Abstract
Objective:
The aim of the study was to investigate the associations between IL-1 receptor antagonist (IL-1RA), IL-6, IL-10, measures of obesity, and insulin resistance in African-Americans.
Research Design and Methods:
Nondiabetic participants (n = 1025) of the Howard University Family Study were investigated for associations between serum IL (IL-1RA, IL-6, IL-10), measures of obesity, and insulin resistance, with adjustment for age and sex. Measures of obesity included body mass index, waist circumference, hip circumference, waist-to-hip ratio, and percent fat mass. Insulin resistance was assessed using the homeostasis model assessment of insulin resistance (HOMA-IR). Data were analyzed with R statistical software using linear regression and likelihood ratio tests.
Results:
IL-1RA and IL-6 were associated with measures of obesity and insulin resistance, explaining 4–12.7% of the variance observed (P values < 0.001). IL-1RA was bimodally distributed and therefore was analyzed based on grouping those with low vs. high IL-1RA levels. High IL-1RA explained up to 20 and 12% of the variance in measures of obesity and HOMA-IR, respectively. Among the IL, only high IL-1RA improved the fit of models regressing HOMA-IR on measures of obesity. In contrast, all measures of obesity improved the fit of models regressing HOMA-IR on IL. IL-10 was not associated with obesity measures or HOMA-IR.
Conclusions:
High IL-1RA levels and obesity measures are associated with HOMA-IR in this population-based sample of African-Americans. The results suggest that obesity and increased levels of IL-1RA both contribute to the development of insulin resistance.
Obesity and inflammation are associated with each other and with insulin resistance (1). Obesity, insulin resistance, and inflammation are precursors to the development of modifiable chronic diseases such as type 2 diabetes (T2D), cardiovascular disease, hypertension, and dyslipidemia (2). Approximately 40% of all adults in the United States are obese (3). Despite the widespread problem of obesity in all U.S. populations, the distribution of obesity and associated complications varies considerably by ethnicity, with African-Americans showing the highest prevalence (35.7%), followed by Hispanics (28.7%), and European Americans (23.7%) (4). Obese individuals have an excess of adipose tissue, often deposited in the visceral area (2). Adipose tissue is metabolically active, secreting biologically active cytokines (adipokines) capable of modulating immunological responses, and plays a role in metabolism via regulation of autocrine and paracrine signaling (5).
IL-1 is a proinflammatory cytokine chronically elevated in the presence of obesity (6). Low concentrations of IL-1 induce the production of proinsulin, thereby decreasing serum glucose levels, whereas high concentrations of IL-1 suppress the production of proinsulin and induce β-cell apoptosis (7). β-Cell apoptosis is postulated to be a major contributor to the development of T2D (8). The IL-1 receptor antagonist (IL-1RA) is more highly correlated with measures of obesity than other cytokines (5). IL-1RA does not directly elicit an antiinflammatory response but competitively binds to the IL-1 receptor on the cell surface, thereby inhibiting the inflammatory effects of IL-1 (7). IL-1RA levels are therefore an indirect measure of IL-1 activity (5). IL-1RA is positively correlated with body mass index (BMI) and insulin resistance (1) and plays a role in cholesterol excretion (5). In contrast to IL-1, IL-1RA appears to play a role in decreasing susceptibility to both type 1 and type 2 diabetes (9).
IL-6 is a proinflammatory cytokine secreted by numerous tissues, including skeletal muscle, white blood cells, hepatocytes, and adipose tissue (10). IL-6 levels are higher in obese compared with nonobese individuals (11). IL-6 levels are positively correlated with BMI (5) and percent fat mass (PFM) (12). Chronic exposure to elevated IL-6 levels is associated with the development of insulin resistance (1), the metabolic syndrome, and T2D (5). The proposed mechanism of this biological effect is reduction of glucose transporter-4 and insulin receptor substrate-1 expression in response to IL-6 exposure (13). IL-6 also plays an antiinflammatory role by reducing TNF-α and interferon-γ and stimulating IL-1RA (5).
IL-10 is an antiinflammatory cytokine that attenuates the inflammatory processes induced by TNF-α, IL-6, and IL-1 while up-regulating the release of IL-1RA (14). IL-10 is negatively correlated with BMI, PFM, and fasting glucose levels (12). Low levels of IL-10 are associated with both the metabolic syndrome and T2D. Although IL-10 is associated with insulin sensitivity (12), the mechanism of action is unknown.
We previously found associations among markers of inflammation (C-reactive protein, haptoglobin, and IL-6), BMI, and insulin resistance in African-Americans (15). Here, we investigated the relationships among IL-1RA, IL-6, IL-10, obesity, and insulin resistance in a large sample of African-Americans from the Washington, D.C., metropolitan area.
Subjects and Methods
The study consisted of 1025 nondiabetic (fasting blood glucose <100 mg/dl × 0.0555 = mmol/liter) unrelated African-Americans from the Howard University Family Study (HUFS). The HUFS is a genetic epidemiology study of African-American families and unrelated individuals enrolled in the Washington, D.C., metropolitan area (15). Compliance with ethical guidelines and standards was assured by the Howard University Internal Review Board. Recruitment and data collection methods have been detailed previously (15).
Weight was recorded on an electronic scale to the closest 0.1 kg with participants wearing light clothing. Height was measured to the closest 0.1 cm using a stadiometer. BMI was calculated by dividing weight by the square of height (in kilograms per square meter). Obesity was defined as BMI of at least 30 kg/m2. Waist circumference (WC) was measured to the nearest 0.1 cm from an anterior view using the narrower part of the trunk/upper body. Hip circumference (HC) was measured to the nearest 0.1 cm at the widest part of the buttocks or hip. The waist-to-hip ratio (WHR) was recorded as WC divided by HC. Total body fat mass was estimated using bioelectric impedance analysis using a 50-kHz single frequency battery-operated bioimpedance analyzer (model BIA 101Q; RJL Systems Inc., Clinton Township, MI). Using the measured resistance, impedance was calculated and used to determine total body water, fat-free mass, and fat mass using validated population-specific equations. PFM was calculated by dividing fat mass by weight and multiplying by 100.
Serum samples were obtained from collected blood samples from participants after an overnight fast of at least 8 h. IL-6, IL-1RA, and IL-10 levels were measured using Quantikine ELISA kits from R&D Systems (Minneapolis, MN). Glucose was measured in milligrams per deciliter using a COBAS INTEGRA 400 Plus analyzer with the Glucose HK Gen.3 test (Roche Diagnostics, Indianapolis, IN). Insulin was measured by electrochemiluminescence on the Elecsys 1010 immunoassay analyzer (Roche Diagnostics). The euglycemic clamp is the “gold standard” technique for quantifying insulin secretion and resistance (16) but is cost- and labor-prohibitive for a large-scale epidemiological study. We used the homeostasis model assessment of insulin resistance (HOMA-IR) equation to estimate insulin resistance because its values are highly correlated with values attained from euglycemic-hyperinsulinemic clamp measures (16). HOMA-IR scores were estimated using the following equation: HOMA-IR = fasting insulin (μU/ml) × fasting glucose (mg/dl) ÷ 405 (16).
All data were analyzed using R version 2.10.0 (17). Outliers were defined as data points greater than 3 sd values from the mean and were excluded. Due to non-normality, BMI, WC, HC, HOMA-IR, IL-1RA, IL-6, IL-10, and fasting insulin were log10-transformed. Categorical variables (sex and obesity) were described as percentages and evaluated by tests of proportions. Continuous variables (age, BMI, WC, HC, IL-6, IL-1RA, IL-10, PFM, and HOMA-IR) were expressed as means and sd values and were evaluated using Student's t test. Linear regression was used to assess the association between continuous outcome variables and continuous or discrete predictor variables. We tested models regressing: 1) IL on measures of obesity; 2) HOMA-IR on IL; 3) HOMA-IR on IL given measures of obesity; and 4) HOMA-IR on measures of obesity given IL. For each model tested, P values ≤ 0.05 were deemed to be significant, whereas P values between 0.05 and 0.1 were deemed to be marginally significant. Adjustment for multiple comparisons was not necessary because we were not interested in simultaneous inference. Due to bimodality, post hoc analyses of IL-1RA were conducted using Welch's two sample t test. The adjusted R2 was calculated as 1 − (1 − R2) , in which R2 is the multiple R2, N is the sample size, and k is the number of predictors in the model.
Results
Clinical characteristics
Clinical characteristics of the study participants (n = 1025) are shown in Table 1. The prevalence of obesity was 40%, and approximately 10.3% of the study participants were morbidly obese (BMI ≥ 40 kg/m2). Women tended to have higher serum IL-1RA, IL-6, and fasting insulin levels but lower levels of glucose and IL-10 compared with men (Table 1). IL-6 and IL-1RA were both associated with age and sex, whereas IL-10 was associated with sex but not age (data not shown). Histograms and scatter plots of the IL levels are illustrated in Supplemental Figs. 1 and 2 (published on The Endocrine Society's Journals Online web site at http://jcem.endojournals.org), respectively.
Table 1.
Clinical characteristics of African-Americans included in this study
| Variable | Males | Females | P value |
|---|---|---|---|
| n | 456 | 564 | |
| Age (yr) | 43.8 (11.0) | 42.7 (10.8) | 0.116 |
| BMI (kg/m2) | 27.2 (1.2) | 29.7 (1.3) | <0.001 |
| Obese (BMI ≥ 30 kg/m2) (%) | 29.5 | 48.3 | <0.001 |
| WC (cm) | 92.2 (1.2) | 92.0 (1.2) | 0.866 |
| HC (cm) | 103.9 (1.1) | 110.5 (1.2) | <0.001 |
| WHR | 0.89 (0.07) | 0.83 (0.07) | <0.001 |
| PFM (%) | 28.2 (9.3) | 40.7 (8.7) | <0.001 |
| Fasting glucose (mg/dl) | 86.6 (11.4) | 83.4 (10.0) | <0.001 |
| Fasting insulin (μU/ml) | 6.60 (2.65) | 7.89 (2.37) | 0.005 |
| HOMA-IR | 1.5 (2.6) | 1.7 (2.3) | 0.039 |
| IL-1RA (pg/ml) | 221.6 (2.5) | 261.4 (2.6) | 0.005 |
| IL-6 (pg/ml) | 1.2 (2.3) | 1.5 (2.2) | <0.001 |
| IL-10 (pg/ml) | 10.0 (1.3) | 9.6 (1.3) | 0.016 |
Data are expressed as mean (sd) or percentage.
Regression analysis
The associations between measures of obesity and each IL are displayed in Supplemental Table 1. The associations between HOMA-IR and IL are displayed in Table 2. In each table, the strongest associations include IL-6 and IL-1RA.
Table 2.
Association between HOMA-IR and IL adjusted for age and sex in a cohort of African-Americans
| ILa | β (se) | P value | R2 (adjusted R2) |
|---|---|---|---|
| IL-6 | 0.206 (0.039) | <0.001 | 0.038 (0.034) |
| IL-1RA | 0.187 (0.031) | <0.001 | 0.046 (0.043) |
| IL-10 | −0.167 (0.107) | 0.121 | 0.009 (0.006) |
| IL-1RA low | −0.062 (0.263) | 0.815 | 0.011 (−0.0058) |
| IL-1RA high | 0.580 (0.062) | <0.001 | 0.120 (0.117) |
Each model represents regression of HOMA-IR on the listed IL. IL-1RA < 100 (n = 183). IL-1RA > 100 (n = 835).
Clinical characteristics of participants with low vs. high IL-1RA levels
The distribution of IL-1RA was bimodal, with participants grouped into low (<100 pg/ml) or high (>100 pg/ml) circulating IL-1RA levels (Supplemental Fig. 2). Participants with high IL-1RA levels were not significantly different from participants with low IL-1RA levels with respect to age, sex, HC, PFM, or glucose levels (Supplemental Table 2). However, participants with high IL-1RA levels had significantly higher WC, WHR, IL-6, and IL-10 and marginally higher BMI and HOMA-IR (Supplemental Table 2).
There was no association between age or sex and low IL-1RA levels. Increased age and female sex were significantly associated with high IL-1RA levels (data not shown). High IL-1RA levels were associated with all measures of obesity (Supplemental Table 3). HOMA-IR was associated with IL-1RA in the group with high IL-1RA but not in the group with low IL-1RA (Table 2).
Likelihood ratio tests
We investigated whether IL were associated with HOMA-IR beyond the effects of obesity using the likelihood ratio test. We compared model fits of HOMA-IR regressed on age, sex, and a measure of obesity with and without an IL. Of the IL, only high IL-1RA resulted in improved model fit (Supplemental Table 4). We also investigated whether obesity was associated with HOMA-IR outside of its effects on IL. We compared model fits of HOMA-IR regressed on age, sex, and an IL with and without a measure of obesity. All measures of obesity investigated in this study improved model fit, with the exception of WHR among those with low IL-1RA levels (Supplemental Table 5).
Discussion
To our knowledge, this study is the first to provide evidence regarding associations between IL-1RA, IL-6, and IL-10 with obesity and insulin resistance in a large well-characterized sample of African-Americans. We demonstrated that IL-1RA and IL-6 were associated with both obesity and insulin resistance, whereas IL-10 was not associated with either obesity or insulin resistance. Adding IL-1RA (among those with high levels) improved model fit of HOMA-IR regressed on measures of obesity, suggesting that IL1-RA (but not IL-6) has an effect on insulin resistance beyond obesity.
The association of high IL-1RA levels with HOMA-IR is of interest given that adiposity-linked diabetes is often preceded by inhibition of the insulin receptor via inflammatory cytokines (18). Some investigators have postulated that an imbalance between IL-1 and IL-1RA may be responsible for the development of insulin resistance and T2D (7, 19). There is evidence that elevation of IL-1 without a sufficient inhibitory response by IL-1RA results in the development of insulin resistance and T2D (20). In our study, IL-1RA was the cytokine most strongly associated with obesity and insulin resistance.
This study is limited by its inability to establish causality due to its cross-sectional nature. A strength of this study is the evidence regarding IL and their relationship to obesity and insulin resistance in an ethnic population in the United States that is disproportionately burdened by obesity, diabetes, and insulin resistance.
Conclusion
Given the increasing incidence of obesity and diabetes globally, elucidation of the biological pathways by which adipokines mediate the development of insulin resistance is worthy of additional investigation. The high IL-1RA levels and obesity measures associated with HOMA-IR in this study and the heterogeneity among adipokines (proinflammatory, antiinflammatory, autocrine and/or paracrine functions) in vivo makes their investigation a rich area for future biochemical and genetic investigation.
Supplementary Material
Acknowledgments
The authors thank the participants of the Howard University Family Study for their participation in this study.
The Howard University Family Study was supported by National Institutes of Health Grants S06GM008016-320107 and S06GM008016-380111. Enrollment was carried out at the Howard University General Clinical Research Center and was supported by National Institutes of Health Grant 2M01RR010284. This research was supported in part by the Intramural Research Program of the Center for Research on Genomics and Global Health. The Center for Research on Genomics and Global Health is supported by the National Human Genome Research Institute, the National Institute of Diabetes and Digestive and Kidney Diseases, the Center for Information Technology, and the Office of the Director at the National Institutes of Health (Z01HG200362). The funders had no role in study design, data collection and analysis, the decision to publish, or preparation of the manuscript. The Intramural Research Program of the Center for Research on Genomics and Global Health was supported by the National Human Genome Research Institute, the National Institute of Diabetes and Digestive and Kidney Diseases, the Center for Information Technology, and the Office of the Director at the National Institutes of Health (Z01HG200362), and the National Human Genome Research Institute Intramural Health Disparities Postdoctoral Fellowship.
Author Contributions: B.A.C. wrote, researched literature, analyzed data, discussed, reviewed, and edited the manuscript. A.D. reviewed and edited the manuscript, designed lab procedures and generated lab data. H.H. generated lab data and reviewed the manuscript. J.Z. managed data and reviewed the manuscript. G.C. reviewed the manuscript. D.S. discussed, reviewed, and edited the manuscript. A.A. managed the original grant, collected data, discussed, edited, and reviewed the manuscript. C.N.R. wrote the original grant and edited and reviewed the manuscript. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official view of the National Institutes of Health.
Disclosure Summary: The authors have nothing to disclose.
Footnotes
- BMI
- Body mass index
- HC
- hip circumference
- HOMA-IR
- homeostasis model assessment of insulin resistance
- IL-1RA
- IL-1 receptor antagonist
- PFM
- percent fat mass
- WC
- waist circumference
- WHR
- waist-to-hip ratio.
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