Insulin resistance: the link between obesity and cardiovascular disease

There seems to be general agreement that the prevalence of obesity is increasing in the United States and that we are in the midst of an obesity epidemic. The disease-related implications of this epidemic have received an enormous amount of publicity in the popular media, but public awareness of the untoward effects of excess weight has not led to an effective approach to dealing with the dilemma. The gravity of the problem is accentuated in light of the report that only approximately 50% of physicians polled provided weight loss counseling. Given the importance of excess adiposity as increasing the risk of CVD, 2DM, and hypertension and the combination of an increase in the prevalence of overweight/obesity and a health care system unprepared to deal with this situation, it is essential that considerable thought be given as to how to best address this dilemma. In this context, it must be emphasized that CVD, 2DM, and hypertension are characterized by resistance to insulin-mediated glucose disposal and that insulin resistance and the compensatory hyperinsulinemia associated with insulin resistance have been shown to be independent predictors of all three clinical syndromes. It has also been apparent for many years that overweight/obese individuals tend to be insulin resistant and become more insulin sensitive with weight loss.25 In light of these observations, it seems reasonable to suggest that insulin resistance is the link between overweight/obesity and the adverse clinical syndromes related to excess adiposity. The evidence summarized in this review shows that the more overweight an individual, the more likely he or she is insulin resistant and at increased risk to develop all the abnormalities associated with this defect in insulin action. Not all overweight/obese individuals are insulin resistant, however, any more than all insulin resistant individuals are overweight/obese. More important, there is compelling evidence that CVD risk factors are present to a significantly greater degree in the subset of overweight/obese individuals that is also insulin resistant. Not surprisingly,we have also demonstrated that an improvement in CVD risk factors with weight loss occurs to a significantly greater degree in those overweight/obese individuals who are also insulin resistant at baseline. In view of the ineffectiveness of current clinical approaches to weight loss, it seems necessary to recognize that not all overweight/obese individuals are at equal risk to develop CVD and that it is clinically useful to identify those at highest risk. The simplest way to achieve this task seems to be focusing on the CVD risk factors that are highly associated with insulin resistance/hyperinsulinemia. If this is done, then intense efforts at weight control can be brought to bear on those who not only need it the most but also have the most to gain by losing weight.

Relationships among insulin resistance, type 2 diabetes, essential hypertension, and cardiovascular disease: similarities and differences

Insulin resistance plays a major role in the pathogenesis and clinical course of patients with type 2 diabetes (2DM) and essential hypertension. However, the syndromes differ in prevalence of insulin resistance, and associated insulin secretory response. Essentially all patients with type 2 diabetes are insulin resistant, whereas only approximately 50% of those with essential hypertension are insulin resistant. Furthermore, 2DM develops when the pancreatic β-cell can no longer maintain the degree of compensatory hyperinsulinemia needed to prevent hyperglycemia. In contrast, the compensatory hyperinsulinemia that prevents most insulin resistant individuals from developing 2DM acts on normally insulin sensitive tissues in a manner that predisposes to the development of essential hypertension. This review will discuss these similarities and differences in some detail, as well as exploring the relationship among insulin resistance and related metabolic abnormalities in the pathogenesis of cardiovascular disease in patients with 2DM and essential hypertension.

Adiposity indices in the prediction of metabolic abnormalities associated with cardiovascular disease in non-diabetic adults

BACKGROUND AND AIMS

The prevalence of insulin resistance and cardiovascular disease (CVD) increases with degree of obesity. Whether measurements of generalized and abdominal obesity differ in the ability to predict changes associated with increased CVD risk is widely debated. We compared the prevalence of metabolic abnormalities in 275 women and 204 men stratified by categories of body mass index (BMI) and waist circumference (WC), and assessed the ability of these adiposity indices in combination with metabolic risk variables to predict insulin resistance.

METHODS AND RESULTS

Healthy, non-diabetic volunteers underwent measurements of BMI, WC, blood pressure, fasting plasma glucose (FPG), lipoprotein concentrations, and direct quantification of insulin-mediated glucose uptake. Insulin resistance was defined as the top tertile of steady-state plasma glucose (SSPG) concentrations. BMI and WC were highly correlated (P < 0.001) in both women and men. Abnormal SSPG and triglyceride concentrations were associated with increasing adiposity by either index in both genders. Among women, abnormal FPG and high density lipoprotein cholesterol (HDL-C) concentrations were associated with increasing BMI and WC. In men, abnormal HDL-C was associated with increasing BMI only. Elevated systolic blood pressure (SBP) was associated with increasing BMI in both genders. The odds of insulin resistance were greatest in women with elevated FPG and triglycerides (4.5-fold). In men, the best predictors were BMI and SBP, and WC and HDL-C (3-fold).

CONCLUSION

BMI is at least comparable to WC in stratifying individuals for prevalence of metabolic abnormalities associated with increased CVD risk and predicting insulin resistance.

Estimates of Insulin Secretory Function in Apparently Healthy Volunteers Vary as a Function of How the Relevant Variables Are Quantified

BACKGROUND

Several surrogate estimates have been used to define relationships between insulin action and pancreatic β-cell function in healthy individuals. Because it is unclear how conclusions about insulin secretory function depend on specific estimates used, we evaluated the effect of different approaches to measurement of insulin action and secretion on observations of pancreatic β-cell function in individuals whose fasting plasma glucose (FPG) was &lt;7.0 mmol/L (126 mg/dL).

METHODS

We determined 2 indices of insulin secretion [homeostasis model assessment of β-cell function (HOMA-β) and daylong insulin response to mixed meals], insulin action [homeostasis model assessment of insulin resistance (HOMA-IR) and steady-state plasma glucose (SSPG) concentration during the insulin suppression test], and degree of glycemia [fasting plasma glucose (FPG) and daylong glucose response to mixed meals] in 285 individuals with FPG &lt;7.0 mmol/L. We compared the relationship between the 2 measures of insulin secretion as a function of the measures of insulin action and degree of glycemia.

RESULTS

Assessment of insulin secretion varied dramatically as a function of which of the 2 methods was used and which measure of insulin resistance or glycemia served as the independent variable. For example, the correlation between insulin secretion (HOMA-β) and insulin resistance varied from an r value of 0.74 (when HOMA-IR was used) to 0.22 (when SSPG concentration was used).

CONCLUSIONS

Conclusions about β-cell function in nondiabetic individuals depend on the measurements used to assess insulin action and insulin secretion. Viewing estimates of insulin secretion in relationship to measures of insulin resistance and/or degree of glycemia does not mean that an unequivocal measure of pancreatic β-cell function has been obtained.

Relationships among insulin resistance, obesity, diagnosis of the metabolic syndrome and cardio-metabolic risk

The aim of this study is to test the hypotheses that: 1) diagnosing the metabolic syndrome does not effectively identify insulin-resistant (IR) individuals; and 2) waist circumference (WC) is no better than body mass index (BMI) in predicting insulin resistance or the components of the metabolic syndrome (MetS). Measurements of BMI, WC, blood pressure, and fasting plasma glucose, insulin (FPI), triglycerides (TG), and HDL-cholesterol (HDL-C) concentrations were made in 1,300 adults, without known cardiovascular disease (CVD) or drug treatment of hypertension or diabetes. Receiver operating characteristic curves were used to determine the ability of the MetS, and its components, to identify IR individuals. In addition, comparisons were made of CVD risk factors following division of the population into quartiles of FPI concentrations, and univariate and multiple regression analysis used to compare the ability of WC, BMI, and FPI as predictors of MetS components. The MetS was no more effective in identifying IR individuals than several individual components (sensitivity~40%), and IR individuals not identified were at significantly increased CVD risk. FPI concentration was the best predictor of an abnormal glucose, TG, and HDL-C, whereas the adiposity indices were better predictors of abnormal blood pressure. The relationship between BMI and WC with the MetS and its components seemed comparable.

The metabolic syndrome: time to get off the merry-go-round?

The diagnostic category of the metabolic syndrome (MetS) has received considerable attention over the last decade, and prestigious organizations continue to strive for its incorporation into medical practice. This review has three goals: (i) summarize the history of the several attempts to define a diagnostic category designated as the MetS; (ii) question the aetiological role of abdominal obesity in the development of the other components of the MetS; and (iii) evaluate a diagnosis of the MetS as an effective way to identify apparently healthy individuals at increased risk to develop cardiovascular disease (CVD) or type 2 diabetes (2DM). The most important conclusion is that the MetS seems to be less effective in this population than the Framingham Risk Score in predicting CVD, and no better, if not worse, than fasting plasma glucose concentrations in predicting 2DM.

What is the effect of rosiglitazone treatment on insulin secretory function in insulin-resistant individuals? It depends on how you measure it

The goal of this study was to compare methods used to quantify the effect of rosiglitazone (RSG) on insulin secretory function, particularly estimates based on changes in fasting plasma glucose and insulin concentration vs daylong insulin responses to meals. To do this, we compared these measures of insulin secretion before and 3 months after RSG treatment in insulin-resistant individuals, subdivided into nondiabetic subjects (n = 29) and patients with type 2 diabetes mellitus (2DM) (n = 22). Insulin resistance was quantified by determining the steady-state plasma glucose concentration during the insulin suppression test and insulin secretory function by homeostasis model assessment of β-cell function (HOMA-β) and the total integrated daylong plasma insulin responses to mixed meals (insulin area under the curve). Baseline fasting and daylong plasma glucose concentrations were higher (P < .001) in patients with 2DM, associated with lower HOMA-β values (P < .001). However, neither fasting nor daylong insulin concentrations after mixed meals differed in the 2 groups. Insulin sensitivity improved (P < .001) after RSG administration, with decreases of 31% ± 23% and 21% ± 14% in steady-state plasma glucose concentration in nondiabetic and diabetic subjects, respectively. Although fasting and daylong plasma glucose and insulin concentrations fell (P < .001) in both groups of RSG-treated individuals, HOMA-β decreased in nondiabetic subjects and did not change in those with 2DM. In conclusion, RSG administration improved insulin sensitivity in both groups, associated with lower fasting and daylong glucose concentrations. Fasting and daylong insulin concentrations were also lower in both groups of RSG-treated subjects, but the values of HOMA-β indicated either a decrease (nondiabetics) or no change (diabetics) in insulin secretory function. These results suggest that measurements of HOMA-β may not provide a complete view of insulin secretory function, either when comparing diabetic with nondiabetic individuals or when assessing the response to RSG treatment in insulin-resistant individuals.

Insulin resistance and cardiovascular disease risk factors in subjects with prehypertension

Prehypertension is considered to be associated with increased cardiovascular disease (CVD), and some data suggest that insulin resistance is common in this group. The goal of this study was to quantify insulin action by determining the steady-state plasma glucose (SSPG) concentration during the insulin suppression test in apparently healthy individuals with prehypertension (n=126) and to elucidate the relationship between insulin action and CVD risk.We found a marked heterogeneity in insulin sensitivity in the prehypertension group, and when we divided the population into insulin-sensitive, insulin-resistant and intermediate groups, there were significant (p<0.01) increases in plasma glucose and triglyceride concentrations and decreases in high-density lipoprotein cholesterol concentrations with progressive degrees of insulin resistance. These data show that at least one-third of patients with prehypertension are insulin resistant, display the accompanying metabolic abnormalities, and merit enhanced surveillance and intensive efforts at therapeutic intervention to prevent CVD.

Apelin decreases lipolysis via G(q), G(i), and AMPK-Dependent Mechanisms

The release of free fatty acids (FFAs) from adipocytes (i.e. lipolysis) is increased in obesity and is a contributory factor to the development of insulin resistance. A recently identified adipokine, apelin, is up-regulated in states of obesity. Although apelin is secreted by adipocytes, its functions in them remain largely unknown. To determine whether apelin affects lipolysis, FFA, glycerol, and leptin levels, as well as abdominal adiposity, were measured at baseline and after reintroduction of exogenous apelin in apelin-null mice. To examine apelin's effects in vitro, isoproterenol-induced FFA/glycerol release, and hormone-sensitive lipase (HSL) and acetyl CoA carboxylase phosphorylation were investigated in 3T3-L1 cells and isolated wild-type adipocytes. Serum FFA, glycerol, and leptin concentrations, as well as abdominal adiposity, were significantly increased in apelin-null vs. wild-type mice; these changes were ameliorated in response to exogenous apelin. Apelin also reduced isoproterenol-induced FFA release in adipocytes isolated from wild-type but not APJ-null mice. In 3T3-L1 cells and isolated adipocytes, apelin attenuated isoproterenol-induced FFA/glycerol release. Apelin's inhibition was reversed by pertussis toxin, the G(q) inhibitor glycoprotein antagonist 2A, and the AMP-activated protein kinase inhibitors compound C and dorsomorphin. Apelin increased HSL phosphorylation at Ser-565 and also abrogated isoproterenol-induced HSL phosphorylation at Ser-563. Notably, apelin increased acetyl CoA carboxylase phosphorylation, suggesting AMPK activation. In conclusion, apelin negatively regulates lipolysis. Its actions may be mediated by pathways involving G(q), G(i), and AMP-activated protein kinase.

Glucose-stimulated insulin secretion in gastric bypass patients with hypoglycemic syndrome: no evidence for inappropriate pancreatic beta-cell function

BACKGROUND

Roux-en-Y gastric bypass surgery (RYGB) has been associated with a hypoglycemic syndrome characterized by postprandial hypoglycemia and hyperinsulinemia. The syndrome is believed to occur due to insulin hypersecretion from either pancreatic beta-cell hyperplasia or hyperfunction.

METHODS

Eight RYGB patients with hypoglycemic syndrome had insulin secretion rates determined during a 240-min graded intravenous glucose infusion. They were compared to 34 nondiabetic, nonsurgical individuals who were divided based on their insulin sensitivity status as measured by the insulin suppression test: insulin-sensitive (n = 8), insulin intermediate (n = 7), and insulin-resistant (n = 19).

RESULTS

RYGB patients had insulin concentrations and HOMA-IR similar to the insulin-sensitive reference group. In addition, integrated insulin secretion rates were comparable to the insulin-sensitive group and significantly lower than the insulin intermediate (p <or= 0.046) and insulin-resistant groups (p <or= 0.001). Pancreatic beta-cell sensitivity to glucose (slope relating glucose and ISR) was lowest in the RYGB group (p <or= 0.04).

CONCLUSIONS

Patients with hypoglycemic syndrome post-RYGB do not have generalized hypersecretion of insulin and appear to have appropriate insulin secretion rate in response to intravenous glucose.

Comparison of surrogate and direct measurement of insulin resistance in chronic hepatitis C virus infection: impact of obesity and ethnicity

Studies using surrogate estimates show high prevalence of insulin resistance in hepatitis C infection. This study prospectively evaluated the correlation between surrogate and directly measured estimates of insulin resistance and the impact of obesity and ethnicity on this relationship. Eighty-six nondiabetic, noncirrhotic patients with hepatitis C virus (age = 48 +/- 7 years, 74% male, 44% white, 22% African American, 26% Latino, 70% genotype 1) were categorized into normal-weight (body mass index [BMI] < 25, n = 30), overweight (BMI = 25-29.9, n = 38), and obese (BMI > or = 30, n = 18). Insulin-mediated glucose uptake was measured by steady-state plasma glucose (SSPG) concentration during a 240-minute insulin suppression test. Surrogate estimates included: fasting glucose and insulin, glucose/insulin, homeostasis model assessment (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), insulin (I-AUC) and glucose (G-AUC) area under the curve during oral glucose tolerance test, and the Belfiore and Stumvoll indexes. All surrogate estimates correlated with SSPG, but the magnitude of correlation varied (r = 0.30-0.64). The correlation coefficients were highest in the obese. I-AUC had the highest correlation among all ethnic and weight groups (r = 0.57-0.77). HOMA-IR accounted for only 15% of variability in SSPG in the normal weight group. The common HOMA-IR cutoff of < or =3 to define insulin resistance had high misclassification rates especially in the overweight group independent of ethnicity. HOMA-IR > 4 had the lowest misclassification rate (75% sensitivity, 88% specificity). Repeat HOMA-IR measurements had higher within-person variation in the obese (standard deviation = 0.77 higher than normal-weight, 95% confidence interval = 0.25-1.30, P = 0.005).

CONCLUSION

Because of limitations of surrogate estimates, caution should be used in interpreting data evaluating insulin resistance especially in nonobese, nondiabetic patients with HCV.

Relationship between body mass index and insulin resistance in patients treated with second generation antipsychotic agents

Second generation antipsychotics (SGAs) can increase weight gain and weight-induced insulin resistance. Recent studies have suggested weight-independent effects of certain SGAs on insulin resistance; however the magnitude of these effects and the relationship between BMI and insulin resistance in patients on SGAs are not established. To evaluate, the relationship between body mass index (BMI) and insulin resistance in 54 patients being stably treated with olanzapine (n=19), risperidone (n=16), or aripiprazole (n=19) was compared with data from a large reference population (n=201) not on SGAs. Insulin resistance was directly quantified by measuring the steady-state plasma glucose (SSPG) concentration during the insulin suppression test. The relationship between BMI and SSPG was similar between the SGA (r=0.58) and the reference population (r=0.50). When SSPG was standardized based on expected values for the reference population, patients on olanzapine had a higher degree of insulin resistance (mean z-score+/-SD, 0.68+/-0.9) than expected for level of BMI compared with those on aripiprazole (-0.25+/-1) and risperidone (-0.3+/-0.9), F(2,51)=6.28 (p=0.004). Thus, olanzapine group was 0.76 SD above the reference population or in the 78 percentile for insulin resistance. SSPG was correlated with fasting plasma insulin concentration (0.78 (0.64-0.87), p<0.001) but not fasting glucose concentration (0.15 (-0.13-0.40), p=0.29). In conclusion, BMI contributes a quarter to a third of the variance in insulin resistance in the SGA population similar to the reference population. Olanzapine also appears to have an independent effect on insulin resistance that is above and beyond obesity.

Pioglitazone increases the proportion of small cells in human abdominal subcutaneous adipose tissue

Rodent and in vitro studies suggest that thiazolidinediones promote adipogenesis but there are few studies in humans to corroborate these findings. The purpose of this study was to determine whether pioglitazone stimulates adipogenesis in vivo and whether this process relates to improved insulin sensitivity. To test this hypothesis, 12 overweight/obese nondiabetic, insulin-resistant individuals underwent biopsy of abdominal subcutaneous adipose tissue at baseline and after 12 weeks of pioglitazone treatment. Cell size distribution was determined via the Multisizer technique. Insulin sensitivity was quantified at baseline and postpioglitazone by the modified insulin suppression test. Regional fat depots were quantified by computed tomography (CT). Insulin resistance (steady-state plasma insulin and glucose (SSPG)) decreased following pioglitazone (P < 0.001). There was an increase in the ratio of small-to-large cells (1.16 +/- 0.44 vs. 1.52 +/- 0.66, P = 0.03), as well as a 25% increase in the absolute number of small cells (P = 0.03). The distribution of large cell diameters widened (P = 0.009), but diameter did not increase in the case of small cells. The increase in proportion of small cells was associated with the degree to which insulin resistance improved (r = -0.72, P = 0.012). Visceral abdominal fat decreased (P = 0.04), and subcutaneous abdominal (P = 0.03) and femoral fat (P = 0.004) increased significantly. Changes in fat volume were not associated with SSPG change. These findings demonstrate a clear effect of pioglitazone on human subcutaneous adipose cells, suggestive of adipogenesis in abdominal subcutaneous adipose tissue, as well as redistribution of fat from visceral to subcutaneous depots, highlighting a potential mechanism of action for thiazolidinediones. These findings support the hypothesis that defects in subcutaneous fat storage may underlie obesity-associated insulin resistance.

Utility of homeostasis model assessment of beta-cell function in predicting diabetes in 12,924 healthy Koreans

OBJECTIVE

It is unclear how well homeostasis model assessment of beta-cell function (HOMA-beta) predicts diabetes development beyond its components, especially glucose.

RESEARCH DESIGN AND METHODS

We identified 12,924 nondiabetic Koreans who had fasting plasma glucose and insulin concentrations measured in 2003 and again in 2008. To minimize the impact of differences in baseline glucose concentration, individuals were divided into three glucose categories: normal fasting glucose (NFG, glucose <5.6 mmol/l), impaired fasting glucose (IFG-100) (5.6-6.0 mmol/l), and IFG-110 (6.1-6.9 mmol/l).

RESULTS

Diabetes developed in 29% of individuals in the IFG-110 group, compared with 5% in IFG-100 and 0.3% in NFG groups. Within each glucose category, those who progressed to diabetes had higher baseline glucose concentrations (P < or = 0.04). Baseline HOMA-beta, however, was not lower but higher in individuals who developed diabetes in the NFG group (P = 0.009) and similar in the IFG-100 and IFG-110 groups.

CONCLUSIONS

These data question the utility of using HOMA-beta to predict the development of diabetes.

Apelin is necessary for the maintenance of insulin sensitivity

The recently discovered peptide apelin is known to be involved in the maintenance of insulin sensitivity. However, questions persist regarding its precise role in the chronic setting. Fasting glucose, insulin, and adiponectin levels were determined on mice with generalized deficiency of apelin (APKO). Additionally, insulin (ITT) and glucose tolerance tests (GTT) were performed. To assess the impact of exogenously delivered apelin on insulin sensitivity, osmotic pumps containing pyroglutamated apelin-13 or saline were implanted in APKO mice for 4 wk. Following the infusion, ITT/GTTs were repeated and the animals euthanized. Soleus muscles were harvested and homogenized in lysis buffer, and insulin-induced Akt phosphorylation was determined by Western blotting. Apelin-13 infusion and ITTs/GTTs were also performed in obese diabetic db/db mice. To probe the underlying mechanism for apelin's effects, apelin-13 was also delivered to cultured C2C12 myotubes. 2-[3H]deoxyglucose uptake and Akt phosphorylation were assessed in the presence of various inhibitors. APKO mice had diminished insulin sensitivity, were hyperinsulinemic, and had decreased adiponectin levels. Soleus lysates had decreased insulin-induced Akt phosphorylation. Administration of apelin to APKO and db/db mice resulted in improved insulin sensitivity. In C2C12 myotubes, apelin increased glucose uptake and Akt phosphorylation. These events were fully abrogated by pertussis toxin, compound C, and siRNA knockdown of AMPKalpha1 but only partially diminished by LY-294002 and not at all by L-NAME. We conclude that apelin is necessary for the maintenance of insulin sensitivity in vivo. Apelin's effects on glucose uptake and Akt phosphorylation are in part mediated by a G(i) and AMPK-dependent pathway.

Insulin secretory function in type 2 diabetes: Does it matter how you measure it?

The following estimates of insulin secretory function have been used widely to evaluate the role of pancreatic β-cells in the pathogenesis and treatment of patients with type 2 diabetes (2DM): (i) Homeostatic Model Assessment (HOMA)-β, a calculation based on fasting plasma glucose and insulin concentrations; (ii) post-glucose acute insulin response (AIRg), the increment in insulin concentration measured in the 5 min after intravenous glucose; and (iii) ΔI/ΔG, the ratio of the increment in plasma insulin concentration (I)/increment in plasma glucose concentration (G) 30 min after the oral administration of 75 g glucose. Experiments based on these approaches have led to a widely held point of view that that the natural history of 2DM is characterized by a progressive increase in the magnitude of hyperglycemia, secondary to an inexorable decline in pancreatic β-cell function: the greater the increase in plasma glucose concentration, the greater the impairment of the ability of the pancreas to secrete insulin. In the present review, theoretical questions are raised as to the physiological validity of these estimates of insulin secretory function and experimental data are presented demonstrating that hourly measurements of plasma insulin and glucose concentrations in response to mixed meals throughout an 8-h day lead to a very different point of view. Studies are also reviewed that question the 'inexorability' of the changes in insulin secretory function that have been reported. It is concluded that it may be time to challenge current conventional wisdom as to the role of the β-cell in the natural history of 2DM.

Pioglitazone decreases postprandial accumulation of remnant lipoproteins in insulin-resistant smokers

BACKGROUND

Fasting hypertriglyceridaemia has been reported to occur commonly in cigarette smokers and is thought to increase cardiovascular disease (CVD) risk in these individuals. More recently, it has been suggested that an increase in non-fasting triglycerides, rather than fasting hypertriglyceridaemia, is an independent CVD risk factor.

METHODS

In this study, we divided 24 smokers into insulin-resistant (IR) and insulin-sensitive (IS) groups by determining their steady-state plasma glucose concentrations during the insulin suppression test and compared fasting and daylong postprandial accumulation of total triglycerides and remnant lipoprotein (RLP) concentrations, before and after 3 months of pioglitazone (PIO) administration.

RESULTS

The two groups were similar in age, body mass index, race and gender distribution, but differed dramatically in insulin sensitivity. Baseline fasting and postprandial triglyceride, RLP cholesterol and RLP triglyceride concentrations were significantly higher in the IR smokers (p=0.01 to <0.01). Insulin resistance [corrected] and both fasting and postprandial triglyceride and RLP triglyceride levels decreased significantly (p=0.05 to 0.01) [corrected] in PIO-treated IR smokers, without any significant increase in weight instead of insulin sensitivity and both fasting and postprandial triglyceride and RLP triglyceride levels decreased significantly (p = 0.05 to, 0.01) in PIO-treated IR smokers, without any significant increase in weight. [corrected]

CONCLUSIONS

The postprandial accumulation of RLP particles is increased in the IR subset of smokers and is likely to contribute to the increased CVD risk in these individuals. Furthermore, PIO administration provides a possible therapeutic approach to decreasing postprandial lipaemia and CVD risk in IR smokers who are unwilling or unable to stop smoking.

The increase in plasma PAI-1 associated with insulin resistance may be mediated by the presence of hepatic steatosis

OBJECTIVE

Recent evidence suggests that plasminogen-activator inhibitor-1 (PAI-1) is abundantly produced by the fatty liver, but it is unclear whether hepatic steatosis (HS) can mediate the increase in plasma PAI-1 induced by insulin resistance/compensatory hyperinsulinemia (IR/CH).

METHODS AND RESULTS

To address this issue, we cross-sectionally evaluated IR/CH as area under the curve of plasma insulin (AUC-PI) concentrations during OGTT, metabolic profile, and ultrasound degree of HS in 235 healthy volunteers (132M, age: 60+/-7 years) with normal transaminase concentrations. Circulating PAI-1 was increased in subjects with classical features of IR/CH (overweight, high fasting and post-OGTT insulin and glucose, high triglycerides (TG), and low HDL-cholesterol), and significantly correlated to prevalence and degree of HS, but not to alcohol intake. In a multivariate model, AUC-PI, TG and degree of HS were independent predictors of plasma PAI-1 (R(2)=0.32). However, AUC-PI was significantly correlated to PAI-1 only in subjects with HS, suggesting an interaction between AUC-PI and HS. In addition, in the presence of HS and IR/CH, PAI-1 concentrations were increased to a similar extent both in heavy and moderate drinkers, suggesting that metabolic and alcoholic steatosis have a similar effect on the relationship between IR/CH and PAI-1.

CONCLUSION

These results support the hypothesis that HS has a major impact on the relationship between IR/CH and plasma PAI-1 concentrations, and this effect seems to be unaffected by the etiology of the HS.

In search of moderators and mediators of hyperglycemia with atypical antipsychotic treatment

Signal detection methods were used to identify values of metabolic variables that predict development of prediabetes or diabetes before (moderators) or associated with treatment (mediators), utilizing data from two multi-center clinical trials of patients with schizophrenia, treated for 6 months with olanzapine (OLZ) or ziprasidone (ZIP). At baseline, participants were often overweight/obese (63% with a body mass index >or=25.0kg/m(2)), dyslipidemic [more than one-third had elevated triglyceride (TG) and low high-density lipoprotein cholesterol (HDL-C) concentrations], and prediabetic (20%). Weight gain was significantly greater in OLZ-treated patients, as was accentuation of dyslipidemia. However, there were no significant correlations between weight gain and lipid changes from baseline to weeks 2, 4, 8 or to last observation. Type 2 diabetes developed in 4% and prediabetes in 18% of the population. Significant baseline predictors of diabetes were a HDL-C concentration <28mg/dL, or being >or=58-years-old if HDL-C concentration was >or=28mg/dL. Baseline plasma glucose concentration >or=92mg/dL was the only significant predictor of developing prediabetes, accounting for 60% of cases. Post-treatment increments in plasma TG concentrations >or=145mg/dL or >or=59mg/dL were significant predictors of diabetes (23%) or prediabetes (27%), respectively. If the increase in TG was <145mg/dL, rapid weight gain >or=6.1kg in 2 weeks predicted development of diabetes (18%). These findings provide a quantitative approach to identify those at greatest treatment-associated risk to develop glucose intolerance, and emphasize the need to address co-morbid medical disorders in these patients.