Comparison between surrogate indexes of insulin sensitivity and resistance and hyperinsulinemic euglycemic clamp estimates in mice

Insulin resistance contributes to the pathophysiology of diabetes, obesity, and their cardiovascular complications. Mouse models of these human diseases are useful for gaining insight into pathophysiological mechanisms. The reference standard for measuring insulin sensitivity in both humans and animals is the euglycemic glucose clamp. Many studies have compared surrogate indexes of insulin sensitivity and resistance with glucose clamp estimates in humans. However, regulation of metabolic physiology in humans and rodents differs and comparisons between surrogate indexes and the glucose clamp have not been directly evaluated in rodents previously. Therefore, in the present study, we compared glucose clamp-derived measures of insulin sensitivity (GIR and SI(Clamp)) with surrogate indexes, including quantitative insulin-sensitivity check index (QUICKI), homeostasis model assessment (HOMA), 1/HOMA, log(HOMA), and 1/fasting insulin, using data from 87 mice with a wide range of insulin sensitivities. We evaluated simple linear correlations and performed calibration model analyses to evaluate the predictive accuracy of each surrogate. All surrogate indexes tested were modestly correlated with both GIR and SI(Clamp). However, a stronger correlation between body weight per se and both GIR and SI(Clamp) was noted. Calibration analyses of surrogate indexes adjusted for body weight demonstrated improved predictive accuracy for GIR [e.g., R = 0.68, for QUICKI and log(HOMA)]. We conclude that linear correlations of surrogate indexes with clamp data and predictive accuracy of surrogate indexes in mice are not as substantial as in humans. This may reflect intrinsic differences between human and rodent physiology as well as increased technical difficulties in performing glucose clamps in mice.     

Validation of simple indexes to assess insulin sensitivity during pregnancy in Wistar and Sprague-Dawley rats

Insulin resistance plays a role in the pathogenesis of diabetes, including gestational diabetes. The glucose clamp is considered the gold standard for determining in vivo insulin sensitivity, both in human and in animal models. However, the clamp is laborious, time consuming and, in animals, requires anesthesia and collection of multiple blood samples. In human studies, a number of simple indexes, derived from fasting glucose and insulin levels, have been obtained and validated against the glucose clamp. However, these indexes have not been validated in rats and their accuracy in predicting altered insulin sensitivity remains to be established. In the present study, we have evaluated whether indirect estimates based on fasting glucose and insulin levels are valid predictors of insulin sensitivity in nonpregnant and 20-day-pregnant Wistar and Sprague-Dawley rats. We have analyzed the homeostasis model assessment of insulin resistance (HOMA-IR), the quantitative insulin sensitivity check index (QUICKI), and the fasting glucose-to-insulin ratio (FGIR) by comparing them with the insulin sensitivity (SI(Clamp)) values obtained during the hyperinsulinemic-isoglycemic clamp. We have performed a calibration analysis to evaluate the ability of these indexes to accurately predict insulin sensitivity as determined by the reference glucose clamp. Finally, to assess the reliability of these indexes for the identification of animals with impaired insulin sensitivity, performance of the indexes was analyzed by receiver operating characteristic (ROC) curves in Wistar and Sprague-Dawley rats. We found that HOMA-IR, QUICKI, and FGIR correlated significantly with SI(Clamp), exhibited good sensitivity and specificity, accurately predicted SI(Clamp), and yielded lower insulin sensitivity in pregnant than in nonpregnant rats. Together, our data demonstrate that these indexes provide an easy and accurate measure of insulin sensitivity during pregnancy in the rat.     

Simple fasting methods to assess insulin sensitivity in childhood

The 'gold standard' techniques used to measure insulin sensitivity in children are the hyperinsulinaemic-euglycaemic clamp and Bergman's minimal model. Although precise, these techniques are complex, invasive and time consuming. Alternative indirect measures of insulin sensitivity have been developed that utilize fasting glucose and insulin data in algorithms or computer programs. These methods include homeostatic model assessment (HOMA), the quantitative insulin sensitivity check index (QUICKI) and the glucose to insulin ratio (G:I). Each of these three fasting techniques has been developed and validated in adults, with little or no validation in children. Increasingly, HOMA and QUICKI are being used in childhood studies to assess insulin sensitivity. In a group of 79 pre-pubertal children, we found that the correlation between the minimal model and RHOMA (r = -0.4) was no better than that between the minimal model and fasting insulin (r = 0.4), with an even weaker correlation between the minimal model and QUICKI (r = 0.2). In addition, neither HOMA nor QUICKI were able to detect a reduction in insulin sensitivity with obesity or during growth hormone therapy, unlike the minimal model. In children with normal glucose levels, neither HOMA nor QUICKI was superior to fasting insulin. Validation of the derivation formulae for these methods in children is needed before they are more widely used. The potential benefits of these simple fasting techniques is that they are useful in large field studies. However, if the study groups are small or longitudinal changes in insulin sensitivity are sought, more precise techniques such as the clamp or minimal model should be used.     

Fatness, fitness, and insulin sensitivity among 7- to 9-year-old children

Objective: The purpose of this study was to examine the relationships among fatness and aerobic fitness on indices of insulin resistance and sensitivity in children. Research Design and Methods: A total of 375 children (193 girls and 182 boys) 7 to 9 years of age were categorized by weight as normal‐weight, overweight, or obese and by aerobic fitness based on a submaximal physical working capacity test (PWC). Fasting blood glucose (GLU) and insulin (INS) were used to calculate various indices of insulin sensitivity (GLU/INS), the homeostasis model assessment (HOMA), and the quantitative insulin sensitivity check index (QUICKI). Surrogate measures of pancreatic β cell function included the insulinogenic index (INS/GLU) and the HOMA estimate of pancreatic β‐cell function (HOMA %B). Results: Insulin sensitivity and secretion variables were significantly different between the normal‐weight children and the overweight and obese subjects. Fasting insulin (FI), HOMA, QUICKI, and INS/GLU were significantly different between the overweight and obese subjects. Likewise, the high fitness group possessed a better insulin sensitivity profile. In general, the normal‐weight–high fit group possessed the best insulin sensitivity profile and the obese‐unfit group possessed the worst insulin sensitivity profile. Several significant differences existed among the six fat‐fit groups. Of particular note are the differences within BMI groups by fitness level and the comparison of values between the normal‐weight–unfit subjects and the overweight and obese subjects with high fitness. Conclusions: The results indicate that aerobic fitness attenuates the difference in insulin sensitivity within BMI categories, thus emphasizing the role of fitness even among overweight and obese children.     

Current approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage

Insulin resistance contributes to the pathophysiology of diabetes and is a hallmark of obesity, metabolic syndrome, and many cardiovascular diseases. Therefore, quantifying insulin sensitivity/resistance in humans and animal models is of great importance for epidemiological studies, clinical and basic science investigations, and eventual use in clinical practice. Direct and indirect methods of varying complexity are currently employed for these purposes. Some methods rely on steady-state analysis of glucose and insulin, whereas others rely on dynamic testing. Each of these methods has distinct advantages and limitations. Thus, optimal choice and employment of a specific method depends on the nature of the studies being performed. Established direct methods for measuring insulin sensitivity in vivo are relatively complex. The hyperinsulinemic euglycemic glucose clamp and the insulin suppression test directly assess insulin-mediated glucose utilization under steady-state conditions that are both labor and time intensive. A slightly less complex indirect method relies on minimal model analysis of a frequently sampled intravenous glucose tolerance test. Finally, simple surrogate indexes for insulin sensitivity/resistance are available (e.g., QUICKI, HOMA, 1/insulin, Matusda index) that are derived from blood insulin and glucose concentrations under fasting conditions (steady state) or after an oral glucose load (dynamic). In particular, the quantitative insulin sensitivity check index (QUICKI) has been validated extensively against the reference standard glucose clamp method. QUICKI is a simple, robust, accurate, reproducible method that appropriately predicts changes in insulin sensitivity after therapeutic interventions as well as the onset of diabetes. In this Frontiers article, we highlight merits, limitations, and appropriate use of current in vivo measures of insulin sensitivity/resistance.     

The Association of the Triglyceride-to-HDL Cholesterol Ratio with Insulin Resistance in White European and South Asian Men and Women

Introduction

There is recent interest surrounding the use of the triglyceride-to-HDL cholesterol ratio as a surrogate marker of insulin resistance in clinical practice, as it may identify people at high risk of developing diabetes or its complications. However, it has been suggested using this lipid ratio may not be appropriate for measuring insulin resistance in African-Americans, particularly women. We investigated if this inconsistency extended to South Asian women in a UK multi-ethnic cohort of White Europeans and South Asians.

Methods

Cross-sectional analysis was done of 729 participants from the ADDITION-Leicester study from 2005 to 2009. The association between tertiles of triglyceride-to-HDL cholesterol ratio to fasting insulin, homeostatic model of assessment for insulin resistance (HOMA1-IR), quantitative insulin sensitivity check index (QUICKI) and glucose: insulin ratio was examined with adjustment for confounding variables.

Results

Incremental tertiles of the triglyceride-to-HDL cholesterol ratio demonstrated a significant positive association with levels of fasting insulin, HOMA1-IR, glucose: insulin ratio and a negative association with QUICKI in White European men (n = 255) and women (n = 250) and South Asian men (n = 124) (all p<0.05), but not South Asian women (n = 100). A significant interaction was demonstrated between sex and triglyceride-to-HDL cholesterol ratio tertiles in South Asians only (p<0.05). The area under the receiver operating characteristic curve for triglyceride-to-HDL cholesterol ratio to detect insulin resistance, defined as the cohort HOMA1-IR≥75^th percentile (3.08), was 0.74 (0.67 to 0.81), 0.72 (0.65 to 0.79), 0.75 (0.66 to 0.85) and 0.67 (0.56 to 0.78) in White European men and women, South Asian men and women respectively. The optimal cut-points for detecting insulin resistance were 0.9–1.7 in mmol/l (2.0–3.8 in mg/dl) for the triglyceride-to-HDL ratio.

Conclusion

In South Asian women the triglyceride-to-HDL cholesterol ratio was not associated with insulin resistance; therefore there may be limitations in its use as a surrogate marker in this group.     

The relationship between insulin sensitivity and serum adiponectin levels in three population groups.

Reduced plasma adiponectin levels are associated with insulin resistance. Black South Africans, like African Americans, are more insulin-resistant than BMI-matched white subjects, as are Asian Indians. We investigated whether this interethnic variation in insulin resistance is due to differences in plasma adiponectin levels. Blood and anthropometric measurements were taken from black, white and Asian-Indian subjects. Serum adiponectin, lipids, glucose and insulin were measured; insulin sensitivity was calculated using HOMA. Black (HOMA = 2.62 +/- 0.99) and Asian-Indian subjects (HOMA = 3.41 +/- 2.85) were more insulin-resistant than BMI-matched white (HOMA = 1.76 +/- 0.63) subjects (p = 0.0001). Furthermore, the white subjects had higher adiponectin levels (8.11 +/- 4.39 microg/ml) compared to black (5.71 +/- 2.50 microg/ml) and Asian Indian (5.86 +/- 2.50 microg/ml) subjects (p = 0.003). When all ethnic groups were combined, multiple regression analysis demonstrated that serum adiponectin levels corrected for BMI and ethnicity did not correlate with HOMA, but did explain 10.0 % of the variance in HDL-cholesterol levels. Within each ethnic group, adiponectin only correlated inversely with HOMA in white subjects. Adiponectin may play a role in determining serum HDL-cholesterol levels, but ethnic variation in insulin sensitivity is not dependent on serum levels of this adipokine. The relationship between adiponectin and insulin resistance varies across ethnic groups.     

Altered insulin sensitivity, insulin secretion and lipid profile in non-diabetic prostate carcinoma

Insulin can influence cancer risk through its effect on cell proliferation, differentiation and apoptosis. Although hyperinsulinemia is considered as a risk factor in the pathogenesis of various cancers, the data related to insulin sensitivity, insulin secretion and lipid profile is lacking in non-diabetic prostate carcinoma cases. The present study was undertaken to evaluate lipid profile parameters and insulin sensitivity and secretion using surrogate markers derived from the measurements of fasting glucose and fasting insulin. The study group comprises 27 prostate carcinoma cases and 27 controls having similar age. Fasting serum insulin, glucose and lipid profile parameters were estimated in both the groups. Insulin sensitivity was assessed by Homeostasis model assessment of insulin sensitivity and Quantitative insulin sensitivity check index. Insulin secretion was assessed by insulinogenic index. Fasting serum insulin, insulinogenic index and LDL-cholesterol were significantly increased (p < 0.05) and HOMA-IS, QUICKI and HDL-cholesterol was significantly decreased (p < 0.05) in carcinoma cases compared to controls. PSA level was significantly associated with fasting insulin (R2 = 0.150, beta = 0.387, p = 0.046) and QUICKI (R2 = 0.173, beta = -0.416, p = 0.031). Fasting insulin was significantly correlated with triglyceride (r = 0.404, p = 0.037) and HDL-cholesterol (r = -0.474, p = 0.013). The present study concludes that hyperinsulinemia associated with reduced insulin sensitivity may play a role in the pathogenesis of prostate carcinoma.     

Chemerin as biomarker for insulin sensitivity in males without typical characteristics of metabolic syndrome

To allow early detection and prevention of metabolic disorders, circulating levels of adipokines involved in insulin sensitivity were compared with the hyperinsulinemic-euglycemic clamp. Twenty non-obese normo-glycaemic men (age 32.1 ± 6 years) underwent a clamp procedure. Levels of leptin, adiponectin, resistin, visfatin, omentin and chemerin levels were determined in fasting blood samples. Pearson correlation coefficients between the M-value for insulin sensitivity and fasting levels of chemerin (r = -0.63, P = 0.003) and leptin (r = -0.54, P = 0.013) performed better than conventional surrogate measures of insulin sensitivity (HOMA-IR: r = -0.45, P = 0.048; Quicki: r = 0.36, P = 0.12). However, only the relation between M-value(LBM) and chemerin remained significant when adjusting for BMI and fasting insulin levels (r = -0.559, P = 0.016). In conclusion, fasting levels of chemerin might be used as biomarker to identify insulin resistance in healthy men without typical characteristics of metabolic disorders.     

Elevated plasma proinsulin/insulin ratio is a marker of reduced insulin secretory capacity in healthy young men.

AIM: To examine whether reduced insulin secretory capacity or increased insulin secretory demand is associated with elevated ratio of plasma proinsulin to immunoreactive insulin (PI/IRI ratio) in non-diabetic subjects. SUBJECTS AND METHODS: We measured various indices of insulin secretory function and insulin sensitivity by frequently sampled intravenous glucose tolerance test (FSIGT) and hyerglycemic glucose clamp in 21 healthy young men. We then examined the relationships between these indices and PI, IRI, or PI/IRI ratio in the fasting state. RESULTS: Insulin sensitivity index (SI) measured by FSIGT correlated inversely with basal IRI (r=-0.53, P < 0.01) and PI levels (r=-0.57, P < 0.01), but there was no significant correlation between SI and PI/IRI ratio (r=0.26, NS). On the other hand, PI/IRI ratio correlated inversely with insulin secretory indices, such as acute insulin responses during FSIGT (r =-0.46, P < 0.01) and hyperglycemic glucose clamp (r=-0.54, P < 0.01) and submaximum insulin response during hyperglycemic glucose clamp (r=-0.59, P < 0.01). CONCLUSIONS: These results indicate that elevated PI/IRI ratio may serve as a marker of reduced insulin secretory function in non-diabetic subjects.     

Improved indices of insulin resistance and insulin secretion for use in genetic and population studies of type 2 diabetes mellitus.

Homeostasis model assessment (HOMA) provides indices of insulin secretion (beta) and insulin resistance (R) derived from fasting plasma glucose (FPG) and fasting plasma insulin (FPI) levels. However, these indices could not account for a significant heritability of fasting plasma glucose (FPG) (h2 = 0.75, P<0.01) in a group of 214 female twins. This result is consistent with a misclassification between effects due to insulin secretion and resistance in the HOMA indices. We report here evidence of such misclassification in the HOMA indices and describe a minor modification to the model which corrects it. Direct measures of insulin resistance (euglycaemic clamp) and secretion (i.v. glucose bolus) were obtained in 43 non-diabetic subjects. Heritability was estimated by statistical modelling of genetic and environmental influences in data from 214 non-diabetic female subjects. Modified HOMA (HOMA') indices were obtained from beta' = (Ln(FPI) - c)/FPG and R' = (Ln(FPI) - c)*FPG where c is a constant derived from regression analysis of Ln(FPI) vs FPG. Indices from both models correlated with the direct measures similarly (r = 0.63 (R), 0.49 (R'), 0.45 (beta), 0.39 (beta'), all P< 0.01). Directly measured insulin resistance and secretion were not significantly correlated (r = 0.13, P = 0.21). However, unmodified HOMA-beta and R were strongly related (r = 0.78, P<0.0001 vs. 0.13) demonstrating substantial misclassification. The relationship between beta' and R' (r = 0.13) was not different from that between the two direct measures and significant heritability of beta' (h2 = 0.68, P<0.01) and R' (h2 = 0.59, P<0.05) was evident in the twin data. The proposed modification to HOMA significantly reduces misclassification and reveals separate components of insulin resistance and insulin secretion in the heritability of FPG.     

Insulin sensitivity and beta-cell function in healthy cats: assessment with the use of the hyperglycemic glucose clamp.

A hyperglycemic clamp (HGC) was developed for use in conscious cats. In 21 healthy, normal glucose tolerant cats glucose disposal rate (M), insulin sensitivity (ISI (HGC)), and beta-cell response (I) at arterial plasma glucose of 9 mmol.l (-1) were measured. The HGC was tolerated well and steady state glucose infusion was achieved. Compared to values reported for humans, M values for the cats were low, which appeared to relate to both a low ISI (HGC) and a low I. HGC measures correlated with fasting plasma glucose and insulin concentrations as well as with their HOMA (homeostasis model assessment) and QUICKI (quantitative insulin sensitivity check index) counterparts. Also, I and ISI (HGC) correlated with their counterparts derived from intravenous glucose tolerance tests. In conclusion, this is the first report of hyperglycemic glucose clamping in cats. The procedure (HGC) allows for measurements of glucose disposal, beta-cell response and insulin sensitivity. Compared to human data, both insulin sensitivity and insulin secretion appeared to be low in cats. This is compatible with the carnivorous nature of this species, for which insulin resistance would be advantageous during periods of restricted food availability.     

Clinical characteristics of OGTT-derived hepatic- and muscle insulin resistance in healthy young men

[Purpose]

Insulin inhibits glucose release in the liver but increases glucose absorption in muscles. When insulin cannot properly control glucose, it negatively affects glucose metabolism and, furthermore, contributes to the onset of metabolic syndrome and chronic disease. Therefore, this study''s goal is to understand the clinical characteristics of hepatic insulin resistance and muscle insulin sensitivity in healthy young men.

[Methods]

Twenty-eight healthy young men (age 23.3 ± 0.5; mean ± SE) participated in this study. Liver function and blood lipids were measured by blood sampling from brachial vein after participants fasted the previous day. Hepatic insulin resistance and muscle insulin sensitivity were evaluated using two-hour OGTT along with surrogate index related to insulin sensitivity. The VO_2max was evaluated using cycle ergometer. Systemic insulin sensitivity was evaluated using two-hour euglycemic hyperinsulinemic clamp method.

[Results]

Hepatic insulin resistance showed a significant correlation with body fat (r = 0.609, p < 0.05). Also, hepatic insulin resistance showed a significant correlation with GOT (r = 0.467), GPT (r = 0.434), and γ-GTP (r = 0.375), reflecting liver functions, as well as showing a significant correlation with hs-CRP (r = 0.492, p < 0.05). On the other hand, muscle insulin sensitivity had no correlation with neither body fat nor liver function index (p > 0.05), and among surrogate indexes, it showed a significant correlation with Avignon (r = -0.493) and Matsuda index (r = -0.577). Glucose infusion rate, using the clamp method, showed a significant correlation with muscle insulin sensitivity (r = 0.448, p < 0.05). The VO_2max had a significant correlation with hepatic insulin resistance (r = -0.435, p < 0.05) and muscle insulin sensitivity (r = 0.474, p < 0.05), respectively.

[Conclusion]

For young men in their 20''s, the OGTT-based hepatic insulin sensitivity was an indicator of hepatic function and body fat but muscle insulin sensitivity was related to peripheral insulin sensitivity. Also, for young men, higher VO_2max indicated lower hepatic insulin resistance and higher muscle insulin sensitivity.     

Retinol-binding protein 4 (RBP-4) levels do not change after oral glucose tolerance test and after dexamethasone, but correlate with some indices of insulin resistance in humans

Introduction: Secretory products from adipocytes may contribute to deterioration in glycaemic control and increased insulin resistance (IR). Retinol-binding protein 4 (RBP-4) may increase IR in mice, with elevated levels in insulin-resistant mice and humans with obesity and type 2 diabetes. However, the mechanisms regulating RBP-4 synthesis remain not fully understood. It is not clear whether short-term glucose-induced hyperglycaemia and hyperinsulinaemia as well as glucocorticosteroid-induced increase in IR might be reflected in alterations in serum RBP-4 levels in humans. In order to investigate this, we measured serum RBP-4, glucose and insulin concentrations during 75.0 gram oral glucose tolerance test (OGTT) - Study 1, as well as before and after oral administration of dexamethasone - Study 2. Material and methods: Both studies included 35 subjects (8 males), age (mean +/- SD) 39.1 +/- 15.6 years, BMI 35.8 +/- 8.7 kg/m(2). Twenty-four of those subjects (5 males), age 38.7 +/- 15.1 years, BMI 34.4 +/- 8.3 kg/m(2), had 75 gram oral glucose tolerance test (OGTT) - Study 1. Blood samples were taken before (0 minutes), and at 60 and 120 minutes of OGTT. 17 subjects (3 males, 4 subjects with type 2 diabetes), age 43.1 +/- 18.1 years, BMI 36.7 +/- 9.0 kg/m(2) underwent screening for Cushing's disease/syndrome (Study 2). Dexamethasone was administered in a dose of 0.5 mg every 6 hours for 48 hours. Fasting serum concentrations of RBP-4, glucose and insulin were assessed before (D0) and after 48 hours of dexamethasone administration (D2). IR was assessed by HOMA in all non-diabetic subjects and in subjects participating in study 1 also by Insulin Resistance Index (IRI), which takes into account glucose and insulin levels during OGTT. Results: Glucose administration resulted in significant increases in insulin and glucose (p < 0.0001). There was, however, no change in RBP-4 concentrations (124.1 +/- 32 mg/ml at 0 minutes, 123 +/- 35 mg/ml at 60 minutes and 126.5 +/- 37.5 mg/ml at 120 minutes of OGTT, p = ns). All subjects in Study 2 achieved suppression of cortisol below 50 nmo/l. Dexamethasone administration resulted in an increase in fasting insulin (from 11.6 +/- 6.8 to 17.1 +/- 7.2 muU/ml; p = 0.003), and an increase in HOMA (from 2.73 +/- 1.74 to 4.02 +/- 2.27; p = 0.015), although without a significant change in RBP-4 levels (119 +/- 26.8 vs. 117.5 +/- 24.8 mg/ml, p = ns). RBP-4 correlated with fasting insulin (r = 0.40, p = 0.025), fasting glucose (r = 0.41, p = 0.02) and HOMA (r = 0.43, p = 0.015), but not with IRI (r = 0.19, p = 0.31). There was, however, only a moderate correlation between HOMA and IRI (r = 0.49 [r(2) = 0.24]; p = 0.006, Spearman rank correlation), while the best correlation was obtained between the product of glucose and insulin levels at 60 min of OGTT and IRI in a non-linear model (r = 0.94 [r(2) = 0.88]; p<0.00001). In subjects who received dexamethasone, a positive correlation between RBP-4 and HOMA (p = 0.01) was lost after two days of dexamethasone administration (p = 0.61). Conclusions: RBP-4 levels do not change during oral glucose tolerance test or after a dexamethasone-induced increase in insulin resistance. This implies that it is highly unlikely that RBP-4 is involved in short-term regulation of glucose homeostasis in humans and that it responds to short-term changes in insulin resistance. A moderate correlation between RBP-4 and some insulin resistance indices (HOMA) does not exclude the fact that RBP-4 might be one of many factors that can influence insulin sensitivity in humans.     

Exercise and diet induced weight loss improves measures of oxidative stress and insulin sensitivity in adults with characteristics of the metabolic syndrome

Obesity and insulin resistance (IR) increase the risk for coronary heart disease; however, much of this risk is not attributable to traditional risk factors. We sought to determine whether weight loss associated with supervised aerobic exercise beneficially alters biomarkers of oxidative stress and whether these alterations are associated with improvements in measures of insulin resistance. Twenty-five sedentary and overweight to obese [body mass index (BMI) = 33.0 +/- 0.8 kg/m(2)] individuals, with characteristics of the metabolic syndrome, participated in a 4- to 7-mo weight loss program that consisted of energy restriction (reduced by approximately 500 kcal/day) and supervised aerobic exercise (5 days/wk, 45 min/day at 60% Vo(2 max); approximately 375 kcal/day). IR and insulin sensitivity were assessed by the calculation of the homeostasis model assessment (HOMA) and quantitative insulin sensitivity check index (QUICKI), respectively. Oxidative stress was assessed by oxidized LDL (oxLDL), myeloperoxidase (MPO), and low- and high- density lipoprotein (LDL and HDL) lipid hydroperoxide concentrations in serum. Indexes for antioxidative status included apolipoprotein A1 (apoA1) concentrations and paraoxonase-1 (PON1) activity and protein concentrations. Exercise- and diet-induced weight loss ( approximately 10%) significantly (P < 0.05) increased insulin sensitivity and reduced IR, oxLDL, and LDL lipid hydroperoxides but did not alter HDL lipid hydroperoxides or MPO concentrations. Lifestyle modification impacted systemic antioxidative status by increasing apoA1 concentrations and reducing serum PON1 protein and activity. Changes in oxidative stress were not associated with alterations in HOMA or QUICKI. Diet- and exercise-induced weight loss ( approximately 10%) improves measures of insulin sensitivity and beneficially alters biomarkers of oxidative status.     

Dependency of the metabolic effect of sc-injected human regular insulin on intra-abdominal fat in patients with type 2 diabetes.

Ten patients with type 2 diabetes were enrolled in an isoglycemic glucose clamp study to determine the impact of intra-abdominal fat, subcutaneous abdominal fat and total abdominal fat on the metabolic effect of a single bolus (0.2 IU/kg) of sc-injected human regular insulin. The maximum metabolic effect associated highly and negatively with intra-abdominal fat (r = - 0.72, p < 0.02) and with the homeostasis model assessment insulin resistance score (HOMA, r = - 0.71, p < 0.03). Likewise, the total metabolic effect of sc-injected insulin correlated strongly and negatively with intra-abdominal fat (r = - 0.77, p < 0.01), HOMA (r = - 0.74, p < 0.02) and HbA (1c) (r = - 0.70, p < 0.03). Stepwise multiple regression analyses showed that the highest metabolic effect was only significantly predicted by intra-abdominal fat, indicating a high negative correlation with the maximum effect (beta = - 0.72) whereas time to maximum metabolic effect showed a strong (beta = 0.72) and positive correlation with HOMA. In combination with the HOMA, it is intra-abdominal fat, and not subcutaneous abdominal fat, which explains 50 - 75 % of the variability of the effect of sc human regular insulin in patients with type 2 diabetes.     

High-dose oral vitamin C partially replenishes vitamin C levels in patients with Type 2 diabetes and low vitamin C levels but does not improve endothelial dysfunction or insulin resistance

Endothelial dysfunction is a hallmark of Type 2 diabetes related to hyperglycemia and oxidative stress. Nitric oxide-dependent vasodilator actions of insulin may augment glucose disposal. Thus endothelial dysfunction may worsen insulin resistance. Intra-arterial administration of vitamin C improves endothelial dysfunction in diabetes. In the present study, we investigated effects of high-dose oral vitamin C to alter endothelial dysfunction and insulin resistance in Type 2 diabetes. Plasma vitamin C levels in 109 diabetic subjects were lower than healthy (36 +/- 2 microM) levels. Thirty-two diabetic subjects with low plasma vitamin C (<40 microM) were subsequently enrolled in a randomized, double-blind, placebo-controlled study of vitamin C (800 mg/day for 4 wk). Insulin sensitivity (determined by glucose clamp) and forearm blood flow in response to ACh, sodium nitroprusside (SNP), or insulin (determined by plethysmography) were assessed before and after 4 wk of treatment. In the placebo group (n = 17 subjects), plasma vitamin C (22 +/- 3 microM), fasting glucose (159 +/- 12 mg/dl), insulin (19 +/- 7 microU/ml), and SI(Clamp) [2.06 +/- 0.29 x 10(-4) dl x kg(-1) x min(-1)/(microU/ml)] did not change significantly after placebo treatment. In the vitamin C group (n = 15 subjects), basal plasma vitamin C (23 +/- 2 microM) increased to 48 +/- 6 microM (P < 0.01) after treatment, but this was significantly less than that expected for healthy subjects (>80 microM). No significant changes in fasting glucose (156 +/- 11 mg/dl), insulin (14 +/- 2 microU/ml), SI(Clamp) [2.71 +/- 0.46 x 10(-4) dl x kg(-1) x min(-1)/(microU/ml)], or forearm blood flow in response to ACh, SNP, or insulin were observed after vitamin C treatment. We conclude that high-dose oral vitamin C therapy, resulting in incomplete replenishment of vitamin C levels, is ineffective at improving endothelial dysfunction and insulin resistance in Type 2 diabetes.     

Effects of Tumour Necrosis Factor Antagonists on Insulin Sensitivity/Resistance in Rheumatoid Arthritis: A Systematic Review and Meta-Analysis

Objective

Beyond the joints, TNFi (tumour necrosis factor inhibitor) therapy may confer systemic benefits in rheumatoid arthritis (RA). Several studies have investigated the role of TNFi on insulin resistance/sensitivity (IR/IS). This question is of general interest given the emerging evidence linking inflammation and insulin resistance. The main aim of this review was to summarise the published data and to determine the effects of TNFi on IR/IS.

Methods

We searched the PubMed and ISI Web of Knowledge databases for studies which examined the effects of TNFi on IR/IS. The studies were assessed independently by two reviewers according to a pre-specified protocol. The data on Homeostatic Model Assessment for Insulin resistance (HOMA) and Quantitative Insulin Sensitivity Check Index (QUICKI) were pooled and reported as standard difference in means (SDM) with 95% confidence interval (CI) using a random-effects model.

Results

A total of eight studies with 260 subjects met the selection criteria. The duration of the studies was from 8 weeks to 12 months. There was statistically significant reduction in HOMA index in six out of eight studies and four reported significant increment in QUICKI. The pooled analysis revealed significant reduction in HOMA [SDM-0.148, 95%CI[-0.278 to -0.017], p=0.026] and increment in QUICKI [SDM 0.312, 95%CI[0.019 to 0.606], p=0.037] with TNFi.

Conclusion

There is emerging evidence to support that TNFi therapy improves IS and reduces IR in RA. Further, well conducted trials are needed to determine if such effects translate to lower incidence of diabetes in RA or other autoimmune conditions on biologic therapy.     

Ethnicity and weight status affect the accuracy of proxy indices of insulin sensitivity

This study tested the hypotheses that correlations between direct measures of insulin sensitivity and proxy indices of insulin sensitivity derived from fasting values, (i) would not be affected by ethnicity, and (ii) would be stronger in overweight vs. weight-reduced states. We further hypothesized that associations between proxy indices and fat distribution would be similar to those between directly measured insulin sensitivity and fat distribution. Testing was performed in weight-stable conditions in 59 African-American (AA) and 62 white-American (WA) overweight, premenopausal women before and after a weight loss intervention. Subjects were retested 1 year following weight loss. Proxy indices were correlated against the insulin sensitivity index S(I) determined via minimal modeling. Fat distribution was assessed using computed tomography. Correlations between Si and proxy indices were consistently stronger among overweight women (r = 0.44-0.52) vs. weight-reduced women (r = 0.18-0.32), and among AA (r = 0.49-0.56, baseline; 0.24-0.36, weight-reduced) vs. WA (r = 0.38-0.46, baseline; 0.19-0.31, weight-reduced). Among subjects who regained >3 kg after 1 year, correlations between S(I) and proxy indices were similar to those observed at baseline, whereas correlations were weak among women who maintained their reduced body weight. S(I) and all proxy indices were similarly correlated with intra-abdominal adipose tissue (IAAT) at baseline, but not after weight loss. In conclusion, correlations between S(I) and proxy indices were affected by both ethnicity and weight status. If proxy indices are used in multiethnic populations, or in populations including both lean and overweight/obese subjects, data should be interpreted with caution.     

Is the insulin resistance of patients with noninsulin-dependent diabetes mellitus secondary to insulin deficiency?

Defects in both insulin secretion and action have been documented in patients with noninsulin-dependent diabetes mellitus (NIDDM), leading to the suggestion that both fasting hyperglycemia and insulin resistance in NIDDM are secondary to insulin deficiency. In order to test this hypothesis, insulin secretion (plasma insulin response to oral glucose) and insulin action (insulin clamp) were determined in 25 patients with NIDDM. The results documented relationships between incremental plasma insulin response to glucose and degree of fasting hyperglycemia (r = -.045, P less than 0.05) and insulin-stimulated glucose utilization (r = 0.25, P = NS). These data indicate that differences in insulin secretory response accounted for only approximately 20% of the variance in fasting plasma glucose level and 6% of the variance in insulin resistance in NIDDM. Thus, differences in insulin-secretory response contribute modestly to magnitude of glycemia, and not at all to variations in insulin resistance in NIDDM, permitting rejection of the hypothesis that insulin resistance is secondary to insulin deficiency.