METS-IR, a novel score to evaluate insulin sensitivity, is predictive of visceral adiposity and incident type 2 diabetes

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Objective

We developed a novel non-insulin-based fasting score to evaluate insulin sensitivity validated against the euglycemic–hyperinsulinemic clamp (EHC). We also evaluated its correlation with ectopic fact accumulation and its capacity to predict incident type 2 diabetes mellitus (T2D).

Design and methods

The discovery sample was composed by 125 subjects (57 without and 68 with T2D) that underwent an EHC. We defined METS-IR as Ln((2*G ₀)+TG ₀)*BMI)/(Ln(HDL-c)) (G ₀: fasting glucose, TG ₀: fasting triglycerides, BMI: body mass index, HDL-c: high-density lipoprotein cholesterol), and compared its diagnostic performance against the M-value adjusted by fat-free mass (MFFM) obtained by an EHC. METS-IR was validated in a sample with EHC data, a sample with modified frequently sampled intravenous glucose tolerance test (FSIVGTT) data and a large cohort against HOMA-IR. We evaluated the correlation of the score with intrahepatic and intrapancreatic fat measured using magnetic resonance spectroscopy. Subsequently, we evaluated its ability to predict incident T2D cases in a prospective validation cohort of 6144 subjects.

Results

METS-IR demonstrated the better correlation with the MFFM ( ρ = −0.622, P < 0.001) and diagnostic performance to detect impaired insulin sensitivity compared to both EHC (AUC: 0.84, 95% CI: 0.78–0.90) and the SI index obtained from the FSIVGTT (AUC: 0.67, 95% CI: 0.53–0.81). METS-IR significantly correlated with intravisceral, intrahepatic and intrapancreatic fat and fasting insulin levels ( P < 0.001). After a two-year follow-up, subjects with METS-IR in the highest quartile (>50.39) had the highest adjusted risk to develop T2D (HR: 3.91, 95% CI: 2.25–6.81). Furthermore, subjects with incident T2D had higher baseline METS-IR compared to healthy controls (50.2 ± 10.2 vs 44.7 ± 9.2, P < 0.001).

Conclusion

METS-IR is a novel score to evaluate cardiometabolic risk in healthy and at-risk subjects and a promising tool for screening of insulin sensitivity.

Related collections

Most cited references 30

Record: found
Abstract: found
Article: not found

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

S Nambi, K Mather, A. Katz … (2000)

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 nonobese, 13 obese, and 15 type 2 diabetic subjects. We obtained correlations between indexes of insulin sensitivity from glucose clamp studies (SI(Clamp)) and minimal model analysis (SI(MM)) 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 (I(0)) and glucose (G(0))] contain critical information about insulin sensitivity. We defined a quantitative insulin sensitivity check index (QUICKI = 1/[log(I(0)) + log(G(0))]) that has substantially better correlation with SI(Clamp) (r = 0.78) than the correlation we observed between SI(MM) and SI(Clamp). Moreover, we observed a comparable overall correlation between QUICKI and SI(Clamp) in a totally independent group of 21 obese and 14 nonobese subjects from another institution. We conclude that QUICKI is an index of insulin sensitivity obtained from a fasting blood sample that may be useful for clinical research.

0 comments Cited 840 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Glucose clamp technique: a method for quantifying insulin secretion and resistance.

J D Tobin, R. Andrés, R DeFronzo (1979)

Methods for the quantification of beta-cell sensitivity to glucose (hyperglycemic clamp technique) and of tissue sensitivity to insulin (euglycemic insulin clamp technique) are described. Hyperglycemic clamp technique. The plasma glucose concentration is acutely raised to 125 mg/dl above basal levels by a priming infusion of glucose. The desired hyperglycemic plateau is subsequently maintained by adjustment of a variable glucose infusion, based on the negative feedback principle. Because the plasma glucose concentration is held constant, the glucose infusion rate is an index of glucose metabolism. Under these conditions of constant hyperglycemia, the plasma insulin response is biphasic with an early burst of insulin release during the first 6 min followed by a gradually progressive increase in plasma insulin concentration. Euglycemic insulin clamp technique. The plasma insulin concentration is acutely raised and maintained at approximately 100 muU/ml by a prime-continuous infusion of insulin. The plasma glucose concentration is held constant at basal levels by a variable glucose infusion using the negative feedback principle. Under these steady-state conditions of euglycemia, the glucose infusion rate equals glucose uptake by all the tissues in the body and is therefore a measure of tissue sensitivity to exogenous insulin.

0 comments Cited 425 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals

Leay-Kiaw Er, Semon Wu, Hsin-Hua Chou … (2016)

Background Insulin resistance (IR) and the consequences of compensatory hyperinsulinemia are pathogenic factors for a set of metabolic abnormalities, which contribute to the development of diabetes mellitus and cardiovascular diseases. We compared traditional lipid levels and ratios and combined them with fasting plasma glucose (FPG) levels or adiposity status for determining their efficiency as independent risk factors for IR. Methods We enrolled 511 Taiwanese individuals for the analysis. The clinical usefulness of various parameters—such as traditional lipid levels and ratios; visceral adiposity indicators, visceral adiposity index (VAI), and lipid accumulation product (LAP); the product of triglyceride (TG) and FPG (the TyG index); TyG with adiposity status (TyG-body mass index [BMI]) and TyG-waist circumference index [WC]); and adipokine levels and ratios—was analyzed to identify IR. Results For all lipid ratios, the TG/high-density lipoprotein cholesterol (HDL-C) ratio had the highest additional percentage of variation in the homeostasis model assessment of insulin resistance (HOMA-IR; 7.0% in total); for all variables of interest, TyG-BMI and leptin-adiponectin ratio (LAR) were strongly associated with HOMA-IR, with 16.6% and 23.2% of variability, respectively. A logistic regression analysis revealed similar patterns. A receiver operating characteristic (ROC) curve analysis indicated that TG/HDL-C was a more efficient IR discriminator than other lipid variables or ratios. The area under the ROC curve (AUC) for VAI (0.734) and TyG (0.708) was larger than that for TG/HDL-C (0.707). TyG-BMI and LAR had the largest AUC (0.801 and 0.801, respectively). Conclusion TyG-BMI is a simple, powerful, and clinically useful surrogate marker for early identification of IR.

0 comments Cited 251 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Title: European Journal of Endocrinology

Publisher: Bioscientifica

ISSN (Print): 0804-4643

ISSN (Electronic): 1479-683X

Publication date Created: May 2018

Publication date (Print): May 2018

Volume: 178

Issue: 5

Pages: 533-544

Article

DOI: 10.1530/EJE-17-0883

PubMed ID: 29535168

SO-VID: ace20285-6121-4fc2-855f-18e413004179

License:

Free to read

History

Data availability:

Comments

Comment on this article

scite_

314

402

Smart Citations

314

402

Citing PublicationsSupportingMentioningContrasting

View Citations

See how this article has been cited at scite.ai

scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.