The metabolic syndrome

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

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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

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.

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Use and Abuse of HOMA Modeling

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...

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

We are facing a global metabolic health crisis provoked by an obesity epidemic. Here we report the human gut microbial composition in a population sample of 123 non-obese and 169 obese Danish individuals. We find two groups of individuals that differ by the number of gut microbial genes and thus gut bacterial richness. They contain known and previously unknown bacterial species at different proportions; individuals with a low bacterial richness (23% of the population) are characterized by more marked overall adiposity, insulin resistance and dyslipidaemia and a more pronounced inflammatory phenotype when compared with high bacterial richness individuals. The obese individuals among the lower bacterial richness group also gain more weight over time. Only a few bacterial species are sufficient to distinguish between individuals with high and low bacterial richness, and even between lean and obese participants. Our classifications based on variation in the gut microbiome identify subsets of individuals in the general white adult population who may be at increased risk of progressing to adiposity-associated co-morbidities.

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Richness of human gut microbiome correlates with metabolic markers

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.

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

A soluble-phase proinsulin assay has been developed which does not require solid-phase antibody-binding. A human proinsulin standard curve is prepared in insulin-free and proinsulin-free plasma for comparison with unknown plasma samples. Proinsulin and insulin are bound with excess anti-insulin antiserum, and free C-peptide is removed by charcoal adsorption. The supernatant is then assayed using a routine C-peptide radioimmunoassay which utilises anti-C-peptide antiserum. The sensitivity of the assay (2 standard deviations above zero) is 9 pmol/L using 200 microL plasma sample. The assay is free from insulin cross-reactivity up to 100 mU/L and C-peptide up to 2000 pmol/L. Between-assay CV is 13% at 100 pmol/L. The assay has been used in subjects with hypoglycaemia of various aetiologies and has shown that a raised plasma proinsulin in the presence of hypoglycaemia can occur in sulphonylurea-induced and reactive hypoglycaemia as well as in insulinomas. After hyperglycaemic clamps at 7.5, 10 and 15 mmol/L glucose, type II diabetics both on and off sulphonylurea, were found to have lower proinsulin concentrations compared with normal subjects, commensurate with the diabetics' lower insulin responses.

B. A. Naylor

Papers

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

A soluble-phase proinsulin radioimmunoassay and its use in diagnosis of hypoglycaemia.