Gerald M. Reaven

Role of Insulin Resistance in Human Disease

Resistance to insulin-stimulated glucose uptake is present in the majority of patients with impaired glucose tolerance (IGT) or non-insulin-dependent diabetes mellitus (NIDDM) and in ∼25% of nonobese individuals with normal oral glucose tolerance. In these conditions, deterioration of glucose tolerance can only be prevented if the β-cell is able to increase its insulin secretory response and maintain a state of chronic hyperinsulinemia. When this goal cannot be achieved, gross decompensation of glucose homeostasis occurs. The relationship between insulin resistance, plasma insulin level, and glucose intolerance is mediated to a significant degree by changes in ambient plasma free-fatty acid (FFA) concentration. Patients with NIDDM are also resistant to insulin suppression of plasma FFA concentration, but plasma FFA concentrations can be reduced by relatively small increments in insulin concentration.Consequently, elevations of circulating plasma FFA concentration can be prevented if large amounts of insulin can be secreted. If hyperinsulinemia cannot be maintained, plasma FFA concentration will not be suppressed normally, and the resulting increase in plasma FFA concentration will lead to increased hepatic glucose production. Because these events take place in individuals who are quite resistant to insulinstimulated glucose uptake, it is apparent that even small increases in hepatic glucose production are likely to lead to significant fasting hyperglycemia under these conditions. Although hyperinsulinemia may prevent frank decompensation of glucose homeostasis in insulin-resistant individuals, this compensatory response of the endocrine pancreas is not without its price. Patients with hypertension, treated or untreated, are insulin resistant, hyperglycemic, and hyperinsulinemic. In addition, a direct relationship between plasma insulin concentration and blood pressure has been noted. Hypertension can also be produced in normal rats when they are fed a fructose-enriched diet, an intervention that also leads to the development of insulin resistance and hyperinsulinemia. The development of hypertension in normal rats by an experimental manipulation known to induce insulin resistance and hyperinsulinemia provides further support for the view that the relationship between the three variables may be a causal one. However, even if insulin resistance and hyperinsulinemia are not involved in the etiology of hypertension, it is likely that the increased risk of coronary artery disease (CAD) in patients with hypertension and the fact that this risk if not reduced with antihypertensive treatment are due to the clustering of risk factors for CAD, in addition to high blood pressure, associated with insulin resistance. These include hyperinsulinemia, IGT, increased plasma triglyceride concentration, and decreased high-density lipoprotein cholesterol concentration, all of which are associated with increased risk for CAD. It is likely that the same risk factors play a significant role in the genesis of CAD in the population as a whole. Based on these considerations the possibility is raised that resistance to insulin-stimulated glucose uptake and hyperinsulinemia are involved in the etiology and clinical course of three major related diseases— NIDDM, hypertension, and CAD.

Banting lecture 1988. Role of insulin resistance in human disease.

Resistance to insulin-stimulated glucose uptake is present in the majority of patients with impaired glucose tolerance (IGT) or non-insulin-dependent diabetes mellitus (NIDDM) and in approximately 25% of nonobese individuals with normal oral glucose tolerance. In these conditions, deterioration of glucose tolerance can only be prevented if the beta-cell is able to increase its insulin secretory response and maintain a state of chronic hyperinsulinemia. When this goal cannot be achieved, gross decompensation of glucose homeostasis occurs. The relationship between insulin resistance, plasma insulin level, and glucose intolerance is mediated to a significant degree by changes in ambient plasma free-fatty acid (FFA) concentration. Patients with NIDDM are also resistant to insulin suppression of plasma FFA concentration, but plasma FFA concentrations can be reduced by relatively small increments in insulin concentration. Consequently, elevations of circulating plasma FFA concentration can be prevented if large amounts of insulin can be secreted. If hyperinsulinemia cannot be maintained, plasma FFA concentration will not be suppressed normally, and the resulting increase in plasma FFA concentration will lead to increased hepatic glucose production. Because these events take place in individuals who are quite resistant to insulin-stimulated glucose uptake, it is apparent that even small increases in hepatic glucose production are likely to lead to significant fasting hyperglycemia under these conditions. Although hyperinsulinemia may prevent frank decompensation of glucose homeostasis in insulin-resistant individuals, this compensatory response of the endocrine pancreas is not without its price. Patients with hypertension, treated or untreated, are insulin resistant, hyperglycemic, and hyperinsulinemic. In addition, a direct relationship between plasma insulin concentration and blood pressure has been noted. Hypertension can also be produced in normal rats when they are fed a fructose-enriched diet, an intervention that also leads to the development of insulin resistance and hyperinsulinemia. The development of hypertension in normal rats by an experimental manipulation known to induce insulin resistance and hyperinsulinemia provides further support for the view that the relationship between the three variables may be a causal one.(ABSTRACT TRUNCATED AT 400 WORDS)

Fructose-induced insulin resistance and hypertension in rats.

To determine if hypertension could be produced in normal rats by feeding them a fructose-enriched diet, Sprague-Dawley rats were fed either normal chow or a diet containing 66% fructose as a percentage of total calories for approximately 2 weeks. At the end of this period systolic blood pressure had increased from 124 +/- 2 to 145 +/- 2 (SEM) mm Hg in the fructose-fed rats, whereas no change occurred in the control group. In addition, hyperinsulinemia and hypertriglyceridemia were associated with hypertension in fructose-fed rats. The addition of clonidine to the drinking water inhibited fructose-induced hypertension, but not the increase in plasma insulin or triglyceride concentration seen in fructose-fed rats. Thus, the metabolic changes associated with fructose-induced hypertension are unlikely to be secondary to an increase in sympathetic activity. Whether or not this is also true of the hypertension remains to be clarified.

Use of Metabolic Markers To Identify Overweight Individuals Who Are Insulin Resistant

Context Insulin resistance is associated with adverse outcomes, such as cardiovascular disease and type 2 diabetes mellitus. The insulin suppression test, the gold standard method of diagnosing insulin resistance, is cumbersome to administer. A simple method to identify persons with insulin resistance would be useful. Contribution In a group of overweight individuals, 3 easily measured variables (triglyceride levels, the ratio of triglyceride to high density lipoprotein [HDL] cholesterol levels, and insulin concentration) identified insulin-resistant individuals with sensitivities of 57% to 67% and specificities of 68% to 85%. Implications Triglyceride levels, the triglyceride-HDL cholesterol ratio, and insulin concentration are imperfect but practical methods for identifying overweight persons who are insulin resistant and at greatest risk for complications. The Editors Recent reports (1) indicate that more than 50% of the U.S. population is overweight (body mass index [BMI] 25 kg/m2), with approximately 20% designated as obese (BMI 30 kg/m2). Because overweight is important in the genesis of type 2 diabetes mellitus and cardiovascular disease (CVD), the absolute number of Americans in this category is disturbing. The gravity of the problem is accentuated in light of the report that only approximately 50% of physicians polled provided weight loss counseling (2) and that pharmacologic treatment of weight loss is not being used appropriately in overweight persons (3). Reluctance to assign weight control programs a high priority might be decreased if identifying overweight or obese individuals at greatest risk for adverse health consequences were possible, particularly if weight loss would significantly attenuate the risk. In this context, it is necessary to begin by emphasizing that the prevalence of insulin resistance is increased in patients with type 2 diabetes mellitus, essential hypertension, and CVD and that insulin resistance and compensatory hyperinsulinemia have been shown to be independent predictors of all 3 clinical syndromes (4-9). Since obese individuals tend to be insulin resistant and become more insulin sensitive with weight loss (10), an obvious approach to identify individuals who would most benefit from weight loss is to measure insulin-mediated glucose disposal. However, direct measures of insulin-mediated glucose disposal are not clinically practical. On the other hand, overweight persons are also at increased risk for glucose intolerance, and the higher the plasma glucose or insulin concentrations in nondiabetic persons, the more likely that the persons are insulin resistant (4, 11). Thus, differences in fasting plasma glucose or insulin concentrations might be useful to identify insulin-resistant persons. These persons also have a characteristic dyslidemia (4), and measuring these variables might also help identify insulin resistance. For example, plasma triglyceride and high-density lipoprotein (HDL) cholesterol levels are independently associated with insulin resistance (12) and are independent predictors of CVD (13, 14). In addition, the plasma concentration ratio of total cholesterol to HDL cholesterol is well recognized as a predictor of CVD (15) and is also highly correlated with insulin resistance (16). A less commonly considered CVD risk factor is the ratio of triglyceride to HDL cholesterol, despite the observation that the triglycerideHDL cholesterol ratio is as significant a predictor of CVD as are the ratios of low-density lipoprotein (LDL) cholesterol to HDL cholesterol or total cholesterol to HDL cholesterol (17). A more recent study showed that persons in the highest tertile of the triglycerideHDL cholesterol ratio had increased CVD risk in the absence of the 4 conventional risk factors, whereas those in the lowest tertile had decreased risk in the presence of the same 4 risk factors (18). Although obese individuals tend to be insulin resistant, hyperinsulinemic, glucose intolerant, and dyslipidemic, not all overweight or obese individuals are insulin resistant, nor do they all have the characteristic disturbances in glucose or lipid metabolism (19-23). Furthermore, not all CVD risk factors improve with weight loss, and the metabolic benefits associated with weight loss are largely confined to overweight or obese individuals with these abnormalities at baseline (20-23). Given the relative ease of measuring plasma glucose, insulin, and lipid concentrations, and their importance as both CVD risk factors and manifestations of insulin resistance, we attempted to develop a simple clinical approach using these measurements to identify overweight or obese individuals who are both insulin resistant and at greatest risk for CVD. Methods The study sample consisted of 258 persons with a BMI of 25 kg/m2 or greater, classified as overweight or obese by National Institutes of Health (24) and World Health Organization criteria (25). Participants were drawn from a large database of 490 healthy volunteers who have participated in research studies in the past 10 years. These studies typically used newspaper advertisements to identify persons without known disease to participate in our efforts to define the relationship between insulin resistance and metabolic abnormalities. According to their medical histories, study participants did not have major chronic medical illnesses, including CVD, and were not taking any medication known to influence insulin resistance or lipid metabolism (such as corticosteroids and lipid-lowering drugs). No clinically significant abnormalities were found during physical examination; participants were not anemic, had normal liver and kidney function, and were nondiabetic on the basis of plasma glucose concentrations in response to a standard oral glucose challenge (26). The 258 individuals included 127 men and 131 women with a mean age (SD) of 50 16 years (range, 19 to 70 years) and a mean BMI (SD) of 29.2 3.2 kg/m2 (range, 25.0 to 39.1 kg/m2). Most participants were white (87%); the remaining participants were Asian American (9%), Hispanic (3%), or African American (1%). Insulin-mediated glucose disposal was estimated by a modification (27) of the insulin suppression test introduced and validated by our research group (28, 29). We have used this approach for more than 35 years to measure insulin action, and results are highly correlated (r > 0.9) with the more commonly used euglycemic, hyperinsulinemic clamp approach (29). After an overnight fast, intravenous catheters are placed in each of the patients arms. A 180-minute infusion of somatostatin (250 g/h), insulin (179 mol/m2 per min 1), and glucose (13.3 mmol/m 2 2 per min) is administered into 1 arm. Blood samples are collected from the other arm every 30 minutes initially and at 10-minute intervals from 150 to 180 minutes of the infusion to determine the steady-state plasma insulin and glucose concentrations. Since steady-state plasma insulin concentrations are similar for all participants, the steady-state plasma glucose concentration directly measures the insulins ability to mediate disposal of the infused glucose load; the higher the steady-state plasma glucose concentration, the more insulin resistant the patient. Blood samples were obtained before the insulin suppression test to measure plasma glucose (30), insulin (31), and lipid and lipoprotein (32-34) levels by methods that were identical during the period of study. We have found that insulins ability to stimulate glucose disposal varied continuously in a sample of 490 healthy persons (35), precluding an objective definition of an individual as being insulin sensitive or insulin resistant. However, in 2 prospective studies (8, 9), we showed that CVD and glucose intolerance or type 2 diabetes developed to a statistically significantly greater degree in one third of the healthy sample that was the most insulin resistant (that is, the tertile with the highest steady-state plasma glucose concentrations). On the basis of these considerations and for the purposes of this analysis, we used as an operational definition of insulin resistance a steady-state plasma glucose concentration in the upper tertile of the distribution of the original 490 healthy volunteers. Because of possible interaction between metabolic markers, sex, and menopausal status of women, we performed logistic regression analysis for predicting insulin resistance that included the best metabolic marker, sex, menopausal status, and all interaction terms. Since there were no significant interactions, men and women, regardless of their menopausal status, were considered together in subsequent analyses. Clinical utility of metabolic markers to identify individuals in the most insulin-resistant tertile was evaluated by constructing receiver-operating characteristic (ROC) curves, which depict the relationship between true-positive (sensitivity) and false-positive (1 specificity) test results for each diagnostic marker. Markers for which a relative increase in sensitivity is matched by a similar increase in false-positive results are represented by a diagonal line and are of less clinical use. Metabolic markers considered were fasting plasma concentrations of glucose, insulin, triglyceride, cholesterol, and HDL cholesterol, as well as the cholesterolHDL cholesterol ratio and the triglycerideHDL cholesterol ratio. Areas under the ROC curves were compared using the method of Hanley and McNeil (36). The metabolic markers of insulin resistance that were statistically significantly better performers were selected for cut-point analysis to identify specific values that would be useful in predicting insulin resistance. The cut-points diagnostic of the top tertile of steady-state plasma glucose were based on the formula M = ws + (1 w) p, where w = prevalence of disease (top tertile steady-state plasma glucose), s = sensitivity, and p = specificity (37). According to this equation, the cut-point identi

Insulin resistance and hyperinsulinemia in individuals with small, dense low density lipoprotein particles.

Subjects characterized by a predominance of small LDL particles (pattern B) have changes in plasma triglyceride (TG) and HDL-cholesterol concentrations consistent with the presence of resistance to insulin-mediated glucose uptake. To pursue this issue, plasma glucose and insulin responses to oral glucose, insulin-mediated glucose disposal, and lipoprotein concentrations were measured in subjects categorized on the basis of LDL peak diameter measured by gradient gel electrophoresis. Subjects with pattern B had higher (P < 0.05-0.001) total integrated plasma glucose (20.7 +/- 1.0 mmol/liter.h) and insulin (1,743 +/- 293 pmol/liter.h) responses to oral glucose compared with glucose (16.3 +/- 0.4 and 19.2 +/- 0.8 mmol/liter.h) and insulin (856 +/- 60 and 1,222 +/- 168 pmol/liter.h) responses in those with either pattern A or an intermediate pattern. Pattern B individuals were shown to be more insulin resistant on the basis of higher steady state plasma glucose concentrations (SSPG, 10.4 +/- 1.0, P < 0.002, vs. 7.5 +/- 0.7 and 6.0 +/- 0.4 mmol/liter) after a constant infusion of somatostatin, glucose, and insulin than those with either the intermediate or pattern A subclass. Pattern B subjects also had higher concentrations of (P < 0.001) TG (1.98 +/- 0.15 vs. 1.33 +/- 0.17 and 0.77 +/- 0.05 mmol/liter) and lower (P < 0.01-0.001) HDL cholesterol (1.12 +/- 0.06 vs. 1.34 +/- 0.05 vs. 1.45 +/- 0.05 mmol/liter) than those with either the intermediate or pattern A. Finally, significant (P < 0.001) correlation coefficients existed between LDL diameter and SSPG (r = -0.44); glucose (r = -0.41) and insulin (r = -0.38) responses; TG (r = -0.65) and HDL-cholesterol (r = 0.42) concentrations; and systolic (r = -0.34) and diastolic (r = -0.34) blood pressure. Thus, pattern B subjects are insulin resistant, have higher glucose, insulin, and TG, lower HDL-cholesterol levels, and higher blood pressure than those with pattern A or intermediate.

Impaired nitric oxide synthase pathway in diabetes mellitus: Role of asymmetric dimethylarginine and dimethylarginine dimethylaminohydrolase

Background—An endogenous inhibitor of nitric oxide synthase, asymmetric dimethylarginine (ADMA), is elevated in patients with type 2 diabetes mellitus (DM). This study explored the mechanisms by which ADMA becomes elevated in DM. Methods and Results—Male Sprague-Dawley rats were fed normal chow or high-fat diet (n=5 in each) with moderate streptozotocin injection to induce type 2 DM. Plasma ADMA was elevated in diabetic rats (1.33±0.31 versus 0.48±0.08 &mgr;mol/L;P <0.05). The activity, but not the expression, of dimethylarginine dimethylaminohydrolase (DDAH) was reduced in diabetic rats and negatively correlated with their plasma ADMA levels (P <0.05). DDAH activity was significantly reduced in vascular smooth muscle cells and human endothelial cells (HMEC-1) exposed to high glucose (25.5 mmol/L). The impairment of DDAH activity in vascular cells was associated with an accumulation of ADMA and a reduction in generation of cGMP. In human endothelial cells, coincubation with the antioxidant polyethylene glycol–conjugated superoxide dismutase (22 U/mL) reversed the effects of the high-glucose condition on DDAH activity, ADMA accumulation, and cGMP synthesis. Conclusions—A glucose-induced impairment of DDAH causes ADMA accumulation and may contribute to endothelial vasodilator dysfunction in DM.

Insulin resistance and cigarette smoking.

Cigarette smoking is associated with increases in plasma triglycerides and decreases in plasma high density-lipoprotein-cholesterol concentration. These changes not only increase risk of coronary heart disease but also are secondary to resistance to insulin-stimulated glucose uptake or hyperinsulinaemia. To see whether there is a relation between cigarette smoking and insulin-mediated glucose uptake we measured plasma lipid and lipoprotein concentrations, plasma glucose and insulin response to an oral glucose challenge, and insulin-mediated glucose uptake in 40 matched healthy volunteers (20 non-smokers, 20 smokers). Smokers had significantly higher mean (SEM) very-low-density-lipoprotein triglycerides (0.66 [0.10] vs 0.39 [0.03] mmol/l, p less than 0.02) and cholesterol (0.45 [0.06] vs 0.23 [0.04] mmol/l, p less than 0.005) concentrations and lower high-density-lipoprotein cholesterol concentrations (1.16 [0.05] vs 1.51 [0.08] mmol/l, p less than 0.001). Although plasma glucose concentrations in response to the oral glucose load were similar in the two groups, plasma insulin response of the smokers was significantly higher (p less than 0.001). Finally, smokers had higher steady-state plasma glucose concentrations in response to a continuous infusion of glucose, insulin, and somatostatin (8.4 [0.2] vs 5.0 [0.3] mmol/l, p less than 0.001), despite similar steady-state plasma insulin concentrations. The findings show that chronic cigarette smokers are insulin resistant, hyperinsulinaemic, and dyslipidaemic compared with a matched group of non-smokers, and may help to explain why smoking increases risk of coronary heart disease.

Measurement of Plasma Glucose, Free Fatty Acid, Lactate, and Insulin for 24 h in Patients With NIDDM

Fasting and postprandial plasma glucose, free fatty acid (FFA), lactate, and insulin concentrations were measured at hourly intervals for 24 h in 27 nonobese individuals—9 with normal glucose tolerance, 9 with mild non-insulin-dependent diabetes mellitus (NIDDM, fasting plasma glucose < 175 mg/dl), and 9 with severe NIDDM (fasting plasma glucose > 250 mg/dl). In addition, hepatic glucose production (HGP) was measured from midnight to 0800 in normal individuals and patients with severe NIDDM. Plasma glucose concentration was highest in patients with severe NIDDM, lowest in those with normal glucose tolerance, and intermediate in those with mild NIDDM (two-way ANOVA, P < .001). Variations in plasma FFA and lactate levels of the three groups were qualitatively similar, with lowest concentrations seen in normal individuals, intermediate levels in the group with mild NIDDM, and the highest concentration in those with severe NIDDM (two-way ANOVA, P < .001). Of particular interest was the observation that plasma FFA concentrations were dramatically elevated from midnight to 0800 in patients with severe NIDDM. The 24-h insulin response was significantly increased in patients with mild NIDDM, with comparable values seen in the other two groups. Values for HGP fell progressively throughout the night in normal individuals and patients with severe NIDDM, despite a concomitant decline in plasma glucose and insulin levels. Although the magnitude of the fall in HGP was greater in NIDDM, the absolute value was significantly (P < .001) greater than normal throughout the period of observation. These results demonstrate that there are differences in substrate level between individuals with normal glucose tolerance and patients with NIDDM and differing degrees of glucose intolerance, unrelated to ambient insulin level, and these changes persist over 24 h.

Metabolic Syndrome Pathophysiology and Implications for Management of Cardiovascular Disease

Case Presentation: E.C. is a 53-year-old postmenopausal female, referred for treatment of hypertension, with a family history of type 2 diabetes, hypertension, and coronary heart disease (CHD). Until learning that her blood pressure was “too high” during a routine physical examination, she felt well, and her postmenopausal symptoms had responded to hormone replacement therapy. She was not overweight (her body mass index [BMI] was 23.7 kg/m2), and the only abnormality on physical examination was a blood pressure of 145/95 RAR. Laboratory results revealed a normal blood count and urinalysis, with the following fasting plasma concentrations of relevant metabolic variables (in mg/dL): glucose 102, triglycerides (TG) 238, low-density lipoprotein cholesterol (LDL-C) 147, and high-density lipoprotein cholesterol (HDL-C) 52. E.C. is hypertensive and hypertriglyceridemic and at increased risk for CHD. Less obvious is that these metabolic abnormalities are highly likely to be the manifestations of a more fundamental defect—resistance to insulin-mediated glucose disposal and compensatory hyperinsulinemia, changes that greatly increase CHD risk.1,2⇓ The importance of insulin resistance as a CHD risk factor was first explicated in 1998, and the cluster of abnormalities likely to appear as manifestations of the defect in insulin action designated as syndrome X.1 Support for this notion has grown almost as fast as the names used to describe the phenomenon. The Adult Treatment Panel III (ATP III) has recently3 recognized the importance as CHD risk factors of a “constellation of lipid and nonlipid risk factors of metabolic origin,” designated this cluster of abnormalities as “the metabolic syndrome,” and indicated that “this syndrome is closely linked to insulin resistance.” Table 1 lists the criteria the ATP III stipulated be used to diagnose the metabolic syndrome, and a recent report4 has applied these criteria to the database of the Third National Health and Nutrition …

Relationship between obesity, insulin resistance, and coronary heart disease risk.

OBJECTIVES The study goals were to: 1) define the relationship between body mass index (BMI) and insulin resistance in 314 nondiabetic, normotensive, healthy volunteers; and 2) determine the relationship between each of these two variables and coronary heart disease (CHD) risk factors. BACKGROUND The importance of obesity as a risk factor for type 2 diabetes and hypertension is well-recognized, but its role as a CHD risk factor in nondiabetic, normotensive individuals is less well established. METHODS Insulin resistance was quantified by determining the steady-state plasma glucose (SSPG) concentration during the last 30 min of a 180-min infusion of octreotide, glucose, and insulin. In addition, nine CHD risk factors: age, systolic blood pressure, diastolic blood pressure (DBP), total cholesterol, triglycerides (TG), high-density lipoprotein (HDL) cholesterol and low-density lipoprotein cholesterol concentrations, and glucose and insulin responses to a 75-g oral glucose load were measured in the volunteers. RESULTS The BMI and the SSPG concentration were significantly related (r = 0.465, p < 0.001). The BMI and SSPG were both independently associated with each of the nine risk factors. In multiple regression analysis, SSPG concentration added modest to substantial power to BMI with regard to the prediction of DBP, HDL cholesterol and TG concentrations, and the glucose and insulin responses. CONCLUSIONS Obesity and insulin resistance are both powerful predictors of CHD risk, and insulin resistance at any given degree of obesity accentuates the risk of CHD and type 2 diabetes.