OBJECTIVE—Compared with Caucasians, obese African-American adolescents have a higher risk for type 2 diabetes. Subclinical inflammation and reduced glucagon-like peptide 1 (GLP-1) concentration are linked to the pathogenesis of the disease. We determined the relationship between insulin resistance, β-cell activity, and subclinical inflammation with GLP-1 concentrations and whether racial disparities in GLP-1 response were present in 49 obese adolescents (14 ± 3 years; 76% African American; 71% female).

RESEARCH DESIGN AND METHODS—Subjects underwent physical examination and an oral glucose tolerance test. We measured levels of high-sensitivity CRP (CRPhs), fibrinogen, glucose, GLP-1total, GLP-1active, and insulin. Insulin and glucose area under the curve (AUC), insulinogenic index (ΔI30/ΔG30), and composite insulin sensitivity index (CISI) were computed. Subjects were categorized by race and as inflammation positive (INF+) if CRPhs or fibrinogen were elevated.

RESULTS—No racial differences were seen in mean or relative BMI. Thirty-five percent of subjects had altered fasting or 2-h glucose levels (African American vs. Caucasian, NS), and 75% were INF+ (African American vs. Caucasian, P = 0.046). Glucose and insulin, CISI, and ΔI30/ΔG30 values were similar; African Americans had lower GLP-1total AUC (P = 0.01), GLP-1active at 15 min (P = 0.03), and GLP-1active AUC (P = 0.06) and higher fibrinogen (P = 0.01) and CRPhs (NS) compared with Caucasians.

CONCLUSIONS—African Americans exhibited lower GLP-1 concentrations and increased inflammatory response. Both mechanisms may act synergistically to enhance the predisposition of obese African Americans to type 2 diabetes. Our findings might be relevant to effective deployment of emerging GLP-1–based treatments across ethnicities.

Childhood obesity has reached epidemic proportions in the U.S. The prevalence of obesity and the rate of increase among African-American adolescents are twice as great as those among Caucasian adolescents. Type 2 diabetes in children also has increased alarmingly and is emerging as a critical health issue (1). Consequently, African-American adolescents have the highest incidence and prevalence of type 2 diabetes (2). Disparities in insulin dynamics, glucose production, or some combination of factors have been suggested to explain the increased risk for African Americans to develop type 2 diabetes (3,4). However, little is known about whether an interaction of the inflammatory response and insulin resistance could affect glucagon-like peptide-1 (GLP-1) responses (incretin responses) contribute to the increased risk for type 2 diabetes in obese African-American adolescents.

Elevated levels of high-sensitivity C-reactive protein (CRPhs) have been associated with increased risk for type 2 diabetes and cardiovascular disease (CVD) (5). Previous studies in children and adults have shown that there are racial differences in inflammatory markers (6). African-American individuals exhibited higher levels of CRPhs and fibrinogen at comparable levels of obesity and fitness. The role of GLP-1 as a major regulator of glucose homeostasis has been demonstrated (7). We have previously shown racial differences in enteroinsular axis (EIA) activity in obese adults. Compared with Caucasian subjects, African-American subjects exhibited higher basal and glucose-stimulated concentrations of total GLP-1 (mostly inactive), which persisted after 6 months of treatment with a long-acting somatostatin analog (8), suggesting that racial disparities could be present in the mechanisms that regulate the secretion, degradation, or clearance of GLP-1. In a biracial sample of obese adolescents, we sought to evaluate how indexes of insulin resistance, β-cell activity, and subclinical inflammation relate to active (GLP-1active) and total (GLP-1total) GLP-1 concentrations and whether racial disparities in GLP-1 response are present in obese adolescents.

All subjects gave written informed consent before eligibility confirmation. Forty-nine adolescents between the ages of 11 and 18 years, with a BMI ≥85th percentile for age and sex and not taking any medication, were recruited for this study. For the oral glucose tolerance test (OGTT), each subject consumed 1.0 g dextrose/kg body weight (Allegiance, McGaw Park, IL) up to a maximum of 75 g, and blood samples were obtained at 0, 15, 30, 60, 90, and 120 min (9). The following indexes from the OGTT were computed: area under the curve (AUC) (10) for insulin glucose, total GLP-1 (GLP-1total AUC), and active GLP-1 (GLP-1active AUC). We chose AUC to estimate as a single value both magnitude and duration of the response for insulin, glucose, GLP-1active, and GLP-1total to glucose load over time, and only absolute concentrations were used to report fasting insulin, glucose, and GLP-1 at baseline and at 15 min. The insulinogenic index (ΔI30/ΔG30) and composite insulin sensitivity index (CISI) = 10,000/square root [(fasting insulin × fasting blood glucose) × (mean insulin (0–120 min) × mean glucose (0–120 min)] were used as surrogate markers of β-cell function and insulin sensitivity, respectively (1). A subject’s glucose tolerance status was defined on the basis of the 2007 American Diabetes Association criteria (11). Subjects were classified as either having normal glucose tolerance (NGT) (fasting plasma glucose concentration <100 mg/dl and plasma postload glucose level <140 mg/dl) or impaired glucose metabolism (IGM). IGM included impaired fasting glucose (IFG) (fasting glucose level of 100–125 mg/dl), impaired glucose tolerance (IGT) (a 2-hour plasma glucose level ≥140 and <200 mg/dl), or diabetes (fasting glucose concentration >126 mg/dl or a 2-hour postload glucose level of ≥200 mg/dl).

Serum glucose was measured by the glucose oxidase method (12). Serum immunoreactive insulin (microunits per milliliter) from each OGTT sample was measured by a standard double-antibody radioimmunoassay (RIA) (Linco Research, St. Louis, MO). Samples for GLP-1 were collected into iced Vacutainer tubes (Becton Dickinson, U.K.) prepared with EDTA and dipeptidyl peptidase IV (DPP-IV) inhibitor (Linco Research) for preventing degradation of GLP-1active (GLP-17–37, GLP-17–36) into truncated, inactive GLP-1 (GLP-1degraded [GLP-19–37, GLP-19–36]). GLP-1total was determined using a specific COOH-terminal antibody RIA that binds to the COOH-terminal portion of GLP-1, both amidated and nonamidated forms (GLP1T-36HK; Linco Research). GLP-1active (GLP-17–37, GLP-17–36) was measured by enzyme-linked immunosorbent assay using a specific NH2-terminal region monoclonal antibody (EGLP-35K; Linco Research).

CRPhs levels were determined using latex immunonephelometry at the University of Miami Diabetes Institute. Fibrinogen levels were measured using modified thrombin time with photo-optical measurement of turbidity (13). CRPhs levels were considered elevated if values were ≥2 mg/l, and fibrinogen was considered increased if values were ≥350 mg/dl. The sample was stratified as subclinical inflammation positive (INF+) if either CRPhs or fibrinogen or both were elevated and as subclinical inflammation negative if neither was elevated.

Statistical data analyses were performed using the SAS system (SAS Institute, Cary, NC). Descriptive statistics are reported as means ± SEM for continuous data and frequencies and percentage for categorical data. AUC was calculated by the trapezoidal method (10). Subjects were stratified and analyzed by race, glucose tolerance status, and inflammatory markers. Statistical analyses consisted of χ2, Fisher’s exact test, Pearson correlation estimation, ANOVA, and ANCOVA (RBMI adjustment was done for CISI, ΔI30/ΔG30, fibrinogen, and CRPhs). For continuous variables adjusted for RBMI, least-squares means ± SEM are reported. P ≤ 0.05 was considered significant, and a trend toward significance was defined by P > 0.05 and ≤ 0.10.

Forty-nine subjects (71.4% female; 76% African-American) were included in the analysis. For the total sample, age was 14.1 ± 1.9 years, weight was 98.0 ± 22.7 kg, BMI was 36.0 ± 7.5 kg/m2, and RBMI was 183.7 ± 35.4%. Seventeen subjects (35%) had IGM, 28 (57%) had blood pressure higher than the 95th percentile, and 75% of the subjects were INF+. None of the clinical characteristics was statistically different between racial groups, except that African Americans had a trend toward a higher prevalence of INF+ (χ2 = 5.3, P = 0.046) and increased blood pressure (χ2 = 4.7, P = 0.09) (Table 1).

Mean values for indicators of insulin dynamics, inflammatory markers, and the EIA for the entire sample, stratified by race, are presented in Table 2. Racial groups exhibited similar values for CISI, ΔI30/ΔG30, fasting glucose and insulin, AUC for insulin, and AUC for glucose. African-American adolescents exhibited higher fibrinogen levels (P = 0.03) and a lower GLP-1 response compared with Caucasian adolescents, as suggested by lower GLP-1total AUC (P = 0.01), GLP-1active AUC (P = 0.06), and GLP-1active at 15 min (P = 0.03). Although fasting values for GLP-1total and GLP-1active were also lower among African-American adolescents, these differences were not statistically significant (Table 2 and Fig. 1). Both IGM and NGT groups had similar BMI, RBMI, age, ΔI30/ΔG30, insulin levels, CISI, CRPhs, fibrinogen, and fasting or stimulated GLP-1active. Only fasting glucose (IGM 103 ± 3.7 vs. NGT 89.3 ± 1.8 mg/dl, P = 0.002) and GLP-1total AUC (IGM 2,233 ± 278 vs. NGT 1,529 ± 159 mg/dl, P = 0.03) were significantly different. Subjects with a higher grade of inflammation (INF+) exhibited higher BMI (37.6 ± 1.2 vs. 31.1 ± 1.7 kg/m2, P = 0.008) and RBMI (191.1 ± 5.9 vs. 160.0 ± 7.4%, P = 0.007) and lower GLP-1active AUC (P = 0.046), fasting-GLP-1active (1.98 ± 1.86 vs. 10.3 ± 2.4 pmol/l, P = 0.004) and a trend toward a lower 15-min GLP-1active (4.2 ± 1.3 vs. 8.7 ± 2.4 pmol/l, P = 0.10). The difference in GLP-1total concentrations did not reached statistical significance.

Severity of overweight (BMI and RBMI) was equally associated with CISI (r = −0.36, P = 0.02 for both measures), fibrinogen (r = 0.47, P = 0.001 and r = 0.45, P = 0.0007), and CRPhs (r = 0.50, P = 0.0003 and r = 0.45, P = 0.0004). Indexes of the EIA, including fasting GLP-1active, were associated with fibrinogen (r = −0.31, P = 0.03), and GLP-1total AUC correlated with glucose AUC (r = 0.39, P = 0.02). There was a trend toward an association between fasting GLP-1active and CISI (r = 0.29, P = 0.07) and between GLP-1active AUC and both fibrinogen and CISI (r = −0.28, P = 0.07 and r = 0.31, P = 0.06).

Relationships among race, severity of obesity, insulin dynamics, and inflammation

Consistent with previous observations (14,15), this study demonstrates that independently of race, adolescents with obesity exhibit an increased risk for insulin resistance, IGM, and subclinical inflammation. Indexes of β-cell activity and insulin action were equally affected, and the prevalence of IGM was similar in both racial groups. For all subjects, severity of overweight appeared to be a major determinant in the development of the above conditions, as suggested by the inverse association between BMI and RBMI with insulin sensitivity and positive correlations with inflammation markers (fibrinogen and CRPhs). There is accumulating evidence supporting adiposity, insulin resistance, and inflammation as major risk factors associated with an increased risk for type 2 diabetes and CVD (16).

Our results agree with previous findings (5,15) and underscore the pathophysiological role of adiposity in regulating inflammation and insulin resistance (17) in adolescents (1719). There are well-documented ethnic disparities in insulin concentrations and actions between African Americans and Caucasians (20,21), which were less evident in our study population. There is a progressive deterioration of insulin sensitivity as severity of overweight progresses, but once children reach a certain overweight threshold (RBMI >150%), insulin sensitivity reaches a maximum deterioration of 55–70% (22). The mean RBMI in our subjects was 183.7 ± 35.4%; they probably had already experienced a maximal reduction in insulin sensitivity, given a mean CISI of 1.68 ± 0.1.

Insulin resistance/hyperinsulinemia could have an independent association with inflammatory marker levels (15). However, in adolescents and young adults, insulin resistance, as assessed by the homeostasis model assessment of insulin resistance, contributed minimally to the variance in subclinical inflammation. In agreement with these results, we found no association between CISI and markers of inflammation.

Racial disparities in inflammation markers

Inflammation has been shown to be a pathophysiological path common to several disorders, such as type 2 diabetes, hypertension, and CVD, each of which is known to contribute disproportionately to the burden of mortality and morbidity in African Americans (15,23). In this study, African-American adolescents exhibited higher concentrations and prevalence of inflammatory markers (Tables 1 and 2).

It has been suggested that genetic factors are likely to play a role in the inflammatory response in African Americans (24,25). Genes encoding critical proinflammatory cytokines, such as interleukin-1 and -6 and tumor necrosis factor-α, have important roles in inflammatory diseases (24). Also, African-American women are more likely to carry allelic variants known to upregulate proinflammatory cytokines. Odds ratios for African Americans versus Caucasians in genotypes upregulating proinflammatory interleukins ranged from 2.1 to 4.9. The proinflammatory cytokine interleukin-6 174 G/G genotype variant was 36.5 times more common among African Americans. Genotypes known to downregulate the anti-inflammatory interleukin-10 were elevated 3.5- and 2.8-fold in African Americans. Cytokine genotypes found to be more common in African-American women were consistently those that upregulate inflammation (24).

Racial disparities in GLP-1 response during OGTT

A novel finding was that at comparable levels of adiposity, glucose, and insulin secretion and sensitivity, African-American adolescents exhibited reduced concentrations of GLP-1total and GLP-1active during an OGTT compared with Caucasian adolescents (Table 2), suggesting that racial discrepancies in the mechanisms regulating the production or secretion of GLP-1 could already be present in obese adolescents. The role of GLP-1 (GLP-17–37, GLP-17–36) as a major regulator of glucose homeostasis has been demonstrated (7,26). GLP-1 is released from L-cells in the distal small bowel and colon, and it is the most potent incretin. In the pancreas, GLP-1 regulates somatostatin and glucagon secretion, proinsulin biosynthesis, apoptosis, and expansion of β-cell mass (7). The role of GLP-1 in the pathogenesis of type 2 diabetes and obesity has been demonstrated. We hypothesize that lower concentrations of GLP-1 could foster the higher risk of African-American adolescents to develop type 2 diabetes and their increased vulnerability to the effects of obesity on glucose metabolism. However, our results cannot explain whether these differences in GLP-1 concentrations are due to race-related inborn mechanisms or are a consequence of obesity itself or some related abnormalities.

It has been demonstrated that compared with leaner subjects, their obese counterparts have lower GLP-1total and GLP-1active concentrations and a lower GLP-1 response to exercise (27). Both abnormalities improved after gastric bypass (28) or significant weight loss (29). In our sample, racial differences in GLP-1 concentrations could not be fully explained by differences in adiposity, as the mean weight, BMI, and RBMI were comparable (Table 1).

AUC is a measure of total response and gives a good estimation of both magnitude and duration of the response to glucose load over time. However, AUC does not indicate which of these components (magnitude or duration) is more relevant. Total levels of GLP-1 (especially at later times during the OGTT) may reflect the interaction of different factors, including production, secretion, and clearance. Fasting and 15-min concentrations may more accurately reflect secretory response and should be evaluated in conjunction with AUC values. Early changes in GLP-1 concentrations may also be more relevant in regulating early insulin response to glucose load.

Another potential explanation for these racial discrepancies in GLP-1 concentrations may be insulin resistance. Rask et al. (27) reported that in nondiabetic men with wide-ranging insulin resistance, the GLP-1 response to a mixed meal is impaired, and it is related to the level of insulin resistance. The most insulin-resistant men had 56% lower GLP-1 levels at 15 min and 63% lower GLP-1 AUC values. Multiple linear regression analysis showed that insulin resistance, but not obesity, was an independent predictor of the decreased incretin response.

Hyperinsulinemia has been suggested as the mechanism by which insulin resistance downregulates the EIA (30,31). In support of this observation, we found that fasting GLP-1active and GLP-1active AUC exhibited a trend toward significant associations with CISI (r = 0.29, P = 0.07 and r = 0.31, P = 0.06, respectively). However, given that our sample African-American and Caucasian adolescents had similar insulin sensitivity, it is unlikely that the observed racial discrepancies in GLP-1 concentrations could be fully explained by these mechanisms. Interestingly, GLP-1total AUC correlated with glucose AUC (r = +0.39, P = 0.02) and subjects with IGM exhibited higher GLP-1total AUC (P = 0.03). These findings support the hypothesis that in obese adolescents with IGM the interaction of mechanisms affecting GLP-1 secretion and degradation could act synergistically to lead to the development of abnormal glucose metabolism.

Both obesity and insulin resistance have been found to be related to subclinical inflammation (15,32). In agreement with other investigators, we found that the levels of fibrinogen were higher in African Americans and that subjects with higher grades of inflammation exhibited higher BMI (P = 0.008), RBMI (P = 0.007), lower fasting GLP-1active, and lower GLP-1active AUC (P = 0.004 and 0.046, respectively). Furthermore, fasting GLP-1active negatively correlated with fibrinogen (r = −0.31, P = 0.03), and there was a trend toward a significant association between fibrinogen and GLP-1active AUC (r = −0.28, P = 0.07). This finding suggests that lower GLP-1active in African Americans could partially be explained by a racial predisposition to enhanced subclinical inflammation (15) and obesity, both of which could affect GLP-1 secretion or degradation.

We hypothesize that a potential mechanism by which obesity and inflammation could affect GLP-1 degradation is by enhancing the expression or activity of DPP-IV. DPP-IV is a type II integral membrane serine protease that is widely distributed throughout the body (33). Human DPP-IV cleaves NH2-terminal amino acids and inactivates the incretin hormones. It inactivates GLP-1 by >50% in ∼1–2 min and 50% of the gastric inhibitory polypeptide within 7 min. (33,34). The expression of DPP-IV is ontogenetically controlled and developmentally regulated during thymocyte maturation (33,35). It is known that DPP-IV is involved in a bimodal modulation of immune functions, mainly via expansion of T-cell activation but also by an inhibitory effect on corticosteroid release and chemokine inactivation. The net effect of DPP-IV activity could also explain the shift toward Th1 cytokine response (proinflammation) through degradation of the cytokines involved in the Th2-like response (anti-inflammatory) (33).

Some limitations of the current study preclude us from making conclusive inferences. First, our small sample increases the potential risk of underestimating the magnitude and statistical significance of racial disparities in enteroinsular activity. For instance, compared with African-American adolescents, Caucasian adolescents showed a 2.6 times higher GLP-1active AUC; however, this marked difference only reached marginal statistical significance (P = 0.06). Studies with larger samples of adolescents can help to reduce the chance of making type II errors. The use of BMI and RBMI as surrogate markers of adiposity and lack of information concerning exercise and dietary intake could represent potential confounders. There were also technical and reporting limitations that may affect the applicability of our results, including the lack of similar commercially available assays to assess active and inactive GLP-1 components. At present, GLP-1active (GLP-17–37, GLP-17–36) is measured by an enzyme-linked immunosorbent assay using a specific NH2-terminal region monoclonal antibody, whereas GLP-1total (degraded GLP-19–37, GLP-19–36) is determined using a specific COOH-terminal antibody RIA that binds to the COOH-terminal portion of GLP-1. This limitation in methodology may foster variability and may not permit a clear comparison to quantify secretion and degradation. Similarly, there are no commercially available methods to assess the expression and activity of DPP-IV. We believe that the use of statistical methods such as AUC help to overcome these limitations because AUC provides a better estimation of the discrepancy in the total response to glucose. Likewise, early changes in the response (during the first 15 min) may be a more accurate indicator of secretion capacity than levels at later times, which may be more affected by either kidney or liver extraction.

Our findings might have relevance for the potential deployment of emerging GLP-1–based antidiabetic agents across ethnicities. Further studies will be needed to address the implications of disparities in GLP-1 levels in responses to antidiabetic agents in subjects from different racial/ethnic backgrounds.

In summary, obese adolescents have a profound deterioration of insulin sensitivity and a higher prevalence of IGM and subclinical inflammation. Severity of overweight seems to be a major determinant in the development of such conditions. At comparable levels of overweight and insulin resistance, obese African-American adolescents exhibit higher concentrations and prevalence of inflammatory markers and lower concentrations of GLP-1active and GLP-1total than their Caucasian peers. We hypothesize that these disparities may act in concert to foster the deterioration of glucose homeostasis in obese African-American adolescents and that these findings might be relevant to effective deployment of emerging GLP-1–based antidiabetic agents across ethnicities.

Figure 1—

Basal and stimulated concentrations of GLP-1active (A) and GLP-1total (B) during the OGTT (75-g glucose load during the 2-h test) in obese adolescent African Americans (○) and Caucasians (□). For GLP-1active AUC P = 0.06, and for GLP-1total AUC P = 0.01.

Figure 1—

Basal and stimulated concentrations of GLP-1active (A) and GLP-1total (B) during the OGTT (75-g glucose load during the 2-h test) in obese adolescent African Americans (○) and Caucasians (□). For GLP-1active AUC P = 0.06, and for GLP-1total AUC P = 0.01.

Close modal
Table 1—

Demographics and clinical characteristics of African-American and Caucasian study subjects

African AmericanCaucasianP value*
n 37 12  
Age (years) 14.1 ± 0.3 14.0 ± 0.7 0.75 
Female sex (%) 78% 50% 0.08 
Weight (kg) 100.0 ± 3.4 91.6 ± 8.1 0.27 
BMI (kg/m237.0 ± 1.2 33.2 ± 2.1 0.88 
RBMI (%) 188.1 ± 5.8 170.3 ± 9.5 0.16 
Systolic BP (mmHg) 126.5 ± 1.9 119.3 ± 4.3 0.17 
Diastolic BP (mmHg) 68.7 ± 1.1 65.2 ± 2.0 0.10 
Abnormal BP 24 (65) 4 (33) 0.09 
IGM 15 (42) 2 (17) 0.20 
Inflammation 30 (83) 6 (50) 0.05 
African AmericanCaucasianP value*
n 37 12  
Age (years) 14.1 ± 0.3 14.0 ± 0.7 0.75 
Female sex (%) 78% 50% 0.08 
Weight (kg) 100.0 ± 3.4 91.6 ± 8.1 0.27 
BMI (kg/m237.0 ± 1.2 33.2 ± 2.1 0.88 
RBMI (%) 188.1 ± 5.8 170.3 ± 9.5 0.16 
Systolic BP (mmHg) 126.5 ± 1.9 119.3 ± 4.3 0.17 
Diastolic BP (mmHg) 68.7 ± 1.1 65.2 ± 2.0 0.10 
Abnormal BP 24 (65) 4 (33) 0.09 
IGM 15 (42) 2 (17) 0.20 
Inflammation 30 (83) 6 (50) 0.05 

Data are least-squares means ± SEM or n (%). Analyses included ANOVA, ANCOVA, and Fisher’s exact test.

*

P values < 0.05 were significant, and values ≤ 0.10 were considered as a trend.

Table 2—

Insulin indices, inflammatory markers, and EIA measures by race

VariableTotal sampleAfrican AmericanCaucasianP value
n 49 37 12  
Fasting glucose (mg/dl) 93.7 ± 1.7 93.9 ± 2.3 93.3 ± 1.5 0.84* 
Glucose AUC 14,503 ± 373 14,434 ± 503 14,681 ± 371 0.80* 
Fasting insulin (μU/ml) 37.2 ± 2.6 37.9 ± 3.0 35.3 ± 5.2 0.60* 
Insulin AUC 22,493 ± 2,932 23,160 ± 3,775 20,736 ± 4,033 0.70* 
ΔI30/ΔG30 5.9 ± 0.8 6.43 ± 0.98 4.75 ± 0.96 0.50 
CISI 1.68 ± 0.15 1.54 ± 0.14 2.03 ± 0.43 0.30 
CRPhs (mg/dl) 3.2 ± 0.6 3.52 ± 0.77 2.34 ± 0.77 0.90 
Fibrinogen (mg/dl) 391 ± 10.2 407.8 ± 10.5 343.2 ± 21.4 0.01 
Fasting GLP-1total (pmol/l) 13.0 ± 1.0 12.75 ± 1.14 13.75 ± 2.5 0.70* 
GLP-1total at 15 min (pmol/l) 19.8 ± 1.5 18.5 ± 1.7 23.5 ± 3.0 0.15* 
GLP-1total AUC 1526 ± 128 1333 ± 108 2034 ± 333 0.01* 
Fasting GLP-1active (pmol/l) 4.1 ± 1.2 3.31 ± 1.14 6.67 ± 3.84 0.30* 
GLP-1active at 15 min (pmol/l) 5.3 ± 1.2 3.75 ± 0.63 9.5 ± 4.5 0.03* 
GLP-1active AUC 538 ± 142 374 ± 55.9 972 ± 490 0.06* 
VariableTotal sampleAfrican AmericanCaucasianP value
n 49 37 12  
Fasting glucose (mg/dl) 93.7 ± 1.7 93.9 ± 2.3 93.3 ± 1.5 0.84* 
Glucose AUC 14,503 ± 373 14,434 ± 503 14,681 ± 371 0.80* 
Fasting insulin (μU/ml) 37.2 ± 2.6 37.9 ± 3.0 35.3 ± 5.2 0.60* 
Insulin AUC 22,493 ± 2,932 23,160 ± 3,775 20,736 ± 4,033 0.70* 
ΔI30/ΔG30 5.9 ± 0.8 6.43 ± 0.98 4.75 ± 0.96 0.50 
CISI 1.68 ± 0.15 1.54 ± 0.14 2.03 ± 0.43 0.30 
CRPhs (mg/dl) 3.2 ± 0.6 3.52 ± 0.77 2.34 ± 0.77 0.90 
Fibrinogen (mg/dl) 391 ± 10.2 407.8 ± 10.5 343.2 ± 21.4 0.01 
Fasting GLP-1total (pmol/l) 13.0 ± 1.0 12.75 ± 1.14 13.75 ± 2.5 0.70* 
GLP-1total at 15 min (pmol/l) 19.8 ± 1.5 18.5 ± 1.7 23.5 ± 3.0 0.15* 
GLP-1total AUC 1526 ± 128 1333 ± 108 2034 ± 333 0.01* 
Fasting GLP-1active (pmol/l) 4.1 ± 1.2 3.31 ± 1.14 6.67 ± 3.84 0.30* 
GLP-1active at 15 min (pmol/l) 5.3 ± 1.2 3.75 ± 0.63 9.5 ± 4.5 0.03* 
GLP-1active AUC 538 ± 142 374 ± 55.9 972 ± 490 0.06* 

Data are means ± SEM. Mean values for CISI, ΔI30/ΔG30, fibrinogen, and CRPhs were adjusted by RBMI from ANCOVA and are least-square means.

*

P values are from Student’s t test except for CISI, ΔI30/ΔG30, fibrinogen, and CRPhs, which are from ANCOVA. P values < 0.05 were significant and values ≤ 0.1 were considered as a trend.

This study was supported by funding from the National Center for Research Resources (Grants RR0207887 and RR-00211), components of the National Institutes of Health (NIH), the Children’s Foundation Research Center, and the University of Tennessee General Clinical Research Center(UT-GCRC).

The authors thank Drs. Donna Hathaway, George Burghen, Frances Tylavsky, and Astrid Velasquez for their teaching, guidance, and support; the nurses at the Lifestyle Clinic and the UT-GCRC for their assistance in the care and evaluation of these subjects; and Andrea Patters for her editorial assistance.

1.
Velasquez-Mieyer PA, Perez-Faustillini S, Cowan PA: Identifying children at risk for obesity, type 2 diabetes, and cardiovascular disease.
Diabet Spectr
18
:
213
–220,
2005
2.
Dagogo-Jack S: Ethnic disparities in type 2 diabetes: pathophysiology and implications for prevention and management.
J Natl Med Assoc
95
:
774
, 779–789,
2003
3.
Gower BA, Granger WM, Franklin F, Shewchuk RM, Goran MI: Contribution of insulin secretion and clearance to glucose-induced insulin concentration in African-American and Caucasian children.
J Clin Endocrinol Metab
87
:
2218
–2224,
2002
4.
Osei K, Schuster DP: Ethnic differences in secretion, sensitivity, and hepatic extraction of insulin in black and white Americans.
Diabet Med
11
:
755
–762,
1994
5.
Haffner SM: The metabolic syndrome: inflammation, diabetes mellitus, and cardiovascular disease.
Am J Cardiol
97
:
3A
–11A,
2006
6.
Kalra L, Rambaran C, Chowienczyk P, Goss D, Hambleton I, Ritter J, Shah A, Wilks R, Forrester T: Ethnic differences in arterial responses and inflammatory markers in Afro-Caribbean and Caucasian subjects.
Arterioscler Thromb Vasc Biol
25
:
2362
–2367,
2005
7.
Drucker DJ: Enhancing incretin action for the treatment of type 2 diabetes.
Diabetes Care
26
:
2929
–2940,
2003
8.
Velasquez-Mieyer PA, Cowan PA, Umpierrez GE, Lustig RH, Cashion AK, Burghen GA: Racial differences in glucagon-like peptide-1 (GLP-1) concentrations and insulin dynamics during oral glucose tolerance test in obese subjects.
Int J Obes Relat Metab Disord
27
:
1359
–1364,
2003
9.
Stumvoll M, Mitrakou A, Pimenta W, Jenssen T, Yki-Jarvinen H, Van Haeften T, Renn W, Gerich J: Use of the oral glucose tolerance test to assess insulin release and insulin sensitivity.
Diabetes Care
23
:
295
–301,
2000
10.
Tallarida RJ, Murray RB:
Manual of Pharmacologic Calculations with Computer Programs
. New York, Springer-Verlag,
1986
, p.
77
–81
11.
American Diabetes Association: Diagnosis and classification of diabetes mellitus.
Diabetes Care
30
:
S42
–47S,
2007
12.
Kadish AH, Little RH, Sternberg JC: A new and rapid method for the determination of glucose by measurement of rate of oxygen consumption.
Clin Chem
14
:
116
–119,
1968
13.
LabCorp:
Directory of Services and Interpretive Guide
. Burlington, NC, LabCorp,
2001
14.
Sinaiko AR, Steinberger J, Moran A, Prineas RJ, Vessby B, Basu S, Tracy R, Jacobs DR Jr: Relation of body mass index and insulin resistance to cardiovascular risk factors, inflammatory factors, and oxidative stress during adolescence.
Circulation
111
:
1985
–1991,
2005
15.
Patel DA, Srinivasan SR, Xu JH, Li S, Chen W, Berenson GS: Distribution and metabolic syndrome correlates of plasma C-reactive protein in biracial (black-white) younger adults: the Bogalusa Heart Study.
Metabolism
55
:
699
–705,
2006
16.
Hanley AJ, Festa A, D’Agostino RB Jr, Wagenknecht LE, Savage PJ, Tracy RP, Saad MF, Haffner SM: Metabolic and inflammation variable clusters and prediction of type 2 diabetes: factor analysis using directly measured insulin sensitivity.
Diabetes
53
:
1773
–1781,
2004
17.
Xu H, Barnes GT, Yang Q, Tan G, Yang D, Chou CJ, Sole J, Nichols A, Ross JS, Tartaglia LA, Chen H: Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance.
J Clin Invest
112
:
1821
–1830,
2003
18.
Korner A, Kratzsch J, Gausche R, Schaab M, Erbs S, Kiess W: New predictors of the metabolic syndrome in children—role of adipocytokines.
Pediatr Res
2007
19.
Kershaw EE, Flier JS: Adipose tissue as an endocrine organ.
J Clin Endocrinol Metab
89
:
2548
–2556,
2004
20.
Ku CY, Gower BA, Hunter GR, Goran MI: Racial differences in insulin secretion and sensitivity in prepubertal children: role of physical fitness and physical activity.
Obes Res
8
:
506
–515,
2000
21.
Uwaifo GI, Nguyen TT, Keil MF, Russell DL, Nicholson JC, Bonat SH, McDuffie JR, Yanovski JA: Differences in insulin secretion and sensitivity of Caucasian and African American prepubertal children.
J Pediatr
140
:
673
–680,
2002
22.
Velasquez-Mieyer PA, Cowan PA, Perez-Faustillini S, Markee J, Burghen GA: Predicting impaired glucose tolerance in severely obese adolescents. In
Proceedings of the International Congress on Endocrinology
,
2004
, p.
1433
–1437
23.
Geffken DF, Cushman M, Burke GL, Polak JF, Sakkinen PA, Tracy RP: Association between physical activity and markers of inflammation in a healthy elderly population.
Am J Epidemiol
153
:
242
–250,
2001
24.
Wessel J, Moratorio G, Rao F, Mahata M, Zhang L, Greene W, Rana BK, Kennedy BP, Khandrika S, Huang P, Lillie EO, Shih PA, Smith DW, Wen G, Hamilton BA, Ziegler MG, Witztum JL, Schork NJ, Schmid-Schonbein GW, O’Connor DT: C-reactive protein, an ‘intermediate phenotype’ for inflammation: human twin studies reveal heritability, association with blood pressure and the metabolic syndrome, and the influence of common polymorphism at catecholaminergic/β-adrenergic pathway loci.
J Hypertens
25
:
329
–343,
2007
25.
Lange LA, Burdon K, Langefeld CD, Liu Y, Beck SR, Rich SS, Freedman BI, Brosnihan KB, Herrington DM, Wagenknecht LE, Bowden DW: Heritability and expression of C-reactive protein in type 2 diabetes in the Diabetes Heart Study.
Ann Hum Genet
70
:
717
–725,
2006
26.
Perfetti R, Zhou J, Doyle ME, Egan JM: Glucagon-like peptide-1 induces cell proliferation and pancreatic-duodenum homeobox-1 expression and increases endocrine cell mass in the pancreas of old, glucose-intolerant rats.
Endocrinology
141
:
4600
–4605,
2000
27.
Rask E, Olsson T, Soderberg S, Johnson O, Seckl J, Holst JJ, Ahren B: Impaired incretin response after a mixed meal is associated with insulin resistance in nondiabetic men.
Diabetes Care
24
:
1640
–1645,
2001
28.
Laferrere B, Heshka S, Wang K, Khan Y, McGinty J, Teixeira J, Hart AB, Olivan B: Incretin levels and effect are markedly enhanced one month after Roux-en-Y gastric bypass surgery in obese patients with type 2 diabetes.
Diabetes Care
30
:
1709
–1716,
2007
29.
Adam TC, Lejeune MP, Westerterp-Plantenga MS: Nutrient-stimulated glucagon-like peptide 1 release after body-weight loss and weight maintenance in human subjects.
Br J Nutr
95
:
160
–167,
2006
30.
Bryer-Ash M, Cheung A, Pederson RA: Feedback regulation of glucose-dependent insulinotropic polypeptide (GIP) secretion by insulin in conscious rats.
Regul Pept
51
:
101
–109,
1994
31.
Sirinek KR, Pace WG, Crockett SE, O’Dorisio TM, Mazzaferri EL, Cataland S: Insulin-induced attenuation of glucose-stimulated gastric inhibitory polypeptide secretion.
Am J Surg
135
:
151
–155,
1978
32.
Steinberg GR: Inflammation in obesity is the common link between defects in fatty acid metabolism and insulin resistance.
Cell Cycle
6
:
888
–894,
2007
33.
Mentlein R: Dipeptidyl-peptidase IV (CD26)—role in the inactivation of regulatory peptides.
Regul Pept
85
:
9
–24,
1999
34.
Ahren B, Hughes TE: Inhibition of dipeptidyl peptidase-4 augments insulin secretion in response to exogenously administered glucagon-like peptide-1, glucose-dependent insulinotropic polypeptide, pituitary adenylate cyclase-activating polypeptide, and gastrin-releasing peptide in mice.
Endocrinology
146
:
2055
–2059,
2005
35.
Ruiz P, Zacharievich N, Hao L, Viciana AL, Shenkin M: Human thymocyte dipeptidyl peptidase IV (CD26) activity is altered with stage of ontogeny.
Clin Immunol Immunopathol
88
:
156
–168,
1998

Published ahead of print at http://care.diabetesjournals.org on 9 January 2008. DOI: 10.2337/dc07-1525.

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