ciotola M, Di Palo C, Grella E, Nicoletti G, Giugliano D. Weight loss reduces IL-18 levels in obese women. J Clin Endocrinol Metab. 2002;87: Escobar-Morreale HF, Botella-Carretero JI, Villuendas G, Sancho J, San Millan JL. Serum IL-18 concentrations are increased in the polycystic ovary syndrome: relationship to insulin resistance and to obesity. J Clin Endocrinol Metab. 2004;89: Esposito K, Nappo F, Marfella R, Giugliano G, Giugliano F, Ciotola M, Quagliaro L, Ceriello A, Giugliano D. Inflammatory cytokine concentrations are acutely increased by hyperglycemia in humans: role of oxidative stress. Circulation. 2002;106: Esposito K, Nappo F, Giugliano F, Di Palo C, Ciotola M, Barbieri M, Paolisso G, Giugliano D. Cytokine milieu tends toward inflammation in type 2 diabetes. Diabetes Care. 2003;26: Aso Y, Okumura K, Takebayashi K, Wakabayashi S, Inukai T. Relationships of plasma IL-18 concentrations to hyperhomocysteinemia and carotid intimal-media wall thickness in patients with type 2 diabetes. Diabetes Care. 2003;26: McQuillan BM, Beilby JP, Nidorf M, Thompson PL, Hung J. Hyperhomocysteinemia but not the C677T mutation of methylenetetrahydrofolate reductase is an independent risk determinant of carotid wall thickening. The Perth Carotid Ultrasound Disease Assessment Study (CUDAS). Circulation. 1999;99: Hung J, McQuillan BM, Nidorf M, Thompson PL, Beilby JP. Angiotensin-converting enzyme gene polymorphism and carotid wall thickening in a community population. Arterioscler Thromb Vasc Biol. 1999;19: Chapman CML, Beilby JP, McQuillan BM, Thompson PL, Hung J. Monocyte count, but not C-reactive protein or IL-6, is an independent risk marker for subclinical carotid atherosclerosis. Stroke. 2004;35: Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO III, Criqui M, Fadl YY, Fortmann SP, Hong Y, Myers GL, Rifai NP, Smith SC, Taubert KP, Tracy RP, Vinicor F. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a Statement for Healthcare Professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation. 2003;107: Laakso M. How good a marker is insulin level for insulin resistance? Am J Epidemiol. 1993;137: Howard G, Bergman R, Wagenknecht LE, Haffner SM, Savage PJ, Saad MF, Laws A, D Agostino RB Jr. Ability of alternative indices of insulin sensitivity to predict cardiovascular risk: comparison with the minimal model. Insulin Resistance Study (IRAS) investigators. Ann Epidemiol. 1998;8: Bastard J-P, Jardel C, Delattre J, Hainque B, Bruckert E, Oberlin F. Evidence for a link between adipose tissue IL-6 content and serum C-reactive protein concentrations in obese subjects. Circulation. 1999; 99:2219c 2222c. 37. Mohamed-Ali V, Goodrick S, Rawesh A, Katz DR, Miles JM, Yudkin JS, Klein S. Subcutaneous adipose tissue releases IL-6, but not tumor necrosis factor-alpha in vivo. J Clin Endocrinol Metab. 1997;82: Pradhan AD, Manson JE, Rifai N, Buring JE, Ridker PM. C-reactive protein, IL 6, and risk of developing type 2 diabetes mellitus. JAmMed Assoc. 2001;286: Festa A, D Agostino R Jr, Tracy RP, Haffner SM; Insulin Resistance Atherosclerosis Study. Elevated levels of acute-phase proteins and plasminogen activator inhibitor-1 predict the development of type 2 diabetes: the Insulin Resistance Atherosclerosis Study. Diabetes. 2002;51: Freeman DJ, Norrie J, Caslake MJ, Gaw A, Ford I, Lowe GD, O Reilly DS, Packard CJ, Sattar N. West of Scotland Coronary Prevention S. C-reactive protein is an independent predictor of risk for the development of diabetes in the West of Scotland Coronary Prevention Study. Diabetes. 2002;51: Duncan BB, Schmidt MI, Pankow JS, Ballantyne CM, Couper D, Vigo A, Hoogeveen R, Folsom AR, Heiss G. Atherosclerosis Risk in Communities Study. Low-grade systemic inflammation and the development of type 2 diabetes: the Atherosclerosis Risk in Communities Study. Diabetes. 2003;52: Spranger J, Kroke A, Mohlig M, Hoffmann K, Bergmann MM, Ristow M, Boeing H, Pfeiffer AF. Inflammatory cytokines and the risk to develop type 2 diabetes: results of the prospective population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Diabetes. 2003;52: Ridker PM. Clinical application of C-reactive protein for cardiovascular disease detection and prevention. Circulation. 2003;107: Ridker PM, Buring JE, Cook NR, Rifai N. C-reactive protein, the metabolic syndrome, and risk of incident cardiovascular events: an 8-year follow-up of initially healthy American women. Circulation. 2003;107: Danesh J, Wheeler JG, Hirschfield GM, Eda S, Eiriksdottir G, Rumley A, Lowe GDO, Pepys MB, Gudnason V. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med. 2004;350: