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(Circulation. 2003;108:1822.)
© 2003 American Heart Association, Inc.

Clinical Investigation and Reports

Inflammation in the Prediabetic State Is Related to Increased Insulin Resistance Rather Than Decreased Insulin Secretion

Andreas Festa, MD; Anthony J.G. Hanley, PhD; Russell P. Tracy, PhD; Ralph D’Agostino, Jr, PhD; Steven M. Haffner, MD

From the Department of Medicine (A.F., S.M.H.), Division of Clinical Epidemiology, University of Texas Health Science Center at San Antonio, Tex; Eli Lilly & Company Area Medical Center (A.F.), Vienna, Austria; Department of Medicine (A.J.G.H.), Mount Sinai Hospital, University of Toronto, Ontario, Canada; Laboratory for Clinical Biochemistry Research (R.P.T.), Department of Pathology, University of Vermont College of Medicine, Burlington, Vt; and Department of Public Health Sciences (R.D.A.), Wake Forest University School of Medicine, Winston Salem, NC.

Correspondence to Steven M. Haffner, MD, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC 7873, San Antonio, TX 78229-3900. E-mail haffner{at}uthscsa.edu

Received February 12, 2003; de novo received June 3, 2003; revision received July 23, 2003; accepted July 23, 2003.

	Abstract

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Background— Elevated levels of proinflammatory proteins are predictive of both cardiovascular (CV) disease and type 2 diabetes. Previously, atherogenic changes in traditional CV risk factors in the prediabetic state were mainly seen in insulin-resistant subjects rather than in those with a predominant defect in insulin secretion.

Methods and Results— We studied in prediabetic individuals from the Insulin Resistance Atherosclerosis Study (IRAS) the relation of C-reactive protein (CRP), plasminogen activator inhibitor (PAI)-1, and fibrinogen to defects in insulin sensitivity (S_I) and first-phase insulin secretion, respectively, as assessed using a frequently sampled intravenous glucose tolerance test. One hundred forty-eight of 906 (16.3%) nondiabetic individuals developed diabetes after a mean follow-up of 5.2 years. Prediabetic individuals who were insulin resistant had higher levels of PAI-1 (mean [95% CI], 25.83 ng/mL [22.42 to 29.77] versus 16.31 ng/mL [12.56 to 21.18]; P=0.003) and CRP (mean [95% CI], 2.88 mg/L [2.33 to 3.56] versus 1.68 mg/L [1.13 to 2.49]; P=0.018) than insulin-sensitive individuals, but individuals with decreased acute insulin response tended to have lower rather than higher levels of inflammatory proteins compared with those with high insulin secretion. Prediabetic subjects who were predominantly insulin resistant had higher levels of inflammatory proteins compared with both prediabetic subjects with decreased insulin secretion as well as nonconverters. By contrast, prediabetic subjects with a predominant defect in first-phase insulin secretion had levels of inflammatory proteins indistinguishable from those in nonconverters.

Conclusions— We have shown an increased proinflammatory state in prediabetic individuals who are predominantly insulin resistant but not in those with a primary defect in ß-cell function. These results provide additional evidence that prediabetic subjects may be at an increased risk of heart disease, and this risk seems to be restricted to subjects with high insulin resistance.

Key Words: cardiovascular diseases • diabetes mellitus • epidemiology • inflammation

	Introduction

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Macrovascular disease remains an unresolved challenge in the treatment of patients with type 2 diabetes. In patients with newly diagnosed type 2 diabetes, improved glycemic control was more strongly associated with microvascular complications than with macrovascular disease.¹ One possible explanation for this finding, which has been substantiated by the results of other studies, is that the risk of coronary heart disease already exists before the onset of diabetes.² Cardiovascular (CV) risk factors are prevalent in the prediabetic state,^2–6 and most of these traditional risk factors, including obesity, hypertension, and dyslipidemia, constitute core features of the insulin-resistance syndrome.^7,8 Both increased insulin resistance and decreased insulin secretion predict the development of type 2 diabetes.^9–11 We have previously shown in the San Antonio Heart Study that atherogenic changes in CV risk factors in the prediabetic state are mainly seen in insulin-resistant subjects rather than in those with a predominant defect in insulin secretion.¹²

CV disease has been related to chronic, subclinical inflammation, as indicated by elevated circulating levels of proinflammatory proteins.¹³ Proinflammatory proteins have been related to insulin resistance^14–16 and glycemia^17,18 cross-sectionally. More recently, elevated levels of inflammatory proteins have also been related to incident diabetes in middle-aged populations,^19,20 an elderly population,²¹ healthy middle-aged women,²² young Pima Indians,²³ and women from the Mexico City Diabetes Study,²⁴ but the mechanisms underlying this association are still incompletely understood.

Therefore, in an attempt to additionally elucidate the role of chronic, subclinical inflammation for the development of type 2 diabetes, we studied prediabetic individuals in the Insulin Resistance Atherosclerosis Study (IRAS). We hypothesized that a proinflammatory state in prediabetic individuals might be characterized predominantly by increased insulin resistance rather than decreased insulin secretion and that the slightly higher glucose levels would not be a major determinant of subclinical inflammation.

	Methods

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The IRAS is a multicenter, epidemiological study aiming to explore relationships between insulin resistance, cardiovascular risk factors, and disease across different ethnic groups and varying states of glucose tolerance. A full description of the design and methods of the IRAS has been published previously.²⁵ The IRAS protocol was approved by local institutional review committees, and all subjects gave informed consent.

A total of 1625 individuals participated in the IRAS. This report includes data on 906 subjects who were nondiabetic at the baseline examination and in whom follow-up data were available. Subjects who developed diabetes during follow-up were defined as prediabetic, and those who remained nondiabetic were defined as nonconverters. The mean follow-up duration was 5.2 years (range, 4.5 to 6.6 years). Each of the 2 IRAS examinations required 2 visits. Patients were asked before each visit to fast for 12 hours, to abstain from heavy exercise and alcohol for 24 hours, and to refrain from smoking the morning of the examination. Smoking status was dichotomized into none and past or current using a standard questionnaire. Race and ethnicity were assessed by self-report.

Assessment of Glucose Tolerance and Insulin Sensitivity
A standard 75-g oral glucose tolerance test was performed, and glucose tolerance status was based on the World Health Organization criteria.²⁶ A frequently sampled intravenous glucose tolerance test²⁷ with minimal model analysis²⁸ was performed to assess insulin sensitivity. Two modifications of the original protocol were used. An injection of regular insulin, rather than tolbutamide, was used to ensure adequate plasma insulin levels for the accurate computation of insulin sensitivity across a broad range of glucose tolerance. In addition, the reduced sampling protocol (which required 12 rather than 30 plasma samples) was used because of the large number of subjects. Insulin sensitivity, expressed as the insulin sensitivity index (S_I), was calculated by mathematical modeling methods (MINMOD, version 3.0, 1994). Acute insulin response (AIR) was calculated as the mean increment in the plasma insulin concentration above basal in the first 8 minutes after the administration of glucose.

Measures of Body Fat and Body Composition
Height was recorded to the nearest 0.5 cm, and weight was measured to the nearest 0.1 kg. Body mass index was calculated as weight/height² (kg/m²) and was used as an estimate of overall adiposity. Girth measurements were estimated as the average of duplicate measures (taken to the nearest 0.5 cm using steel tape). Waist circumference was considered an estimate of visceral fat mass and measured on bare skin during midrespiration at the natural indentation between the 10th rib and the iliacal crest (minimum waist).

Laboratory Measurements
Glucose and insulin levels were measured using standard methods. C-reactive protein (CRP) was measured by in-house ultrasensitive competitive immunoassay (antibodies and antigens from Calbiochem, La Jolla, Calif) with an interassay coefficient of variation of 8.9%.²⁹ Fibrinogen was measured in citrated plasma with a modified clot-rate assay using the Diagnostica STAGO ST4 instrument, as described previously.³⁰ This was based on the original method of Clauss³¹ with a coefficient of variation of 3.0%. Plasminogen activator inhibitor (PAI)-1 was also measured in citrated plasma³² using a 2-site immunoassay that is sensitive to free PAI-1 but not to PAI-1 complexed with tissue plasminogen activator.³³ The citrate sample was centrifuged for a minimum of 10 minutes with 3000g (or a corresponding combination of time and centrifugal force) to make certain that there was no contamination from platelet PAI-1; the coefficient of variation was 14%. Samples for fibrinogen, PAI-1, and CRP were frozen and stored at -70°C at the centers not later than 90 minutes after blood drawing. Frozen samples were shipped on a monthly basis to the Laboratory for Clinical Biochemistry Research, University of Vermont (R.P.T.), where measurements were performed.

Statistical Analysis
All analyses were conducted using the Statistical Analysis System (SAS, Version 8.02, SAS Institute). Means and standard deviations or proportions were presented, and t tests and ² tests were used to assess univariate differences between continuous and categorical variables, respectively (Table 1). The distributions of insulin, PAI-1, and CRP were substantially skewed, and thus the natural logarithmic transformations of these variables were used in the analysis, with back-transformed results presented in Tables and Figures. Given that some subjects had S_I=0, we used log(S_I+1) as the transformation for the insulin sensitivity variable in multivariate analyses, with back-transformed results presented. In addition, we used the rank transformation of AIR to estimate probability values for this variable in multivariate analyses. Among prediabetic subjects, mean values of metabolic and inflammation variables were presented stratified by median values (below/above) of S_I and AIR, with the medians based on the overall nondiabetic population at baseline (Table 2, Figure 1). ANCOVA was used to test differences in metabolic and inflammation variables between those below and above the median after adjustment for covariates (Table 3). Four models were used, with adjustment for age, sex, clinical center, ethnicity, and smoking (demographic variables); demographic variables plus body mass index (BMI); demographic variables plus fasting glucose; and demographic variables plus AIR (in models comparing groups by median split of S_I) or S_I (in models comparing groups by median split of AIR). Finally, we calculated mean values of metabolic and inflammation variables (adjusted for age, sex, clinical center, ethnicity, and smoking) in prediabetic subjects stratified by whether they had predominantly high insulin resistance (low S_I/high AIR), predominantly low insulin secretion (high S_I/low AIR), a combined defect (low S_I/low AIR), or no defect (high S_I/high AIR) (Tables 4 and 5 , Figure 2). In each case, low and high were defined based on medians in the overall nondiabetic population at baseline. These values were also calculated within strata of BMI (low/high based on median split among prediabetic subjects), and interaction terms were included in the models to assess effect modification by BMI (Figure 3). Table 5 was done by ANCOVA. Probability less than 0.05 (2-sided) was considered statistically significant.

View this table: [in this window] [in a new window]   TABLE 1. Clinical Characteristics at Baseline According to Conversion Status at Follow-Up

View this table: [in this window] [in a new window]   TABLE 2. Mean Values (SE) of Outcome Variables (Unadjusted) in Prediabetic Individuals (n=148) Stratified by Median Values (Below/Above) of SI and AIR at Baseline, Respectively

View larger version (63K): [in this window] [in a new window]   Figure 1. Levels of inflammatory markers (unadjusted) in prediabetic subjects stratified by median values of SI (left) and AIR (right), respectively. A, Fibrinogen. B, PAI-1. C, CRP.

View this table: [in this window] [in a new window]   TABLE 3. Mean Values (SE or 95% CI for Back-Transformed Variables) of Inflammatory Markers in Prediabetic Individuals Stratified by Median Values (Below/Above) of SI and AIR at Baseline, Respectively

View this table: [in this window] [in a new window]   TABLE 4. Mean Values of Outcome Variables (Adjusted for Age, Sex, Clinical Center, Ethnicity, and Smoking) in Prediabetic Subjects Stratified by Whether They Had Predominantly High Insulin Resistance (Low Insulin Sensitivity or Low SI/High AIR), Predominantly Low Insulin Secretion (high SI/low AIR), a Combined Defect (low SI/low AIR), or No Defect (High SI/High AIR)

View this table: [in this window] [in a new window]   TABLE 5. Mean Values of Outcome Variables (Adjusted for Age, Sex, Clinical Center, Ethnicity, and Smoking) in Nonconverters Stratified by Whether They Had Predominantly High Insulin Resistance (Low SI/High AIR) or Predominantly Low Insulin Secretion (High SI/Low AIR)

View larger version (51K): [in this window] [in a new window]   Figure 2. Levels of inflammatory markers in prediabetic subjects who had predominantly high insulin resistance or predominantly low insulin secretion and in subjects who remained nondiabetic at follow-up (nonconverters). A, Fibrinogen (high resistance vs low secretion, P=0.11; high resistance vs nonconverters, P=0.03; low secretion vs nonconverters, P=0.8). B, PAI-1 (high resistance vs low secretion, P=0.0075; high resistance vs nonconverters, P<0.0001; low secretion vs nonconverters, P=0.5). C, CRP (high resistance vs low secretion, P=0.0055; high resistance vs nonconverters, P<0.0001; low secretion vs nonconverters, P=0.9).

View larger version (48K): [in this window] [in a new window]   Figure 3. Levels of inflammatory markers in prediabetic subjects who had predominantly high insulin resistance or predominantly low insulin secretion and in subjects who remained nondiabetic at follow-up (nonconverters) stratified by median levels of BMI (cut-off value, 27.30 kg/m2). A, Fibrinogen (low BMI: high resistance vs low secretion, P=0.3; high resistance vs nonconverters, P=0.07; low secretion vs nonconverters, P=0.3; high BMI: high resistance vs low secretion, P=0.3; high resistance vs nonconverters, P=0.5; low secretion vs nonconverters, P=0.2). B, PAI-1 (low BMI: high resistance vs low secretion, P=0.8; high resistance vs nonconverters, P=0.3; low secretion vs nonconverters, P=0.04; high BMI: high resistance vs low secretion, P=0.0009; high resistance vs non-converters, P<0.0001; low secretion vs nonconverters, P=0.2). C, CRP (low BMI: high resistance vs low secretion, P=0.06; high resistance vs nonconverters, P=0.0028; low secretion vs nonconverters, P=0.3; high BMI: high resistance vs low secretion, P=0.053; high resistance vs nonconverters, P=0.09; low secretion vs nonconverters, P=0.2).

	Results

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As has been shown in other populations,^2–6,9–12 prediabetic individuals were older and had higher BMI, waist circumference, fasting glucose, 2-hour glucose, fasting insulin, and levels of inflammatory proteins^19–23 than nonconverters. By contrast, S_I and AIR were lower, indicating increased insulin resistance and decreased first-phase insulin secretion (Table 1).

Prediabetic individuals who were insulin resistant (as defined by S_I below the median in the total nondiabetic population at baseline; 1.64x10^-4min^-1 · µU^-1 · mL^-1) had higher BMI, waist circumference, 2-hour glucose, fasting insulin, AIR (Table 2), and circulating levels of PAI-1 (mean [95% CI], 25.83 ng/mL [22.42 to 29.77] versus 16.31 ng/mL [12.56 to 21.18], P=0.003) and CRP (mean [95% CI], 2.88 mg/L [2.33 to 3.56] versus 1.68 mg/L [1.13 to 2.49], P=0.018) (Figures 1B and 1C) than prediabetic subjects with high insulin sensitivity (S_I above median). By contrast, prediabetic individuals with a low first-phase insulin secretion (AIR below the median; 374.41 pmol/L) had higher S_I, fasting, and 2-hour glucose levels and lower fasting insulin levels (Table 2), but levels of inflammatory proteins were not significantly different, showing a tendency toward lower (rather than higher) levels (Figure 1) compared with prediabetic subjects with a high first-phase insulin secretion (AIR above median).

Because body fat and fasting glycemia were significantly different in prediabetic subjects with low versus high S_I and in prediabetic subjects with low versus high AIR, respectively (Table 2), we adjusted for these 2 covariates in additional models comparing mean values of inflammatory proteins according to the insulin resistance and insulin secretion status, respectively. BMI attenuated the differences in PAI-1 and CRP in both the S_I as well as the AIR models (Table 3), and this BMI effect was somewhat more pronounced in the S_I models. However, stratified analyses (below and above median of BMI) and corresponding interaction analyses showed no significant interaction of BMI on the relation of S_I and AIR, respectively, to levels of the 3 inflammatory proteins (data not shown). In a similar model using waist instead of BMI as a covariate, comparable results were obtained (data not shown). Adjustment for fasting glucose did not affect the differences in PAI-1 and CRP levels between insulin-resistant and insulin-sensitive subjects, and the differences in PAI-1 and CRP levels were more pronounced (versus the demographically adjusted model) comparing subjects with low versus high insulin secretion (Table 3). Finally, adjusting for AIR or S_I in the corresponding S_I and AIR models showed that differences in levels of inflammatory markers (mainly PAI-1 and CRP) by S_I status remained unaffected after adjustment for AIR, whereas the differences in CRP and PAI-1 levels by AIR status were attenuated after adjusting for S_I. These results indicate that differences in PAI-1 and CRP in insulin-resistant versus insulin-sensitive individuals are partly explained by differences in body weight, unaffected by differences in glycemia, and unaffected by differences in first-phase insulin secretion (AIR). By contrast, differences in inflammatory markers in subjects according to the AIR status were largely explained by differences in S_I (AIR models adjusted for demographic covariates plus S_I).

Stratification of prediabetic subjects by insulin resistance (defined as below or above median of S_I) or insulin secretion (defined as below or above median of AIR) yielded 4 subgroups; 25.8% had predominantly high insulin resistance (low S_I and high AIR), 18.9% had predominantly decreased insulin secretion (high S_I and low AIR), 51.5% had a combined defect (low S_I and low AIR), and 3.8% had no defect (high S_I and high AIR). These prevalence rates are comparable to the San Antonio Heart Study using HOMA-IR to assess insulin resistance and the increment of insulin relative to the increment of glucose during an OGTT as a measure of insulin secretion (28.7%, 15.9%, 54.0%, and 1.5%, respectively).¹² As shown in Table 4, insulin-resistant prediabetic individuals (high resistance) presented with increased levels of circulating inflammatory proteins versus individuals with a predominant ß-cell defect (low secretion) (P=0.002 and P=0.008 for PAI-1 and CRP, respectively). After additionally adjusting for BMI, the differences in inflammatory proteins narrowed (data not shown). Subjects with a defect in insulin secretion had a somewhat more favorable (conventional) risk factor profile as indicated by lower BMI, waist, and fasting insulin levels versus higher fasting glucose levels (Table 4).

We also performed multiple linear regression analyses in which PAI-1 and CRP were dependent variables and BMI, S_I, and demographic variables were independent variables. BMI was a significant predictor of CRP (P=0.023), and S_I was a significant predictor of both PAI-1 (P=0.001) and CRP (P<0.001).

Furthermore, we compared prediabetic subjects who were predominantly insulin-resistant (high insulin resistance and high insulin secretion) and those with a predominant defect in first-phase insulin secretion (low insulin secretion and low insulin resistance), respectively, with subjects who remained nondiabetic during follow-up (nonconverters) (Figures 2 and 3). Overall, the resulting pattern was similar for all 3 markers, reaching statistical significance for PAI-1 and CRP (P=0.0075 and P=0.0055, respectively) and borderline significance for fibrinogen (P=0.11) (Figure 2). Prediabetic subjects who were predominantly insulin resistant (high resistance) had higher levels of inflammatory proteins compared with both prediabetic subjects with decreased insulin secretion (low secretion) and nonconverters. By contrast, prediabetic subjects with a predominant defect in first-phase insulin secretion (low secretion) had levels of inflammatory proteins indistinguishable from those in nonconverters. Stratified analyses by BMI yielded comparable patterns for all 3 inflammatory proteins (Figure 3), with the exception of PAI-1 in lean individuals. The common pattern was that in lean individuals (BMI below median), insulin-resistant subjects (high resistance) had the highest levels; subjects with low AIR (low secretion) had intermediate and nonconverters had the lowest levels of inflammatory proteins. In obese subjects, the high-resistance group had higher levels than the low-secretion group, but nonconverters tended to have higher levels than subjects with low insulin secretion. Despite this slightly different pattern in lean versus obese subjects, the respective interaction terms for BMI were not significant (P=0.4 for fibrinogen, P=0.08 for PAI-1, and P=0.17 for CRP, respectively). This indicates that high versus low BMI did not significantly modify the association of insulin resistance or AIR, respectively, with elevations in the levels of inflammatory markers.

Finally, analyses were also performed in the subjects who did not convert to diabetes. As shown in Table 5, differences in levels of inflammatory proteins between subjects with high insulin resistance versus those with low secretion were comparable to those seen in prediabetic subjects, only on a lower level regarding absolute values of these proteins. Note that among the subjects who did not convert to diabetes (Table 5), insulin resistance was associated with increased 2-hour glucose level (+17 mg/dL, P<0.001) (Table 5), whereas among the prediabetic subjects (Table 4), insulin resistance was not associated with higher 2-hour glucose levels (+3.7 mg/dL, P=0.6) but was associated with lower fasting glucose levels (-5.6 mg/dL, P=0.037) than in prediabetic subjects with a predominant defect in insulin secretion.

	Discussion

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Previous studies have indicated that high levels of CRP^19–22 and PAI-1²⁰ predict type 2 diabetes. In the present study, we have extended these previous observations by showing that CRP and PAI-1 levels were elevated in prediabetic individuals characterized by increased insulin resistance but not in prediabetic individuals presenting with decreased first-phase insulin secretion. This proinflammatory state in insulin-resistant prediabetic individuals was partly mediated by differences in body weight. (In Figure 3C, insulin resistance rather than obesity seems to be the major determinant of CRP levels.) Furthermore, insulin-resistant prediabetic subjects had higher levels of inflammatory proteins than subjects who stayed nondiabetic during follow-up (nonconverters). By contrast, prediabetic individuals with a predominant defect in insulin secretion did not present with signs of chronic subclinical inflammation compared with nonconverters. Thus, elevations in markers of inflammation are associated with insulin resistance rather than increases in glycemia or an insulin secretory defect. Similar relations of inflammatory proteins to insulin resistance and insulin secretion, respectively, were found in nonconverters, suggesting that our findings may be extended to the general nondiabetic population.

In this report, we focused on prediabetic subjects, because in the overall nondiabetic population (nonconverters), high insulin resistance is associated with higher glucose levels relative to the group with low insulin secretion (Table 5). This is important, because even small changes in glycemia may confer increased cardiovascular risk.³⁴ In contrast, in prediabetic subjects (all of whom by definition will develop diabetes), insulin resistance is not associated with higher glucose concentrations (Table 4). Therefore, by focusing on prediabetic subjects, we could better separate the effects of insulin resistance from the effects of hyperglycemia on inflammatory proteins. Also, characterization of the prediabetic state is important from a clinical point of view, mainly because of the potential to identify at an early stage those individuals who will eventually develop the disease and because cardiovascular risk is elevated in the prediabetic state. Recently, Hu et al³⁵ have shown that the risk of developing CV disease in prediabetic individuals is increased even before the onset of diabetes. Therefore, whereas interventions aimed at the prevention of diabetes will target all prediabetic individuals, prediabetic individuals with a high risk of developing cardiovascular disease emerge as particularly valuable targets for interventions aimed at preventing cardiovascular disease (in addition to diabetes). CV risk factors prevail not only in overall prediabetic individuals^2–6 but notably also in insulin-resistant prediabetic individuals.¹² In the present study, prediabetic subjects with insulin resistance had signs of chronic, subclinical inflammation and may therefore have increased risk of CHD; in contrast, prediabetic individuals whose major defect is insulin secretion did not have low-grade inflammation and thus had potentially lower rates of future CVD. It can therefore be assumed that prediabetic individuals who are predominantly insulin resistant will benefit more from preventive measures (in terms of absolute CV risk) than those with a primary ß-cell defect. In the present study, the relation of insulin resistance to chronic, subclinical inflammation in prediabetic individuals was unaffected by differences in glycemia and attenuated after adjusting for differences in body weight. This suggests that insulin resistance per se or increased body weight, rather than glycemia or impaired ß-cell function, contributes to the proinflammatory state in prediabetic individuals. Accordingly, the primary target of cardiovascular prevention in these individuals should be insulin resistance or obesity rather than glycemia or ß-cell dysfunction. Also, these findings support a strategy based on prevention of type 2 diabetes (and concomitantly cardiovascular disease) rather than just frequent screening for diabetes and intensive control of hyperglycemia. Thus, intervention (pharmacological or nonpharmacological) should target individuals at risk for diabetes before the onset of the disease instead of solely directing intervention toward glycemia. This needs yet to be shown in controlled clinical trials.

In the present study, insulin secretion was estimated using a frequently sampled intravenous glucose tolerance test, primarily reflecting first-phase insulin secretion. Therefore, we acknowledge that conclusions to be drawn from the data as presented will apply to first-phase secretion, not taking into account alterations in second-phase insulin secretion or defects in insulin secretion in response to an oral glucose load or regular meals.

Although subjects with subclinical inflammation and high PAI-1 concentrations are at high risk of developing diabetes, some subjects with low levels of CRP and PAI-1 can develop diabetes (much as some subjects with low CRP levels can develop coronary heart disease). Thus, CRP or PAI-1 should be considered statistical predictors of diabetes at the current time.

In summary, we have shown an increased proinflammatory state in prediabetic individuals who are predominantly insulin resistant but not in those with a primary defect in ß-cell function. These results provide additional evidence that prediabetic subjects may be at an increased risk of heart disease, and this risk seems to be restricted to subjects with high insulin resistance.

	Acknowledgments

 
This work was supported by the National Heart, Lung And Blood Institute (grants Hl47887, Hl47889, Hl47890, Hl47892, Hl47902, Hl55208, and R01 Hl58329) and the General Clinic Research Centers Program (grants NCRR GCRC, M01 RR431, and M01 RR01346).

	Footnotes

 
Andreas Festa is an employee of Eli Lilly and Co.

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