A. S. Rudenski

Bio: A. S. Rudenski is an academic researcher from University of Oxford. The author has contributed to research in topics: Insulin & Diabetes mellitus. The author has an hindex of 13, co-authored 19 publications receiving 28035 citations.

Homeostasis model assessment : insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man

Abstract: The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.

Continuous infusion of glucose with model assessment: measurement of insulin resistance and beta-cell function in man.

Abstract: Continuous infusion of glucose with model assessment (CIGMA) is a new method of assessing glucose tolerance, insulin resistance and beta-cell function. It consists of a continuous glucose infusion 5 mg glucose/kg ideal body weight per min for 60 min, with measurement of plasma glucose and insulin concentrations. These are similar to postprandial levels, change slowly, and depend on the dynamic interaction between the insulin produced and its effect on glucose turnover. The concentrations can be interpreted using a mathematical model of glucose and insulin homeostasis to assess insulin resistance and beta-cell function. In 23 subjects (12 normal and 11 with Type 2 (non-insulin-dependent diabetes) the insulin resistance measured by CIGMA correlated with that measured independently by euglycaemic clamp (Rs = 0.87, p less than 0.0001). With normal insulin resistance defined as 1, the median resistance in normal subjects was 1.35 by CIGMA and 1.39 by clamp, and in diabetic patients 4.0 by CIGMA and 3.96 by clamp. In 21 subjects (10 normal and 11 Type 2 diabetic) the beta-cell function measured by CIGMA correlated with steady-state plasma insulin levels during hyperglycaemic clamp at 10 mmol/l (Rs = 0.64, p less than 0.002). The CIGMA coefficient of variability was 21% for resistance and 19% for beta-cell function. CIGMA is a simple, non-labour-intensive method for assessing insulin resistance and beta-cell function in normal and Type 2 diabetic subjects who do not have glycosuria during the test.

Similar reduction of first- and second-phase B-cell responses at three different glucose levels in type II diabetes and the effect of gliclazide therapy.

Abstract: To characterize the abnormal B-cell response to glucose in type II diabetes, five diet-treated diabetic and six weight-matched non-diabetic subjects were studied using the hyperglycemic clamp technique on three separate days at glycemic levels of 7.5, 10 and 15 mmol/L for 150 minutes with assessment of plasma insulin and C-peptide responses. To reduce possible secondary effects of hyperglycemia, diabetic subjects on a weight-maintaining diet were chosen who had only a slight elevation of the fasting plasma glucose, mean 6.0 mmol/L. They had a normal time-course of both first- and second-phase responses, but both were impaired at each glucose clamp concentration. The first-phase and second-phase C-peptide responses of the diabetic subjects were similarly reduced to mean 49% and 59% of normal, respectively, and the first- and second-phase insulin responses were also reduced to mean 39% and 44% of normal, respectively. The ratio of second- to first-phase plasma C-peptide responses were similar in the diabetic and normal subjects, median 1.6 and 1.5, respectively, as were the same ratios for the insulin responses, 1.4 and 1.1, respectively. The previously described selective reduction of the first-phase response in type II diabetes may be partly a function of the bolus intravenous glucose tests used, in which impaired glucose tolerance in the diabetics gave a greater glycemic stimulus to the second phase than in normal subjects, and partly secondary to long-term hyperglycemia. The diabetic subjects were re-studied after treatment with a sulphonylurea, gliclazide, with a normal fasting plasma glucose, mean 5.1 mmol/L.(ABSTRACT TRUNCATED AT 250 WORDS)

Understanding “insulin resistance”: Both glucose resistance and insulin resistance are required to model human diabetes

Abstract: A mathematical model of normal glucose/insulin homoeostasis has been based on the known, experimentally determined responses of the liver and periphery to different glucose/insulin concentrations. Different defects of glucose resistance and insulin resistance have been applied to the model to investigate the degree to which these abnormalities could successfully predict the range of fasting glucose and insulin values found in normal, obese, and diabetic subjects. Modeling glucose resistance or insulin resistance at the liver or the periphery alone did not increase the plasma glucose to levels observed in diabetes, even when associated with marked deficiency of beta-cell function. A defect of either glucose resistance or insulin resistance affecting both periphery and liver allowed a wider range of basal glucose and insulin concentration values, but resulted in unphysiologically low hepatic glucose output: with modeling insulin resistance, hyperglycemia suppressed glucose output, whereas with glucose resistance, raised insulin levels suppressed hepatic glucose output. A wide range of glucose and insulin values, with appropriate basal hepatic glucose output, could only be modeled by insulin resistance at both the liver and periphery with additional glucose resistance at the liver. The modeling results are in accord with investigative studies that suggest secondary hepatic and peripheral glucose resistance in response to hyperglycemia. Modeling provides a systematic means of examining the likely effect of different putative defects in a complex physiological system.

Homeostasis model assessment : insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man

Abstract: The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.

Magnesium Replacement Improves the Metabolic Profile in Obese and Pre-Diabetic Patients with Mild-to-Moderate Chronic Kidney Disease: A 3-Month, Randomised, Double-Blind, Placebo-Controlled Study

Abstract: Background/Aims: Magnesium is an essential mineral for many metabolic functions. There is very little information on the effect of magnesium supplementation on me

Use and Abuse of HOMA Modeling

Abstract: Homeostatic model assessment (HOMA) is a method for assessing beta-cell function and insulin resistance (IR) from basal (fasting) glucose and insulin or C-peptide concentrations. It has been reported in >500 publications, 20 times more frequently for the estimation of IR than beta-cell function. This article summarizes the physiological basis of HOMA, a structural model of steady-state insulin and glucose domains, constructed from physiological dose responses of glucose uptake and insulin production. Hepatic and peripheral glucose efflux and uptake were modeled to be dependent on plasma glucose and insulin concentrations. Decreases in beta-cell function were modeled by changing the beta-cell response to plasma glucose concentrations. The original HOMA model was described in 1985 with a formula for approximate estimation. The computer model is available but has not been as widely used as the approximation formulae. HOMA has been validated against a variety of physiological methods. We review the use and reporting of HOMA in the literature and give guidance on its appropriate use (e.g., cohort and epidemiological studies) and inappropriate use (e.g., measuring beta-cell function in isolation). The HOMA model compares favorably with other models and has the advantage of requiring only a single plasma sample assayed for insulin and glucose. In conclusion, the HOMA model has become a widely used clinical and epidemiological tool and, when used appropriately, it can yield valuable data. However, as with all models, the primary input data need to be robust, and the data need to be interpreted carefully.

Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

Abstract: Insulin resistance plays an important role in the pathophysiology of diabetes and is associated with obesity and other cardiovascular risk factors. The “gold standard” glucose clamp and minimal model analysis are two established methods for determining insulin sensitivity in vivo, but neither is easily implemented in large studies. Thus, it is of interest to develop a simple, accurate method for assessing insulin sensitivity that is useful for clinical investigations. We performed both hyperinsulinemic isoglycemic glucose clamp and insulin-modified frequently sampled iv glucose tolerance tests on 28 non-obese, 13 obese, and 15 type 2 diabetic subjects. We obtained correlations between indexes of insulin sensitivity from glucose clamp studies (SIClamp) and minimal model analysis (SIMM) that were comparable to previous reports (r = 0.57). We performed a sensitivity analysis on our data and discovered that physiological steady state values [i.e. fasting insulin (I0) and glucose (G0)] contain critical informa...