Elsevier

Diabetes & Metabolism

Volume 34, Issue 5, November 2008, Pages 457-463
Diabetes & Metabolism

Original article
A lipid-parameter-based index for estimating insulin sensitivity and identifying insulin resistance in a healthy populationUn index établi sur des paramètres lipidiques permet l’estimation de la sensibilité à l’insuline et le diagnostic de l’insulinorésistance dans une population saine

https://doi.org/10.1016/j.diabet.2008.02.009Get rights and content

Abstract

Aim

Insulin resistance needs to be identified as early as possible in its development to allow targeted prevention programmes. Therefore, we compared various fasting surrogate indices for insulin sensitivity using the euglycaemic insulin clamp in an attempt to develop the most appropriate method for assessing insulin resistance in a healthy population.

Methods

Glucose, insulin, proinsulin, glucagon, glucose tolerance, fasting lipids, liver enzymes, blood pressure, anthropometric parameters and insulin sensitivity (Mffm/I) using the euglycaemic insulin clamp were obtained for 70 normoglycaemic non-obese individuals. Spearman’s rank correlations were used to examine the association between Mffm/I and various fasting surrogate indices of insulin sensitivity. A regression model was used to determine the weighting for each variable and to derive a formula for estimating insulin resistance. The clinical value of the surrogate indices and the new formula for identifying insulin-resistant individuals was evaluated by the use of receiver operating characteristic (ROC) curves.

Results

The variables that best predicted insulin sensitivity were the HDL-to-total cholesterol ratio, the fasting NEFA and fasting insulin. The use of the lipid-parameter-based formula Mffm/I = 12 × [2.5 × (HDL-c/total cholesterol)  NEFA] – fasting insulin appeared to have high clinical value in predicting insulin resistance. The correlation coefficient between Mffm/I and the new fasting index was higher than those with the most commonly used fasting surrogate indices for insulin sensitivity.

Conclusion

A lipid-parameter-based index using fasting samples provides a simple means of screening for insulin resistance in the healthy population.

Résumé

But

L’insulinorésistance doit être identifiée précocement de manière à cibler les populations pouvant bénéficier de stratégies préventives. En conséquence, nous avons comparé, dans une population saine, divers index d’insulinosensibilité/résistance avec le clamp euglycémique hyperinsulinémique et nous avons essayé de développer la méthode la plus appropriée pour dépister l’insulinorésistance dans une telle population.

Méthodes

La glycémie, l’insulinémie, la tolérance au glucose, le bilan lipidique, le bilan hépatique, la pression artérielle, les paramètres anthropométriques et la sensibilité à l’insuline (Mffm/I) quantifiée par le clamp euglycémique hyperinsulinémique, ont été obtenus pour 70 sujets normoglycémiques et non obèses. Le test de rang de Spearman a été utilisé pour déterminer les corrélations entre Mffm/I et les index d’insulinosensibilité. Un modèle de régression a été utilisé pour déterminer le poids de chaque variable et dériver une formule estimant au mieux l’insulinorésistance. La valeur clinique des index et de cette nouvelle formule pour identifier les sujets insulinorésistants a été évaluée par une analyse receiver operating characteristic (ROC).

Résultats

Les variables les plus utiles pour la prédiction de la sensibilité à l’insuline dans notre population saine sont le rapport HDL sur cholestérol total, le niveau d’acides gras libres plasmatique et l’insulinémie à jeun. La formule fondée sur les paramètres lipidiques : [M ffm/I = 12 × (2,5 × (HDL-c/total cholesterol) – AGL) – Insulinémie à jeun] présente une forte valeur clinique prédictive de l’insulinorésistance. Le coefficient de corrélation entre Mffm/I et ce nouvel index est plus élevé que ceux des index habituellement utilisés pour estimer la sensibilité à l’insuline.

Conclusion

Un index fondé sur des paramètres lipidiques à jeun est un moyen simple de réaliser un dépistage de l’insulinorésistance dans une population considérée comme saine.

Introduction

Insulin resistance is a major risk factor for type 2 diabetes and is frequently associated with cardiovascular disease (CVD) [1]. Early screening for insulin resistance could be of value as a way of monitoring populations with a high metabolic risk before the emergence of the classical markers of the ‘metabolic syndrome’. At present, the gold standard for measuring and quantifying insulin resistance is the hyperinsulinaemic euglycaemic clamp [2]. However, in clinical practice, this method is difficult and impractical. Therefore, a number of surrogate indices for insulin sensitivity has been developed, derived from fasting glucose and insulin levels, or based on the oral glucose tolerance test. Clearly, the reliability of these surrogate indices depends on the degree to which they correlate with direct measurements of insulin activity. In a healthy non diabetic population, surrogates of insulin action are not sufficiently efficient and do not appear to offer advantages over fasting plasma insulin concentration [3], [4], [5]. However, fasting plasma insulin measurement is not sensitive enough to be used as a tool for insulin-resistance screening in the apparently healthy population.

In the present study, we attempted to develop a simple and sensitive estimate of insulin resistance in a non obese normoglucose-tolerant population by using several metabolic markers in addition to measures of insulin.

Section snippets

Methods

A population of 70 subjects from the EGIR-RISC study cohort [6], corresponding to all of the subjects tested at the Human Nutrition Research Centre of Rhône-Alpes, was selected for this study. To be included in the study, subjects had to have a normal medical history, be clinically healthy, have a fasting plasma glucose less than 7.0 mmol/L (126 mg/dL), have a two-hour plasma glucose less than 11.1 mmol/L (200 mg/dL), and undergo a physical examination and routine clinical laboratory tests together

Results

The baseline characteristics of the subjects are presented in Table 1. By study design, all subjects were glucose–tolerant, and displayed a normal lipid profile and liver-enzyme status. Despite the homogeneity of the baseline characteristics of our study population, we observed a wide range of insulin-sensitivity values as assessed by the hyperinsulinaemic euglycaemic clamp (Fig. 1). As expected, when separating subjects according to their insulin-sensitive status as defined above, we found

Discussion

Quantifying insulin sensitivity and identifying insulin-resistant subjects in an apparently healthy non diabetic population is crucial for the development of prevention programmes to delay progression towards diabetes and cardiovascular complications. Several surrogate indices to estimate insulin action have been developed to quantify insulin sensitivity easily. These indices are based on fasting plasma insulin and glucose levels [11], [12], [13], or on OGTT results [15], [16]. It has been

Conclusion

Identifying and quantifying insulin resistance in apparently healthy populations offers the possibility of preventing the metabolic syndrome and its cardiovascular complications. We have developed a simple and accurate tool, based on lipid parameters, to assess insulin resistance from fasting blood samples. This index needs to be validated in a large cohort of healthy subjects and in other non diabetic populations. New prospective studies should be undertaken to determine if the formula

Acknowledgements

The RISC Study is partly supported by EU grant QLG1-CT-2001-01252. Additional support was provided by AstraZeneca (Sweden).

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