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Journal of Clinical Endocrinology & Metabolism, doi:10.1210/jc.2007-0955
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The Journal of Clinical Endocrinology & Metabolism Vol. 92, No. 12 4569-4574
Copyright © 2007 by The Endocrine Society

Low-Grade Inflammation, Obesity, and Insulin Resistance in Adolescents

Christian Herder, Sophie Schneitler, Wolfgang Rathmann, Burkhard Haastert, Heiko Schneitler, Horst Winkler, Renate Bredahl, Erik Hahnloser and Stephan Martin

Institute for Clinical Diabetes Research (C.H., S.S., S.M.) and Institute of Biometrics and Epidemiology (W.R., B.H.), German Diabetes Center, Leibniz Institute at Heinrich Heine University, 40225 Düsseldorf, Germany; and Gesundheitsamt (Public Health Office) (H.S., H.W., R.B., E.H.), 40227 Düsseldorf, Germany

Address all correspondence and requests for reprints to: Dr. Christian Herder, Institute for Clinical Diabetes Research, German Diabetes Center, Auf’m Hennekamp, 40225 Düsseldorf, Germany. E-mail: christian.herder{at}ddz.uni-duesseldorf.de.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Context: Low-grade inflammation is associated with insulin resistance and precedes the onset of type 2 diabetes mellitus in adults, but there are no comparable data in youth.

Objective: The objective of the study was to characterize the pattern of subclinical immune activation that is associated with indices of obesity and insulin resistance in youth and analyze whether this association is explained by obesity.

Design: This was a cross-sectional study.

Setting: Medical check-up of schoolchildren was conducted by the Public Health Office in Düsseldorf (Germany).

Participants: Participants included 519 adolescents (mean age 15.5 ± 0.8 yr).

Main Outcome Measures: Measures included body mass index (BMI) and waist circumference (WC) as indices of obesity; fasting glucose, insulin, and homeostasis model assessment of insulin resistance; serum concentrations of TNF{alpha}, IL-6, IL-8, IL-18, monocyte chemoattractant protein-1, interferon-{gamma}-inducible protein (IP)-10 and adiponectin as immunological variables.

Results: In age-, sex-, and lipid-adjusted analyses, IL-6, IL-18, IP-10, and adiponectin (inversely) were associated with both BMI and WC (all P ≤ 0.002). None of the immune markers was related to glucose, but IL-6, IL-18, and adiponectin (inversely) were associated with insulin and homeostasis model assessment of insulin resistance in age- and sex-adjusted models. Adjustment for BMI or WC indicated that a considerable proportion of these associations may be mediated by obesity.

Conclusions: We found that a differential low-grade immune activation is associated with parameters of obesity in adolescents. Moreover, there is evidence that IL-6, IL-18, IP-10, and adiponectin (inversely) are associated with insulin resistance and that these associations can mainly be attributed to obesity.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
IN ADULTS, NUMEROUS STUDIES have shown that a differential, subclinical, chronic activation of the immune system precedes the manifestation of type 2 diabetes mellitus (T2DM). Elevated systemic concentrations of specific acute-phase proteins, cytokines, and chemokines as well as reduced levels of the adipokine adiponectin predict the development of T2DM (1, 2). This association between low-grade inflammation and T2DM remains significant after adjustment for traditional risk factors so that it is reasonable to assume that low-grade inflammation is relevant in the pathogenesis of T2DM. However, some of the association between elevated levels of immune mediators and T2DM is also explained by obesity because adipose tissue has been shown to secrete many of the cytokines and chemokines that are considered T2DM risk factors (3, 4, 5, 6, 7).

The analysis of the role of low-grade inflammation in the development of insulin resistance and T2DM in children and adolescents is relevant because, in contrast to adults, it can be assumed that associations between low-grade inflammation, insulin resistance, and T2DM are not confounded by chronic inflammatory conditions such as cardiovascular disease, arthritis, or bronchitis that are frequent comorbidities in T2DM patients or in old age. However, to the best of our knowledge, data from prospective studies that investigate low-grade inflammation as a risk factor for T2DM in youth are not available. There is some evidence from case-control and cross-sectional surveys that low-grade inflammation is associated with T2DM risk and insulin resistance in children and adolescents. Most data come from studies that describe the positive association between C-reactive protein (CRP) and obesity as a major risk factor for T2DM (8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21). Only a few studies also investigated the relationship between CRP and glucose metabolism and found that higher levels of CRP were associated with elevated fasting insulin levels and/or insulin resistance (14, 19, 20). These observations were extended in one study that showed that the positive association between CRP and insulin is markedly attenuated after adjusting for BMI (14). This finding indicates that in youth as well as adults, the association between inflammation and T2DM risk cannot be explained by obesity alone and may support the development of T2DM at all ages.

Although CRP is widely considered a general marker of immune activation, cross-sectional studies show that CRP is only moderately or weakly correlated with many cytokines, chemokines, and adiponectin (22, 23, 24) and that the significant association between elevated levels of these mediators of innate immunity and incident T2DM is independent of CRP levels (25, 26). Thus, it can be expected that these markers represent different components of the immune system and that they provide different information than CRP measurement. It is therefore interesting that several other reports suggested that also circulating concentrations of IL-6 (18, 21, 27), TNF{alpha} (16, 28), soluble TNF{alpha} receptors (18, 28, 29), and E-selectin (21) are elevated in obesity and that IL-6 (27) and soluble TNF{alpha} receptor 2 may be associated with insulin resistance in children and adolescents (29).

In addition, there are data from multiple adolescent populations on the inverse association between adiponectin and obesity and insulin resistance (30, 31, 32). Adiponectin may be largely independent of systemic levels of many cytokines and chemokines (23) but has been shown to have strong antiinflammatory effects on the molecular and cellular level (33, 34) so that it may also be considered as immune marker.

Taken together, there is growing evidence that obesity is associated with low-grade inflammation in youth, but data on the association with insulin resistance are limited to CRP and soluble TNF{alpha} receptor 2. The objectives of this study were thus as follows: 1) to investigate the association between low-grade inflammation and measures of both obesity and glucose metabolism by analyzing immune mediators that are expressed in adipocytes and may represent novel risk factors for the development of T2DM in adults, and 2) to examine whether the association between low-grade inflammation and insulin resistance is independent of obesity as assessed by body mass index (BMI) and waist circumference (WC).


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Study design/participants

In Düsseldorf (Germany), all school-leaving students from selected secondary schools are routinely invited to a medical check-up by the local Public Health Office (Gesundheitsamt) in their final year. The schools that are enrolled in this program (Hauptschulen and Sonderschulen) are characterized by an overrepresentation of schoolchildren with lower socioeconomic status, with learning difficulties or other special needs. In 2005, 1261 schoolchildren were examined, and complete data on age, sex, and anthropometric and metabolic variables including BMI and fasting glucose were obtained from 721 adolescents (57%; 404 boys, 317 girls) as described before (35). This study was based on a subset of 519 of these participants for whom sufficient quantities of serum for the determination of insulin and immune markers was available. There were no statistically significant differences between this subset (n = 519) and the individuals for whom insufficient serum was available (n = 202) regarding age; BMI; WC; blood pressure; or levels of glucose, triglycerides, total cholesterol, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol (data not shown). Written informed consent was obtained from the parents and oral consent from all adolescents. All parts of the study were performed in accordance with the guidelines in the Declaration of Helsinki.

Data collection and biochemical analyses

Body weight was measured in light clothing to the nearest 0.1 kg and height to the nearest 0.1 cm. BMI was calculated as weight in kilograms divided by the square of height in meters. Waist circumference was measured at a level midway between the lower rib margin and iliac crest to the nearest 0.5 cm. Blood pressure was measured using an automatic device (Boso-Medicus Prestige; Bosch+Sohn, Jungingen, Germany).

After overnight fasting, serum samples were obtained for metabolic and immunological analyses. The Dimension Xpand analyzer (Dade Behring, Eschborn, Germany) was used to measure blood glucose (hexokinase method; GLUC Flex), triglycerides, total cholesterol (CHOL Flex), and HDL cholesterol (AHDL Flex). LDL cholesterol was calculated with the Friedewald formula.

Serum samples were stored at –80 C for analysis of insulin and immune markers. Insulin was measured using an ELISA from Biosource (Solingen, Germany). homeostasis model assessment of insulin resistance (HOMA-IR) was determined as fasting plasma glucose (mmol/liter)* fasting serum insulin (milliinternational units per liter)/22.5. IL-6, TNF{alpha}, and total adiponectin were measured using Quantikine HS (IL-6, TNF{alpha}) and Quantikine (adiponectin) ELISAs from R&D Systems (Wiesbaden, Germany). Serum levels of IL-18, IL-8, monocyte chemoattractant protein (MCP)-1, and inducible protein (IP)-10 were quantified using a bead-based multiplex assay on a Luminex 100 analyzer (Luminex Corp., Austin, TX) as described (25, 26). Fluorescent xMAP COOH microspheres were purchased from Luminex. Recombinant proteins were obtained from MBL (Nagoya, Japan; IL-18), R&D Systems (MCP-1), the National Institute for Biological Standards and Controls (Potters Bar, UK; IL-8), and BD Biosciences (Heidelberg, Germany; IP-10). Antibody pairs were purchased from MBL (IL-18), R&D Systems (MCP-1, IL-8), and BD Biosciences (IP-10). Assay characteristics for the measurement of insulin, IL-6, IL-18, TNF{alpha}, IL-8, MCP-1, IP-10, and adiponectin were as follows: intraassay coefficients of variation, 1.7, 5.2, 3.7, 6.7, 3.6, 3.0, 3.6, and 10.6%, respectively; interassay coefficients of variation, 5.1, 15.5, 8.5, 8.8, 17.8, 5.8, 22.7, and 13.6%, respectively; limits of detection, 1.3 mIU/liter, 0.08 pg/ml, 9.8 pg/ml, 0.25 pg/ml, 0.62 pg/ml, 4.9 pg/ml, 9.8 pg/ml, and 1.9 pg/ml, respectively.

Statistical analyses

The distributions of continuous variables were assessed for normality and ln transformations of skewed variables were used. Data with Gaussian distribution were described by means ± SD and all other continuous variables by median and 25th/75th percentiles. Differences between boys and girls were analyzed by unpaired t test or Wilcoxon test, respectively. For dichotomous variables, absolute numbers were given. Pearson correlation coefficients were used to analyze associations between ln-transformed values of cytokine, chemokine, and adiponectin concentrations. Associations of serum concentrations of immunological markers and measures of obesity or glucose metabolism were analyzed using multiple linear regression models with ln-transformed concentrations of immune markers as dependent and BMI, WC, total cholesterol, HDL cholesterol, triglycerides (ln-transformed), glucose, insulin (ln-transformed) or HOMA-IR (ln-transformed) as independent variables. The level of significance was set at 0.05. Calculations were carried out using the SAS statistical package version 8.2 TS2M0 (SAS Institute, Cary, NC).


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
Characteristics of the study population

Table 1Go gives an overview of the characteristics of study participants. Boys and girls differed statistically significantly in most of the investigated anthropometric and metabolic variables. Briefly, girls were slightly younger and had lower systolic pressure and higher BMI, insulin, HOMA-IR, triglycerides, total cholesterol, HDL cholesterol, and LDL cholesterol than boys (Table 1Go). For the immunological markers, we found significant sex differences for MCP-1, IP-10, and adiponectin (P < 0.05).


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  		TABLE 1. Description of the study population stratified by sex

 
Correlations between the immunological markers

Table 2Go summarizes the results from the total study population (i.e. boys and girls combined) because, in contrast to the systemic concentrations, correlations among immune markers were not different between boys and girls (data not shown). Systemic concentrations of cytokines, chemokines, and adiponectin correlated with each other to some extent, but apart from the correlations between IL-6 and TNF{alpha} (r = 0.23) and between IL-18 and IP-10 (r = 0.23), correlations were relatively low (|r| < 0.2) (Table 2Go).


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  		TABLE 2. Correlations among cytokines, chemokines, and adiponectin in the total study population

 
Associations between immune markers and measures of obesity and glucose metabolism

First, we used multiple linear regression models to characterize the association between the seven measured immunological biomarkers and BMI and WC as parameters of obesity. There was a consistent pattern of elevated levels of IL-6, IL-18, and IP-10 and lower adiponectin levels that was significantly associated with both higher BMI and higher WC (P ≤ 0.001 in all cases; Table 3Go). In contrast, TNF{alpha} and MCP-1 were not significantly associated with BMI and WC. There was also a borderline significant inverse association between IL-8 and WC (P = 0.047) but not with BMI. These results remained virtually unaltered after additional adjustment for lipids, i.e. total cholesterol, HDL cholesterol, and triglycerides.


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  		TABLE 3. Association between immune mediators and indices of obesity

 
Second, the analysis of indices of glucose metabolism showed that none of the measured biomarkers was significantly associated with glucose levels in age- and sex-adjusted models or after adjustment for age, sex, lipids, and either BMI or WC (Table 4Go).


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  		TABLE 4. Association between immune mediators and parameters of glucose metabolism

 
Third, regarding insulin and HOMA-IR, the data indicated a similar pattern as in the association with BMI and WC. After adjustment for age and sex, IL-6, IL-18, and (inversely) adiponectin were significantly associated with both insulin and HOMA-IR, whereas IP-10 was associated only with insulin (Table 4Go). Adjustment for lipids had almost no impact on the associations among IL-6, IL-18, insulin, and HOMA-IR, whereas the associations among IP-10, adiponectin, insulin, and HOMA-IR were attenuated. To find out whether the associations between immune markers and indices of glucose metabolism were mediated by or independent of obesity, BMI or WC was included in the models (Table 4Go). Adjustment for BMI or WC almost eliminated the associations of IL-18, IP-10, and adiponectin with insulin and HOMA-IR but indicated that the association between IL-6 and insulin may be partly independent of obesity (P = 0.024 and P = 0.068 in the WC- and BMI-adjusted models, respectively). In contrast to these results, adjustment for WC strengthened the association of MCP-1 with HOMA-IR (P = 0.032), but the association did not reach significance in the analogous BMI-adjusted model (P = 0.089).

Because the use of oral contraceptives (OCs) could be a confounder in the association between low-grade inflammation and metabolic parameters, we compared girls who reported use of OCs (n = 31) with those who did not (n = 166) and found no significant differences regarding age, BMI, WC, glucose, insulin, HOMA-IR, blood pressure, total cholesterol, HDL cholesterol, and six of the seven investigated immune mediators. Girls who used OCs had higher levels of triglycerides (P = 0.013), higher LDL (P = 0.037), and lower levels of IL-6 (P = 0.020). To assess whether the use of OCs affected the associations between low-grade inflammation and indexes of obesity and insulin resistance, we calculated age-adjusted, age- and BMI-adjusted, and age- and WC-adjusted multiple linear regression models with and without use of OCs. However, the addition of OCs had virtually no effect on β- or P values of the associations between immune mediators and parameters of obesity and insulin resistance (data not shown).


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
In the present study, we analyzed the relationship among low-grade inflammation, obesity, and insulin resistance in adolescents. There are three main findings that result from our study.

Inflammation and obesity

The first main finding was that obesity in youth is associated with a specific up-regulation of proinflammatory cytokines and chemokines and a down-regulation of the antiinflammatory adipokine adiponectin. Our data go beyond previous studies because this is the first study to examine the association with systemic chemokine levels and indices of obesity in youth. Chemokines are discussed as mediators in the infiltration of leukocytes into adipose tissue in obesity (36) and may therefore play an important role in establishing and maintaining a proinflammatory state that predisposes to the development of T2DM and cardiovascular disease (1, 2, 4, 37).

Although all seven immunological mediators that were measured in this study are expressed by and secreted by adipose tissue (3, 4, 5, 6, 7), we found that high BMI and WC were highly significantly associated only with elevated circulating levels of IL-6, IL-18, and IP-10 as well as lower levels of adiponectin (P ≤ 0.001 in age- and sex-adjusted analyses), whereas no significant associations could be detected for TNF{alpha} and MCP-1. IL-8 showed a weak inverse association with WC (P = 0.047) but not BMI (P = 0.260). Given the fact that IL-8 is an adipokine that has been shown to be positively associated with various indices of obesity in adults (22), it is conceivable that this difference is due to a chance finding as result of multiple tests in the present study. Because our previous studies in adults showed some associations between systemic concentrations of immune mediators and lipids (22, 23, 25, 26), we also adjusted for total cholesterol, HDL cholesterol, and triglycerides, but these adjustments did not alter the aforementioned associations in youth.

IL-6, TNF{alpha}, and adiponectin have been investigated before in this context, and our data confirm previously described associations between obesity and IL-6 (18, 21, 27) as well as adiponectin (30, 31, 32). However, we could not replicate reports on a positive association between obesity and TNF{alpha} (16, 28). This inconsistency may be attributable to the different study designs. The present study is based on an population of mostly nonobese schoolchildren with continuous distributions of BMI and WC, whereas Moon et al. (28) and Reinehr et al. (16) compared TNF{alpha} concentrations from obese adolescent patients and lean controls (i.e. focusing on the extremes of the distributions for BMI and WC) and may therefore have been better able to detect less pronounced associations than our study design.

Low-grade inflammation and insulin resistance

The second main finding of this study is the fact that basal insulin resistance (HOMA-IR) is associated with the same pattern of immune activation as BMI and WC. Increased levels of IL-6 (27) and decreased levels of adiponectin in insulin resistance (30, 31, 32) have been described before in children and adolescents, but to the best of our knowledge, data on the association among IL-18, TNF{alpha}, IL-8, MCP-1, and IP-10 and obesity in youth have not been reported. However, these immune markers are of considerable interest because elevated levels of IL-18, IL-8, MCP-1, and IP-10 precede the onset of T2DM in adults (25, 26) and may thus also be important for the mechanism of the development of insulin resistance and T2DM in youth. These immune mediators were only moderately or weakly correlated with each other in the present study, and previous studies did not find stronger correlations with CRP (22, 23, 24), so that measurement of multiple cytokines, chemokines, and adipokines provides much more information on the quality of immune activation than CRP alone.

The association among IL-6, IL-18, IP-10, and adiponectin on the one side and insulin resistance on the other side appeared mainly mediated by the association of these immune markers with fasting insulin levels, not fasting glucose levels. This was different from MCP-1, which showed only a borderline significant association with insulin resistance (P = 0.068 in the age and sex adjusted model), which appeared mainly attributable to a trend toward association with fasting glucose levels, not with fasting insulin.

Obesity as confounder in the association between low-grade inflammation and insulin resistance?

The third main result from this study refers to the role of obesity in the relationship between low-grade inflammation and insulin resistance. We found that the associations between systemic concentrations of immune mediators with insulin resistance were strongly confounded by BMI and WC and to a lesser extent also by lipid levels. The association between IL-6 and insulin resistance were attenuated, and associations between IL-18, IP-10 and adiponectin with insulin resistance disappeared when lipids and either BMI or WC were included as covariables in linear regression models. Therefore, obesity seems to mediate most of the association between these markers and insulin resistance. The same model also indicated that MCP-1 might be associated with insulin resistance independently of obesity. We are aware of one study that has also investigated this aspect in adolescents (14). In this Canadian population of schoolchildren, there was a strong association between CRP and fasting insulin levels that was considerably attenuated by adjustment for BMI.

Overall, our data suggest that IL-6 may be associated with fasting insulin levels and that MCP-1 may be associated with HOMA-IR. IL-6 has been described in many studies as an independent risk factor for T2DM in adults, although the exact role of this cytokine in the pathogenesis of T2DM is not yet clear (Ref. 38 and references therein). We previously showed that elevated levels of MCP-1 predict the manifestation of T2DM in an elderly cohort, even after adjustment for multiple risk factors (26). The importance of low-grade immune activation that we describe here, be it obesity related or obesity independent, is further emphasized by recent studies that demonstrate that a proinflammatory state also represents a major cardiovascular risk factor (37).

Strengths and limitations

Our study has several limitations that need to be addressed. First, because it is a cross-sectional study, we cannot infer conclusions about cause and effect in the relationships between subclinical inflammation, obesity, and insulin resistance. Second, we used BMI and WC as markers of obesity but did not have data on other measures of body fat distribution. Third, we assessed insulin resistance using HOMA-IR and not the hyperinsulinemic-euglycemic clamp or frequently sampled iv glucose tolerance test, which are widely considered to be more accurate. However, HOMA-IR has been validated as a surrogate marker of insulin resistance in nondiabetic children and adolescents in several studies and compares reasonably well with clamp or frequently sampled iv glucose tolerance test data (39, 40, 41, 42). Fourth, the characterization of the study participants could have been more extensive. Data on the ethnic background or the family history of type 2 diabetes were not available and could therefore not be included in our multiple regression models as potential confounders. However, given the young age of participants, the prevalence of type 2 diabetes, at least among first-degree relatives, can be expected to be very low and should not affect our results. Fifth, the participation rate of 57% was only modest, which might have led to a selection bias.

There are also several strengths of the present study that should be mentioned briefly. The sample was relatively large; study participants were recruited from secondary schools and not from hospital-based case-control settings (therefore resulting in a population with a continuous distribution of risk factors and thus yielding a more accurate estimation of the strength of associations); and the characterization of immune activation based on three cytokines, three chemokines, and adiponectin was more comprehensive than in previous studies.

Conclusions

In conclusion, high BMI and high WC are associated with a specific pattern of low-grade immune activation in adolescents. The same proinflammatory pattern is also seen in insulin-resistant boys and girls. Obesity appears to mediate some of this association. However, prospective studies will be necessary to evaluate the relevance of subclinical inflammation for T2DM risk in youth and allow comparisons of the role of this mechanism among children, adolescents, and adults.


   Acknowledgments
 
The authors thank Dr. Michael Schäfer, Dr. Jörg-Schmitz-Beuting, and Christian Schmitz-Beuting (Public Health Office, Düsseldorf) for their support with conducting the study and Ulrike Poschen and Gabi Gornitzka (German Diabetes Center, Düsseldorf) for excellent technical assistance.


   Footnotes
 
This work was supported by the German Federal Ministry of Health and Social Security and the Ministry of Science and Research of the State North-Rhine Westphalia.

Disclosure Statement: The authors have nothing to disclose.

First Published Online October 2, 2007

Abbreviations: BMI, Body mass index; CRP, C-reactive protein; HDL, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; IP, interferon-{gamma}-inducible protein; LDL, low-density lipoprotein; MCP, monocyte chemoattractant protein; OC, oral contraceptive; T2DM, type 2 diabetes mellitus; WC, waist circumference.

Received April 27, 2007.

Accepted September 21, 2007.


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 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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