Original articleA 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
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).
References (26)
- et al.
Surrogate indexes vs. euglycaemic-hyperinsulinemic clamp as an indicator of insulin resistance and cardiovascular risk factors in overweight and obese postmenopausal women
Diabetes Metab
(2006) - et al.
The metabolic syndrome-a new worldwide definition
Lancet
(2005) - et al.
Accuracy of the ratio of triglycerides to high-density lipoprotein cholesterol for predicting low-density lipoprotein cholesterol particle sizes, phenotype B, and particle concentrations among Asian Indians
Am J Cardiol
(2006) Banting lecture 1988. Role of insulin resistance in human disease
Diabetes
(1988)- et al.
Glucose clamp technique: a method for quantifying insulin secretion and resistance
Am J Physiol
(1979) - et al.
Relationship between several surrogate estimates of insulin resistance and quantification of insulin-mediated glucose disposal in 490 healthy nondiabetic volunteers
Diabetes Care
(2000) - et al.
Diagnosing insulin resistance in the general population
Diabetes Care
(2001) - et al.
The EGIR-RISC STUDY (The European group for the study of insulin resistance: relationship between insulin sensitivity and cardiovascular disease risk): I. Methodology and objectives
Diabetologia
(2004) - Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 1997;...
- et al.
Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation
Diabet Med
(1998)
Regulation by insulin of gene expression in human skeletal muscle and adipose tissue. Evidence for specific defects in type 2 diabetes
Diabetes
How to measure insulin sensitivity
J Hypertens
Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man
Diabetologia
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Surrogate measures of insulin sensitivity when compared to euglycemic hyperinsulinemic clamp studies in Asian Indian men without diabetes
2016, Journal of Diabetes and its ComplicationsCitation Excerpt :Zaletel et al. (2010) showed that FGIR in patients with type 2 diabetes was not better than other indices. But studies in subjects without diabetes showed that FGIR was at least as good as other fasting surrogate indices when compared with the euglycemic hyperinsulinemic clamp study (Disse et al., 2008; Ijzerman et al., 2009). As the physiology of insulin secretion and action varies significantly among subjects with and without diabetes, it is possible that different surrogate indices may be appropriate in different groups of patients.
How can we measure insulin sensitivity/resistance?
2011, Diabetes and MetabolismCitation Excerpt :Indeed, among the variables tested, fasting insulin, NEFA and the HDL cholesterol/total cholesterol ratio explained 53% of the variation of insulin sensitivity, expressed as MFFM/I. We also derived a simplified formula from the regression equation, the Disse index: 12 × {2.5 × [HDL-cholesterol (mmol/L)/total cholesterol (mmol/L)]–NEFA (mmol/lL)}–insulinaemia (μIU/mlmL) [75]. The Disse index was highly correlated with MFFM/I (r = 0.79, P < 0.001), and there was good agreement between the two methods.
Evaluation of the SIisOGTT index in a healthy population with normal glucose tolerance
2009, Diabetes and MetabolismDifferential performance of surrogate indices of fasting insulin resistance in low-birthweight and normal-birth weight cohorts: Observations from Hyperinsulinaemic-Euglycaemic clamp studies in young, Asian Indian males
2019, Diabetes and Metabolic Syndrome: Clinical Research and ReviewsCitation Excerpt :Moreover, our study on Asian Indian males has validated surrogate indices of insulin resistance/sensitivity in comparison to the M value obtained from HEC procedure. It has been reported that the FG-IR is better than HOMA-IR as a surrogate index of insulin resistance, when applied in normoglycaemic subjects [18] and compared to diabetic subjects [19]. An important observation in this study is the consistent positive correlations of FG-IR with M value in the low birth weight cohort before and after adjustment for confounders.