Recent studies have shown that low-grade inflammation is linked both to insulin resistance (1,2) and the metabolic syndrome (3,4) and may even predict the development of type 2 diabetes (5–8).

However, adipose tissue might play an important role in these relationships. There is still controversy about whether low-grade inflammation is an intermediate factor between obesity and insulin resistance or whether it has an independent effect on the development of type 2 diabetes through a mechanism separate from obesity.

The aim of this study was to explore whether low-grade inflammation (measured by plasma C-reactive protein (CRP) levels) was related to insulin resistance and to parameters of metabolic syndrome, independent of obesity.

We conducted a cross-sectional, single-center study on 400 men aged between 40 and 80 years. The subjects, methods of recruitment, study procedures and anthropometrical and laboratory measurements have been described elsewhere (9). Twenty-one participants had prevalent diabetes and were excluded from the study; 13 participants were excluded because their level of CRP was above 10 mg/l and 2 because blood samples had been taken in a nonfasting state. Our final study population comprised 364 participants.

Various measures of obesity were obtained: weight, BMI, waist circumference, waist-to-hip ratio, visceral and subcutaneous fat using ultrasound measurement (10), and total body fat mass using dual-energy X-ray absorptiometry.

Information on prevalent diseases, medication use, and lifestyle factors was available. Peripheral blood pressure was measured. Physical activity was assessed using the Voorrips score (11).

High-sensitivity–CRP, HDL cholesterol, triglycerides, glucose, and insulin were measured in fasting blood samples. Details about the precision of the assays have been reported (9,12,13). Insulin sensitivity was determined with the homeostasis model assessment of insulin resistance (HOMA-IR): [fasting insulin (mU/l) × fasting glucose (mmol/l)]/22.5. The presence of metabolic syndrome was defined according to the National Cholesterol Education Program criteria (14).

Statistical analysis

Subjects were divided into quartiles according to their CRP level. Linear regression analysis was used to estimate the relation of CRP with insulin resistance and the individual components of metabolic syndrome. The P value for linear trend was calculated with the median of the CRP level in each quartile. Multivariate analyses were adjusted for age, smoking, and physical activity. To explore the relationship between CRP and insulin resistance and between CRP and metabolic syndrome independently of markers of obesity, the models were also adjusted for various different body composition parameters. Statistical analyses were performed using SPSS, version 12.0.1 for Windows.

In general, men with higher CRP levels were older, scored higher on markers of obesity, were less physically active, and had higher glucose levels and insulin resistance. They also fulfilled the criteria for metabolic syndrome more often (Online Appendix Table 1 [available at http://dx.doi.org/10.2337/dc06-2531]).

After adjusting for confounders (age, smoking, and physical activity), insulin resistance was significantly higher in the 4th quartile of CRP compared to the 1st, but after adjusting for the various parameters of obesity, the difference in HOMA-IR between the quartiles of CRP was no longer evident (Table 1). However, adjustment for subcutaneous fat attenuated the relationship between CRP and HOMA-IR to a lesser extent than the other parameters of obesity.

Of the individual components of metabolic syndrome, waist circumference, glucose, and HDL-cholesterol showed a statistically significant association with CRP (data not shown). When we further adjusted the relationship between CRP and the individual components of metabolic syndrome for measures of obesity, only glucose remained statistically significantly higher in the 4th quartile of CRP compared to the 1st quartile (Table 1).

CRP was not related to insulin resistance after adjustment for parameters of body composition, whereas CRP was independently associated with glucose, but not with the other components of metabolic syndrome.

Recently Kahn et al. (15) showed that the relationship between CRP and the number of components of metabolic syndrome markedly attenuated and became nonsignificant after adjusting for BMI in drug-naive type 2 diabetes patients. Because all the patients in their study satisfied the glucose criteria of metabolic syndrome by definition, this criterion did not contribute to the correlation between CRP and components of metabolic syndrome. Our study therefore broadens what is known about this topic, since it shows that CRP is associated with plasma glucose, independently of obesity. Furthermore, in healthy elderly men we confirmed Kahn et al.'s finding that CRP is not independently related to other components of metabolic syndrome.

Conflicting results have been found regarding the correlation between CRP and insulin resistance (2,16–20). However most of these studies did not have the prime aim of exploring the underlying pathways. Some of these studies did not therefore adjust for parameters of obesity at all, while others did not investigate the effect of a separate adjustment for obesity.

A limitation of our study is its cross-sectional design, and, therefore, we can only suggest, but not prove, the causality of the observed relationships. We used HOMA-IR and ultrasound instead of hyperinsulinemic-euglycemic clamp and computed tomography scan, respectively, for assessing insulin sensitivity and visceral and subcutaneous fat. However, these measurements have proven to be strongly correlated with the gold standards (correlation coefficients −0.82 and 0.81, respectively) (10,21)

Our data point to an obesity-independent mechanism which relates CRP and glucose. One explanation might be the proinflammatory effects of glucose: In itself, glucose is proinflammatory (22), and it can increase IL (interleukin)-6, tumor necrosis factor-α, and IL-18 release in healthy subjects and persons with impaired glucose tolerance (23). Furthermore, prolonged hyperglycemia and the accompanying production of excess amounts of advanced glycation end products can activate nuclear factor-κB (24). This will lead to an inflammatory reaction, independently of adipose tissue.

In conclusion, our findings strongly point to low-grade inflammation as an intermediate factor in the relationship between adipose tissue and insulin resistance. The independent association of glucose with CRP suggests an additional mechanism by which glucose and CRP are related, independent of obesity.

Table 1—

Relationship between CRP (in quartiles) and insulin resistance as assessed by HOMA-IR and between CRP (in quartiles) and glucose, with the first quartiles as reference

Adjustments*Insulin resistance: β-coefficient (95% CI) per quartile of CRP†
Glucose: β-coefficient (95% CI) per quartile of CRP†
1234P‡1234P‡
Confounders only Ref. 0.32 (−0.13 to 0.77) 0.38 (−0.07 to 0.82) 0.62 (0.15 to 1.09) 0.023 Ref. 0.17 (−0.12 to 0.45) 0.13 (−0.15 to 0.41) 0.57 (0.27 to 0.87) <0.001 
Weight Ref. 0.09 (−0.33 to 0.51) 0.04 (−0.39 to 0.46) 0.30 (−0.14 to 0.75) 0.163 Ref. 0.07 (−0.22 to 0.35) −0.01 (−0.29 to 0.27) 0.44 (0.14 to 0.73) 0.001 
WC Ref. 0.02 (−0.38 to 0.42) −0.06 (−0.46 to 0.35) 0.16 (−0.27 to 0.59) 0.396 Ref. 0.03 (−0.24 to 0.31) −0.04 (−0.32 to 0.23) 0.37 (0.07 to 0.67) 0.005 
WHR Ref. 0.07 (−0.36 to 0.49) 0.11 (−0.31 to 0.53) 0.27 (−0.19 to 0.72) 0.229 Ref. 0.04 (−0.24 to 0.32) 0.01 (−0.27 to 0.28) 0.39 (0.10 to 0.69) 0.003 
BMI Ref. 0.13 (−0.26 to 0.53) −0.02 (−0.42 to 0.38) 0.24 (−0.18 to 0.67) 0.293 Ref. 0.07 (−0.20 to 0.35) −0.04 (−0.31 to 0.24) 0.41 (0.11 to 0.70) 0.003 
Visceral fat Ref. 0.18 (−0.23 to 0.58) 0.01 (−0.40 to 0.42) 0.14 (−0.30 to 0.58) 0.730 Ref. 0.10 (−0.18 to 0.38) −0.02 (−0.30 to 0.26) 0.36 (0.10 to 0.66) 0.012 
Subcutaneous fat Ref. 0.07 (−0.37 to 0.51) 0.13 (−0.30 to 0.56) 0.49 (0.03 to 0.94) 0.020 Ref. 0.10 (−0.19 to 0.39) 0.07 (−0.22 to 0.35) 0.53 (0.23 to 0.83) <0.001 
Percentage of fat mass Ref. 0.02 (−0.38 to 0.42) −0.02 (−0.42 to 0.37) 0.06 (−0.37 to 0.50) 0.764 Ref. 0.04 (−0.25 to 0.32) −0.03 (−0.31 to 0.25) 0.39 (0.08 to 0.71) 0.006 
Adjustments*Insulin resistance: β-coefficient (95% CI) per quartile of CRP†
Glucose: β-coefficient (95% CI) per quartile of CRP†
1234P‡1234P‡
Confounders only Ref. 0.32 (−0.13 to 0.77) 0.38 (−0.07 to 0.82) 0.62 (0.15 to 1.09) 0.023 Ref. 0.17 (−0.12 to 0.45) 0.13 (−0.15 to 0.41) 0.57 (0.27 to 0.87) <0.001 
Weight Ref. 0.09 (−0.33 to 0.51) 0.04 (−0.39 to 0.46) 0.30 (−0.14 to 0.75) 0.163 Ref. 0.07 (−0.22 to 0.35) −0.01 (−0.29 to 0.27) 0.44 (0.14 to 0.73) 0.001 
WC Ref. 0.02 (−0.38 to 0.42) −0.06 (−0.46 to 0.35) 0.16 (−0.27 to 0.59) 0.396 Ref. 0.03 (−0.24 to 0.31) −0.04 (−0.32 to 0.23) 0.37 (0.07 to 0.67) 0.005 
WHR Ref. 0.07 (−0.36 to 0.49) 0.11 (−0.31 to 0.53) 0.27 (−0.19 to 0.72) 0.229 Ref. 0.04 (−0.24 to 0.32) 0.01 (−0.27 to 0.28) 0.39 (0.10 to 0.69) 0.003 
BMI Ref. 0.13 (−0.26 to 0.53) −0.02 (−0.42 to 0.38) 0.24 (−0.18 to 0.67) 0.293 Ref. 0.07 (−0.20 to 0.35) −0.04 (−0.31 to 0.24) 0.41 (0.11 to 0.70) 0.003 
Visceral fat Ref. 0.18 (−0.23 to 0.58) 0.01 (−0.40 to 0.42) 0.14 (−0.30 to 0.58) 0.730 Ref. 0.10 (−0.18 to 0.38) −0.02 (−0.30 to 0.26) 0.36 (0.10 to 0.66) 0.012 
Subcutaneous fat Ref. 0.07 (−0.37 to 0.51) 0.13 (−0.30 to 0.56) 0.49 (0.03 to 0.94) 0.020 Ref. 0.10 (−0.19 to 0.39) 0.07 (−0.22 to 0.35) 0.53 (0.23 to 0.83) <0.001 
Percentage of fat mass Ref. 0.02 (−0.38 to 0.42) −0.02 (−0.42 to 0.37) 0.06 (−0.37 to 0.50) 0.764 Ref. 0.04 (−0.25 to 0.32) −0.03 (−0.31 to 0.25) 0.39 (0.08 to 0.71) 0.006 
*

All analyses are adjusted for the following confounders: age, physical activity, and smoking.

†

CRP quartile ranges: 1) 0–0.6, 2) 0.6–1.2, 3) 1.2–2.6, and 4) 2.6–10.0 mg/l.

‡

P for trend. WC, waist circumference; WHR, waist-to-hip ratio.

View Large

We thank Jackie Senior for critically reading the manuscript. This work was supported by an Innovatieve Onderzoeks Programma's (Innovative Research Programs) grant from the Dutch Ministry of Economic Affairs (grant no. IGE05012).

1.
Yudkin JS, Stehouwer CD, Emeis JJ, Coppack SW: C-reactive protein in healthy subjects: associations with obesity, insulin resistance, and endothelial dysfunction: a potential role for cytokines originating from adipose tissue?
Arterioscler Thromb Vasc Biol
 
19
:
972
–978,
1999
2.
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
 
102
:
42
–47,
2000
3.
Florez H, Castillo-Florez S, Mendez A, Casanova-Romero P, Larreal-Urdaneta C, Lee D, Goldberg R: C-reactive protein is elevated in obese patients with the metabolic syndrome.
Diabetes Res Clin Pract
 
71
:
92
–100,
2006
4.
Tamakoshi K, Yatsuya H, Kondo T, Hori Y, Ishikawa M, Zhang H, Murata C, Otsuka R, Zhu S, Toyoshima H: The metabolic syndrome is associated with elevated circulating C-reactive protein in healthy reference range, a systemic low-grade inflammatory state.
Int J Obes Relat Metab Disord
 
27
:
443
–449,
2003
5.
Freeman DJ, Norrie J, Caslake MJ, Gaw A, Ford I, Lowe GD, O'Reilly DS, Packard CJ, Sattar N: C-reactive protein is an independent predictor of risk for the development of diabetes in the West of Scotland Coronary Prevention Study.
Diabetes
 
51
:
1596
–1600,
2002
6.
Festa A, D'Agostino R Jr, Tracy RP, Haffner SM: Elevated levels of acute-phase proteins and plasminogen activator inhibitor-1 predict the development of type 2 diabetes: the insulin resistance atherosclerosis study.
Diabetes
 
51
:
1131
–1137,2002
7.
Barzilay JI, Abraham L, Heckbert SR, Cushman M, Kuller LH, Resnick HE, Tracy RP: The relation of markers of inflammation to the development of glucose disorders in the elderly: the Cardiovascular Health Study.
Diabetes
 
50
:
2384
–2389,
2001
8.
Pradhan AD, Manson JE, Rifai N, Buring JE, Ridker PM: C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus.
JAMA
 
286
:
327
–334,
2001
9.
Muller M, Grobbee DE, den Tonkelaar I, Lamberts SW, van der Schouw YT: Endogenous sex hormones and metabolic syndrome in aging men.
J Clin Endocrinol Metab
 
90
:
2618
–2623,
2005
10.
Stolk RP, Wink O, Zelissen PM, Meijer R, van Gils AP, Grobbee DE: Validity and reproducibility of ultrasonography for the measurement of intra-abdominal adipose tissue.
Int J Obes Relat Metab Disord
 
25
:
1346
–1351,
2001
11.
Voorrips LE, Ravelli AC, Dongelmans PC, Deurenberg P, Van Staveren WA: A physical activity questionnaire for the elderly.
Med Sci Sports Exerc
 
23
:
974
–979,
1991
12.
Nakhai Pour HR, Grobbee DE, Muller M, van der Schouw YT: Association of endogenous sex hormone with C-reactive protein levels in middle-aged and elderly men.
Clin Endocrinol
 
65
:
621
–622,
2007
13.
Weitgasser R, Gappmayer B, Pichler M: Newer portable glucose meters: analytical improvement compared with previous generation devices?
Clin Chem
 
45
:
1821
–1825,
1999
14.
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
 
285
:
2486
–2497,
2001
15.
Kahn SE, Zinman B, Haffner SM, O'Neill MC, Kravitz BG, Yu D, Freed MI, Herman WH, Holman RR, Jones NP, Lachin JM, Viberti GC: Obesity is a major determinant of the association of C-reactive protein levels and the metabolic syndrome in type 2 diabetes.
Diabetes
 
55
:
2357
–2364,
2006
16.
Temelkova-Kurktschiev T, Siegert G, Bergmann S, Henkel E, Koehler C, Jaross W, Hanefeld M: Subclinical inflammation is strongly related to insulin resistance but not to impaired insulin secretion in a high risk population for diabetes.
Metabolism
 
51
:
743
–749,
2002
17.
Hak AE, Stehouwer CD, Bots ML, Polderman KH, Schalkwijk CG, Westendorp IC, Hofman A, Witteman JC: Associations of C-reactive protein with measures of obesity, insulin resistance, and subclinical atherosclerosis in healthy, middle-aged women.
Arterioscler Thromb Vasc Biol
 
19
:
1986
–1991,
1999
18.
Kriketos AD, Greenfield JR, Peake PW, Furler SM, Denyer GS, Charlesworth JA, Campbell LV: Inflammation, insulin resistance, and adiposity: a study of first-degree relatives of type 2 diabetic subjects.
Diabetes Care
 
27
:
2033
–2040,
2004
19.
Forouhi NG, Sattar N, McKeigue PM: Relation of C-reactive protein to body fat distribution and features of the metabolic syndrome in Europeans and South Asians.
Int J Obes Relat Metab Disord
 
25
:
1327
–1331,
2001
20.
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
 
23
:
650
–655,
2003
21.
Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, Monauni T, Muggeo M: Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity.
Diabetes Care
 
23
:
57
–63,
2000
22.
Mohanty P, Hamouda W, Garg R, Aljada A, Ghanim H, Dandona P: Glucose challenge stimulates reactive oxygen species (ROS) generation by leucocytes.
J Clin Endocrinol Metab
 
85
:
2970
–2973,
2000
23.
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
 
106
:
2067
–2072,
2002
24.
Shoelson SE, Lee J, Goldfine AB: Inflammation and insulin resistance.
J Clin Invest
 
116
:
1793
–1801,
2006

Published ahead of print at http://care.diabetesjournals.org on 19 March 2007. DOI: 10.2337/dc06-2531.

Additional information for this article can be found in an online appendix at http://dx.doi.org/10.2337/dc06-2531.

C.W. is currently affiliated with the Department of Genetics, University Medical Center Groningen, Groningen, the Netherlands.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C Section 1734 solely to indicate this fact.

DIABETES CARE
2007

Supplementary data

Supplemental Table 1: Baseline characteristics of subjects- doc file