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(Circulation. 2004;110:803-809.)
© 2004 American Heart Association, Inc.
Original Articles |
From the Cardiovascular Division and Center for Experimental Therapeutics, Department of Medicine, University of Pennsylvania School of Medicine (M.P.R., M.L.W., N.M., D.J.R.), and the Department of Epidemiology, Merck Research Laboratories (T.R., C.G.), Philadelphia, Pa.
Correspondence to Muredach Reilly, Cardiovascular Division, University of Pennsylvania Medical Center, 909 BRB 2/3, 421 Curie Blvd, Philadelphia, PA 19104-6160. E-mail muredach{at}spirit.gcrc.upenn.edu
Received December 23, 2003; revision received April 1, 2004; accepted April 4, 2004.
| Abstract |
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Methods and Results We examined the association of insulin resistance and MetSyn with coronary artery calcification (CAC) in 840 asymptomatic nondiabetic subjects. Both NCEP and World Health Organizationdefined MetSyn were associated (ordinal regression odds ratio [OR] and 95% confidence intervals for NCEP-defined MetSyn) with CAC after controlling for age, non-MetSyn risk factors, and plasma CRP levels (OR, 1.93 [1.43 to 2.60], P<0.001) and after further controlling for homeostasis model assessment index (HOMA) (OR, 1.56 [1.14 to 2.15], P=0.006). Conversely, HOMA was significantly associated with CAC after adjusting for age, non-MetSyn risk factors, and CRP levels (OR, 1.62 [1.31 to 2.01], P<0.001) and after further adjusting for NCEP-defined MetSyn (OR, 1.45 [1.16 to 1.82], P=0.007). Addition of HOMA to the NCEP MetSyn significantly improved the association with CAC, but addition of CRP data to MetSyn or HOMA did not.
Conclusions Both MetSyn and HOMA index were associated with coronary atherosclerosis independent of established risk factors, including CRP. These findings support the use of biomarkers of insulin resistance in addition to NCEP MetSyn criteria in assessing cardiovascular disease risk.
Key Words: metabolism insulin atherosclerosis
| Introduction |
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The National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) expert panel10 and World Health Organization (WHO)11 have proposed distinct definitions of MetSyn to aid in clinical practice and research. The NCEP definition, unlike the WHO, does not include measurement of insulin and therefore may fail to detect insulin resistance.5,8,12,13 Furthermore, the association of MetSyn with incident diabetes and CVD has varied substantially when the two definitions have been applied in a single study.5,79 Additional definitions of MetSyn have been proposed,14,15 underscoring the need for unified criteria for use in clinical practice.
Chronic subclinical inflammation is thought to be part of the MetSyn.16 Inflammatory markers such as C-reactive protein (CRP) may provide independent information regarding diabetes and CVD risk beyond NCEP MetSyn criteria.7,17 However, it remains unclear if plasma levels of CRP are predictive of cardiovascular events after adjustment for measures of insulin resistance.
Recent studies of coronary artery calcification (CAC) in asymptomatic samples have shown an association of MetSyn and insulin resistance with the burden of coronary atherosclerosis.1821 Previously, we have reported on the association of established risk factors, including CRP, with CAC in the Study of Inherited Risk of Coronary Atherosclerosis (SIRCA).2224 In this report, we examine the association of MetSyn and measures of insulin resistance with CAC and we assess the incremental value of measures of insulin resistance in predicting of CAC beyond the clinical diagnosis of the MetSyn and plasma CRP levels.
| Methods |
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Evaluated Parameters
Study subjects were evaluated at the General Clinical Research Center at the University of Pennsylvania Medical Center after a 12-hour overnight fast. Plasma total cholesterol, HDL cholesterol, triglyceride, and glucose levels were measured enzymatically on a Cobas Fara II (Roche Diagnostic Systems Inc) in a Centers for Disease Controlcertified lipoprotein laboratory, with the use of Sigma reagents. LDL cholesterol was calculated by means of the Friedewald formula. Plasma insulin levels were measured with the use of a commercial enzyme immunoassay (Linco Research). The intra-assay coefficient of variation was 2.95±2.52% for insulin standard. The interassay coefficient of variation was 4.1% for insulin standard and 11.6% for pooled human plasma. Plasma CRP levels were assayed with the use of an ultra high-sensitivity latex turbidimetric immunoassay (Wako Ltd).23
Subjects were classified as having MetSyn by 2 criteria, the NCEP ATP III criteria10 and a modification of the original WHO definition as applied by Lakka et al5 and Laaksonen et al.12 By NCEP criteria, a person has MetSyn if 3 or more of the following are present: (1) central obesity: waist >102 cm in men and >88 cm in women, (2) hypertriglyceridemia:
1.695 mmol/L (150 mg/dL), (3) low HDL cholesterol: <1.036 mmoL/L (40 mg/dL) in men and <1.295 mmol/L (50 mg/dL) in women, (4) high blood pressure:
130/85 or use of blood pressure medications, (5) high fasting glucose:
6.1 mmol/L (110 mg/dL).
According to recent applications5,12 of WHO criteria, a person has MetSyn if they have insulin resistance defined as homeostasis model assessment (HOMA) index (fasting glucose [mmol/L] x fasting insulin [µU/mL]/22.5)25 in the top quartile (>2.114 in the SIRCA sample), impaired fasting glucose (
6.1 mmol/L), or diabetes with 2 or more of the following: (1) central obesity: waist >94 cm in men and >88 cm in women, (2) dyslipidemia: triglycerides
1.695 mmol/L or HDL <1.036 mmoL/L in women and 0.9065 mmol/L (35 mg/dL) in men, (3) high blood pressure:
140/90 or use of blood pressure medications. HOMA was the primary measure of insulin sensitivity, but fasting plasma insulin levels provided comparable results.
Global CAC scores were determined as described,24 with customized software (Imatron) used according to the method of Agatston26 from 40 continuous 3-mm-thick computed tomograms collected on an electron beam tomography (EBT) scanner (Imatron). Reproducibility studies with the use of these techniques suggest that artifact in EBT estimation of CAC accounts for a small proportion of CAC variability.27
Statistical Analysis
Data are reported as median and interquartile range or mean±SD for continuous variables and as proportions for categoric variables. Analyses were performed for each sex separately, in addition to the full sample. The crude association of MetSyn with CAC was examined as an ordinal variable (number of MetSyn features) or as a binary variable (presence or absence of NCEP or WHO criteria). The crude association of HOMA with CAC was examined through the use of HOMA quartiles (0.043 to <0.90, 0.90 to <1.427, 1.427 to <2.114, 2.114 to 7.751). Median CAC scores were compared across ordinal MetSyn categories and HOMA quartiles by means of the Kruskal-Wallis rank test and Wilcoxon test for trend. Ordinal logistic regression is a method appropriate for the analysis of CAC data, which has a markedly nonnormal distribution and a significant proportion of subjects with no detectable CAC.24,28 Ordinal CAC outcome categories were 0, 1 to 10, 11 to 100, 101 to 400, and >400, with published criteria used to approximate no, mild, moderate, and severe coronary atherosclerosis.29
The association of MetSyn with CAC was assessed in sex-specific models that included (1) MetSyn and age (age and age2); (2) MetSyn, CRP levels, non-MetSyn risk factors, and age; and (3) HOMA data, NCEP-defined MetSyn, CRP levels, non-MetSyn risk factors, and age. Non-MetSyn risk factors included smoking, family history of premature CAD, exercise, alcohol intake, race, LDL cholesterol, use of medications (aspirin, statins, ß-blockers, ACE inhibitors, and hormone replacement therapy). The association of HOMA (or plasma insulin) with CAC was assessed in models adjusted for (1) age; (2) age, CRP, and non-MetSyn risk factors; and (3) age, CRP, and non-MetSyn risk factors and NCEP-defined MetSyn.
The interaction between sex and MetSyn or HOMA data were assessed in adjusted models by means of the likelihood-ratio (LR) test. The LR test also was applied to nested models to determine if addition of HOMA to NCEP-defined MetSyn, plasma CRP levels to MetSyn, or HOMA improved the prediction of CAC. The results of ordinal logistic regression are presented as the odds ratio (OR) of being in a higher CAC category for the presence or absence of MetSyn and for a 1-U change in ln-HOMA. Statistical analyses were performed with the use of Stata 8.0 software (Stata Corp).
| Results |
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Approximately 27% of men and 22% of women met criteria for MetSyn according to NCEP (Table 2), roughly comparable to the age-adjusted prevalence for white subjects in the Third National Health and Nutrition Examination Survey (NHANES).1 Estimates of the prevalence of the WHO criteria were slightly lower (Table 2). Consistent with previous reports of a lack of sensitivity of NCEP-defined MetSyn for insulin resistance,8,12,15 15.1% (19.2% of men and 10.7% of women) of subjects classified as non-MetSyn by NCEP criteria (ie, expected not to be insulin resistant) had WHO-defined insulin resistance (HOMA values in the upper quartile). In fact, of subjects with HOMA values in the upper quartile, 45% were classified as not having MetSyn by the NCEP definition.
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Crude Association of MetSyn and Insulin Resistance With CAC
There was no statistically significant interaction between sex and MetSyn or HOMA data in the association with CAC. Median CAC scores were significantly higher in both men and women with MetSyn compared with those without (Table 2) and increased with increasing prevalence of MetSyn features according to NCEP criteria (trend, P<0.001) and WHO criteria (trend, P<0.001) (Figure). Median (interquartile range) CAC scores increased across HOMA quartiles (P<0.001) [(men: 2.0 (0 to 53), 2.5 (0 to 37.5), 6.0 (1.5 to 75.5), 20 (3 to 92); women: 0 (0 to 4), 1 (0 to 9), 1 (0 to 29), 4 (0 to 22)].
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Multivariable Analysis of the Association of MetSyn and Insulin Resistance With CAC
MetSyn definitions, individual MetSyn features, and HOMA index were associated with CAC in age-adjusted analyses, although the strength of these associations varied by sex and the criteria used (Table 3). Waist circumference was the strongest single predictor of CAC.
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Both MetSyn and HOMA index were independently associated with CAC after controlling for age, non-MetSyn risk factors, and plasma CRP (Table 4). Notably, adding ln-HOMA to a model with NCEP-defined MetSyn significantly strengthened (LR test P=0.001) the association with CAC, and adding MetSyn to a model containing ln-HOMA also improved (LR test P=0.006) prediction of CAC scores. In contrast, CRP did not add significantly to models that already contained MetSyn (LR test P=0.15) or ln-HOMA (LR test P=0.48). Results were similar when plasma insulin levels were used in place of HOMA data (Tables 3 and 4
).
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| Discussion |
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The insulin resistance syndrome or MetSyn2 is characterized by a clustering of atherosclerotic CVD risk factors.3,4,16 Insulin resistance is thought to be the most prominent pathophysiological process underlying MetSyn.2,14,15 The WHO definition of MetSyn11 requires the presence of insulin resistance plus 2 other of central obesity, hypertension, or dyslipidemia, whereas the NCEP definition does not require a laboratory measure of insulin.10 Despite this, the NCEP criteria, based on features typically correlated with insulin resistance, should identify insulin-resistant subjects. However, analysis of NHANES data suggests that the NCEP criteria fail to detect a significant proportion of patients with insulin resistance, particularly in ethnic minorities.8 The NCEP definition was less sensitive than the WHO definition in predicting both type 2 diabetes12,15 and the development of CVD in men.5,8,9 In our nondiabetic sample, the NCEP definition failed to detect
15% of subjects defined as insulin-resistant by WHO criteria.
Evidence continues to emerge supporting the increased risk of CVD events in patients with MetSyn.59,17 Lakka et al5 found a 2- to 4-fold increased risk of cardiovascular death with MetSyn in a sample of 1209 Finnish men free from diabetes and CVD at baseline. MetSyn predicted atherosclerosis progression and CVD events in 888 subjects in the Bruneck study, whereas most individual components of the syndrome were not significantly associated with CVD outcomes,9 supporting the concept that MetSyn provides information that is "more than the sum of its parts."31
Studies demonstrating an increased burden of subclinical atherosclerosis in subjects with insulin resistance and MetSyn suggest that promotion of atherosclerosis is a basis, at least in part, for the link to clinical events.9,1821,32 Arad et al18 found a positive association between CAC and the number of MetSyn features, HOMA, and visceral adiposity in the St Francis Heart Study (n=1160). In 1000 asymptomatic subjects recruited to the Prospective Army Coronary Calcification study, there was a graded association between CAC and the number of NCEP MetSyn features or the presence of MetSyn,20 but this failed to meet statistical significance for MetSyn after adjusting for LDL cholesterol (OR, 1.54 [0.91 to 2.6]). Wong et al21 found that the NCEP MetSyn (OR, 1.40 [1.05 to 1.87]) and the number of MetSyn features were associated with CAC after controlling for traditional risk factors in 1823 asymptomatic subjects.
Chronic inflammation may represent a common pathophysiological basis for insulin resistance, MetSyn, and atherosclerotic CVD.16,33 However, current definitions of MetSyn do not incorporate measures of inflammation. Recent studies have shown that CRP levels predict CVD even in subjects with NCEP-defined MetSyn.7,17 However, in SIRCA, CRP did not add value to the association with CAC beyond MetSyn or insulin resistance. Thus, an association between CRP and plaque rupture or thrombosis, rather than atherosclerotic burden, may form the basis for the relation of CRP to clinical events.23 Alternatively, CRP levels may not be predictive of CVD if laboratory measures of insulin resistance are included in the analyses. A unique and important finding in our study was that insulin resistance and NCEP-defined MetSyn were additive in the association with CAC, independent of plasma levels of CRP.
This study has several limitations. SIRCA is a cross-sectional, nonpopulation- based study that is predominantly white and may not be generalizable to minority groups.8 We used surrogate measures of insulin resistance and therefore may have underestimated its prevalence. There remains controversy regarding the type of atherosclerotic plaques detected at EBT and the utility of CAC in predicting clinical events. However, CAC exhibits strong correlation with both histopathological and angiographic measures of atherosclerosis,34,35 and prospective data support its ability to predict future events.36 The results of our study need to be confirmed in diverse samples with the use of alternative measures of atherosclerosis and, ultimately, in prospective studies of CVD.
| Conclusions |
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| Acknowledgments |
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| Footnotes |
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| References |
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2. Reaven GM. Banting lecture 1988: role of insulin resistance in human disease. Diabetes. 1988; 37: 15951607.[Abstract]
3. Meigs JB. Invited commentary: insulin resistance syndrome? Syndrome X? Multiple metabolic syndrome? A syndrome at all? Factor analysis reveals patterns in the fabric of correlated metabolic risk factors. Am J Epidemiol. 2000; 152: 908912.
4. 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: 897907.
5. Lakka HM, Laaksonen DE, Lakka TA, Niskanen LK, Kumpusalo E, Tuomilehto J, et al. The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA. 2002; 288: 27092716.
6. Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K, Nissen M, et al. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care. 2001; 24: 683689.
7. Sattar N, Gaw A, Scherbakova O, Ford I, OReilly DS, Haffner SM, et al. 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: 414419.
8. Ford ES, Giles WH. A comparison of the prevalence of the metabolic syndrome using two proposed definitions. Diabetes Care. 2003; 26: 575581.
9. Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Bonadonna RC, et al. Carotid atherosclerosis and coronary heart disease in the metabolic syndrome: prospective data from the Bruneck study. Diabetes Care. 2003; 26: 12511257.
10. 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). JAMA. 2001; 285: 24862497.
11. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications, II: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 1998; 15: 539553.[CrossRef][Medline] [Order article via Infotrieve]
12. 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: 10701077.
13. Meigs JB, Wilson PW, Nathan DM, DAgostino RB Sr, Williams K, Haffner SM. Prevalence and characteristics of the metabolic syndrome in the San Antonio Heart and Framingham Offspring Studies. Diabetes. 2003; 52: 21602167.
14. Balkau B, Charles MA, Drivsholm T, Borch-Johnsen K, Wareham N, Yudkin JS, et al. Frequency of the WHO metabolic syndrome in European cohorts, and an alternative definition of an insulin resistance syndrome. Diabetes Metab. 2002; 28: 364376.[Medline] [Order article via Infotrieve]
15. Hanley AJ, Wagenknecht LE, DAgostino RB Jr, Zinman B, Haffner SM. Identification of subjects with insulin resistance and beta-cell dysfunction using alternative definitions of the metabolic syndrome. Diabetes. 2003; 52: 27402747.
16. Festa A, DAgostino 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: 4247.
17. 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 14 719 initially healthy American women. Circulation. 2003; 107: 391397.
18. Arad Y, Newstein D, Cadet F, Roth M, Guerci AD. Association of multiple risk factors and insulin resistance with increased prevalence of asymptomatic coronary artery disease by an electron-beam computed tomographic study. Arterioscler Thromb Vasc Biol. 2001; 21: 20512058.
19. Meigs JB, Larson MG, DAgostino RB, Levy D, Clouse ME, Nathan DM, et al. Coronary artery calcification in type 2 diabetes and insulin resistance: the Framingham Offspring Study. Diabetes Care. 2002; 25: 13131319.
20. Hunt ME, OMalley PG, Feuerstein I, Taylor AJ. The relationship between the metabolic score and sub-clinical atherosclerosis detected with electron beam computed tomography. Coron Artery Dis. 2003; 14: 317322.[CrossRef][Medline] [Order article via Infotrieve]
21. Wong ND, Sciammarella MG, Polk D, Gallagher A, Miranda-Peats L, Whitcomb B, et al. The metabolic syndrome, diabetes, and subclinical atherosclerosis assessed by coronary calcium. J Am Coll Cardiol. 2003; 41: 15471553.
22. Valdes AM, Wolfe ML, OBrien EJ, Spurr NK, Gefter W, Rut A, et al. Val64Ile polymorphism in the C-C chemokine receptor 2 is associated with reduced coronary artery calcification. Arterioscler Thromb Vasc Biol. 2002; 22: 19241928.
23. Reilly MP, Wolfe ML, Localio AR, Rader DJ. C-reactive protein and coronary artery calcification: the Study of Inherited Risk of Coronary Atherosclerosis (SIRCA). Arterioscler Thromb Vasc Biol. 2003; 23: 18511856.
24. Reilly MP, Wolfe ML, Localio AR, Rader DJ. Coronary artery calcification and cardiovascular risk factors: impact of the analytic approach. Atherosclerosis. 2004; 173: 6978.[CrossRef][Medline] [Order article via Infotrieve]
25. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985; 28: 412419.[CrossRef][Medline] [Order article via Infotrieve]
26. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M, Jr., Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990; 15: 827832.[Abstract]
27. Achenbach S, Ropers D, Mohlenkamp S, Schmermund A, Muschiol G, Groth J, et al. Variability of repeated coronary artery calcium measurements by electron beam tomography. Am J Cardiol. 2001; 87: 210213.[CrossRef][Medline] [Order article via Infotrieve]
28. Newman AB, Naydeck BL, Whittle J, Sutton-Tyrrell K, Edmundowicz D, Kuller LH. Racial differences in coronary artery calcification in older adults. Arterioscler Thromb Vasc Biol. 2002; 22: 424430.
29. Rumberger JA, Brundage BH, Rader DJ, Kondos G. Electron beam computed tomographic coronary calcium scanning: a review and guidelines for use in asymptomatic persons. Mayo Clin Proc. 1999; 74: 243252.[Abstract]
30. Kardia SL, Haviland MB, Ferrell RE, Sing CF. The relationship between risk factor levels and presence of coronary artery calcification is dependent on apolipoprotein E genotype. Arterioscler Thromb Vasc Biol. 1999; 19: 427435.
31. Reilly MP, Rader DJ. The metabolic syndrome: more than the sum of its parts? Circulation. 2003; 108: 15461551.
32. Howard G, OLeary DH, Zaccaro D, Haffner S, Rewers M, Hamman R, et al. Insulin sensitivity and atherosclerosis: the Insulin Resistance Atherosclerosis Study (IRAS) Investigators. Circulation. 1996; 93: 18091817.
33. Ridker PM, Hennekens CH, Buring JE, Rifai N. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med. 2000; 342: 836843.
34. Rumberger JA, Simons DB, Fitzpatrick LA, Sheedy PF, Schwartz RS. Coronary artery calcium area by electron-beam computed tomography and coronary atherosclerotic plaque area: a histopathologic correlative study. Circulation. 1995; 92: 21572162.
35. Rumberger JA, Sheedy PF, Breen JF, Schwartz RS. Electron beam computed tomographic coronary calcium score cutpoints and severity of associated angiographic lumen stenosis. J Am Coll Cardiol. 1997; 29: 15421548.[Abstract]
36. Kondos GT, Hoff JA, Sevrukov A, Daviglus ML, Garside DB, Devries SS, et al. Electron-beam tomography coronary artery calcium and cardiac events: a 37-month follow-up of 5635 initially asymptomatic low- to intermediate-risk adults. Circulation. 2003; 107: 25712576.
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