Using common clinical data improves the prediction of abnormal glucose tolerance by the new criteria of impaired fasting glucose: Tehran lipid and glucose study

A novel test for IGT utilizing metabolite markers of glucose tolerance

The oral glucose tolerance test (OGTT) is the only method to diagnose patients having impaired glucose tolerance (IGT), but its use has diminished considerably in recent years. Metabolomic profiling studies have identified a number of metabolites whose fasting levels are associated with dysglycemia and type 2 diabetes. These metabolites may serve as the basis of an alternative test for IGT. Using the stable isotope dilution technique, quantitative assays were developed for 23 candidate biomarker metabolites. These metabolites were measured in fasting plasma samples taken just prior to an OGTT from 1623 nondiabetic subjects: 955 from the Relationship between Insulin Sensitivity and Cardiovascular Disease Study (RISC Study; 11.7% IGT) and 668 subjects from the Diabetes Mellitus and Vascular Health Initiative (DMVhi) cohort from the DEXLIFE project (11.8% IGT). The associations between metabolites, anthropometric, and metabolic parameters and 2hPG values were assessed by Pearson correlation coefficients and Random Forest classification analysis to rank variables for their ability to distinguish IGT from normal glucose tolerance (NGT). Multivariate logistic regression models for estimating risk of IGT were developed and evaluated using AUCs calculated from the corresponding ROC curves. A model based on the fasting plasma levels of glucose, α-hydroxybutyric acid, β-hydroxybutyric acid, 4-methyl-2-oxopentanoic acid, linoleoylglycerophosphocholine, oleic acid, serine and vitamin B5 was optimized in the RISC cohort (AUC = 0.82) and validated in the DMVhi cohort (AUC = 0.83). A novel, all-metabolite-based test is shown to be a discriminate marker of IGT. It requires only a single fasted blood draw and may serve as a more convenient surrogate for the OGTT or as a means of identifying subjects likely to be IGT.

Impaired fasting glucose cutoff value of 5.6 mmol/l combined with other cardiovascular risk markers is a better predictor for incident Type 2 diabetes than the 6.1 mmol/l value: Tehran lipid and glucose study

OBJECTIVE

To investigate whether cutoff value of 5.6 mmol/l for impaired fasting glucose (IFG) improves the prediction of Type 2 diabetes mellitus (T2DM) in comparison to the 6.1 mmol/l value.

RESEARCH DESIGN AND METHODS

A total of 5794 non-diabetic subjects aged 42+/-13 years were followed for 6.5 years. T2DM was defined based on the WHO 1999 criteria. Cox regression analysis was used to calculate the relative risk (RR) of developing T2DM. Model discrimination was assessed by calculating the area under the receiver operating characteristic curve (AUC).

RESULTS

During the follow-up, there were 351 incident T2DM. The RR (95% CI) of the 6.1 and 5.6 mmol/l cutoffs were comparable in both univariate and multivariate analysis [9.6 (7.5-12.3) vs. 8.4 (6.4-10.0), respectively in univariate and 2.4 (1.8-3.2) vs. 3.3 (2.6-4.2), respectively in multivariate models]. Using the 5.6 mmol/l cutoff value in the multivariate model significantly improved its discrimination in comparison to the 6.1 mmol/l value [AUC (95% CI): 0.78 (0.74-0.83) vs. 0.74 (0.70-0.79), P<0.01]. Models with impaired glucose tolerance and fasting glucose had the highest AUC of 0.81(95% CI: 0.78-0.85).

CONCLUSIONS

The 5.6 mmol/l cutoff value of IFG combined with other diabetes risk factors performs significantly better than the 6.1 mmol/l value for prediction of future T2DM.

The metabolic syndrome and incident diabetes: Assessment of alternative definitions of the metabolic syndrome in an Iranian urban population

AIMS

To compare the ability of definitions of Metabolic Syndrome (MetS) in the prediction of type 2 diabetes.

METHODS

We examined 4756 subjects in an Iranian population who were non-diabetic at baseline. After 3.6 years, 188 individuals developed diabetes.

RESULTS

Impaired glucose tolerance (IGT) and MetS definitions predicted type 2 diabetes with odds ratios ranging from 3.7 to 11.9 (all P<0.05) although IGT had the highest area under the receiver operator characteristic (aROC) curve than all the MetS definitions. Reduction of glucose in the National Cholesterol Education Program (NCEP) definition of the MetS increased diabetes prediction, but adding the family history of diabetes did not change aROC curves. The International Diabetes Federation (IDF) definition had the highest sensitivity and false positive rate (72.2 and 35.1%, respectively) and the WHO definition had the lowest ones (54.8 and 9.2%, respectively) for predicting diabetes. The positive predictive values of all definitions were low (8.6-19.7%) but their negative predictive values were around 98%.

CONCLUSIONS

In Iranian population, the MetS was inferior to IGT for predicting type 2 diabetes. The NCEP definition of the MetS with reduced level of glucose (not including the family history of diabetes) and IDF definition predicted type 2 diabetes at least as well as WHO definition.