ABSTRACT
BACKGROUND: Insulin resistance (IR) can precede the dysglycemic states of prediabetes and type 2 diabetes mellitus (T2DM) by a number of years and is an early marker of risk for metabolic and cardiovascular disease. There is an unmet need for a simple method to measure IR that can be used for routine screening, prospective study, risk assessment, and therapeutic monitoring. We have reported several metabolites whose fasting plasma levels correlated with insulin sensitivity. These metabolites were used in the development of a novel test for IR and prediabetes. METHODS: Data from the Relationship between Insulin Sensitivity and Cardiovascular Disease Study were used in an iterative process of algorithm development to define the best combination of metabolites for predicting the M value derived from the hyperinsulinemic euglycemic clamp, the gold standard measure of IR. Subjects were divided into a training set and a test set for algorithm development and validation. The resulting calculated M score, M(Q), was utilized to predict IR and the risk of progressing from normal glucose tolerance to impaired glucose tolerance (IGT) over a 3 year period. RESULTS: M(Q) correlated with actual M values, with an r value of 0.66. In addition, the test detects IR and predicts 3 year IGT progression with areas under the curve of 0.79 and 0.70, respectively, outperforming other simple measures such as fasting insulin, fasting glucose, homeostatic model assessment of IR, or body mass index. CONCLUSIONS: The result, Quantose(TM), is a simple test for IR based on a single fasting blood sample and may have value as an early indicator of risk for the development of prediabetes and T2DM.
Subject(s)
Blood Glucose/metabolism , Insulin Resistance , Prediabetic State/blood , Adult , Algorithms , Area Under Curve , Blood Glucose/analysis , Fasting/blood , Female , Humans , Insulin/blood , Male , Middle AgedABSTRACT
BACKGROUND: Insulin resistance is a risk factor for type 2 diabetes and cardiovascular disease progression. Current diagnostic tests, such as glycemic indicators, have limitations in the early detection of insulin resistant individuals. We searched for novel biomarkers identifying these at-risk subjects. METHODS: Using mass spectrometry, non-targeted biochemical profiling was conducted in a cohort of 399 nondiabetic subjects representing a broad spectrum of insulin sensitivity and glucose tolerance (based on the hyperinsulinemic euglycemic clamp and oral glucose tolerance testing, respectively). RESULTS: Random forest statistical analysis selected alpha-hydroxybutyrate (alpha-HB) as the top-ranked biochemical for separating insulin resistant (lower third of the clamp-derived M(FFM) = 33 [12] micromol x min(-1) x kg(FFM) (-1), median [interquartile range], n = 140) from insulin sensitive subjects (M(FFM) = 66 [23] micromol x min(-1) x kg(FFM) (-1)) with a 76% accuracy. By targeted isotope dilution assay, plasma alpha-HB concentrations were reciprocally related to M(FFM); and by partition analysis, an alpha-HB value of 5 microg/ml was found to best separate insulin resistant from insulin sensitive subjects. alpha-HB also separated subjects with normal glucose tolerance from those with impaired fasting glycemia or impaired glucose tolerance independently of, and in an additive fashion to, insulin resistance. These associations were also independent of sex, age and BMI. Other metabolites from this global analysis that significantly correlated to insulin sensitivity included certain organic acid, amino acid, lysophospholipid, acylcarnitine and fatty acid species. Several metabolites are intermediates related to alpha-HB metabolism and biosynthesis. CONCLUSIONS: alpha-hydroxybutyrate is an early marker for both insulin resistance and impaired glucose regulation. The underlying biochemical mechanisms may involve increased lipid oxidation and oxidative stress.