Lipoprotein heterogeneity may help to detect individuals with insulin resistance.

Abstract

The triacylglycerol (TG)-to-HDL-cholesterol ratio has been shown to detect insulin resistance. However, the added predictive value of a more comprehensive assessment of lipoprotein composition is unknown. We analysed cross-sectional data from 882 non-diabetic participants in the Insulin Resistance Atherosclerosis Study (IRAS). Lipoproteins were measured by nuclear magnetic resonance (NMR) spectroscopy. Determined by the frequently sampled intravenous glucose tolerance test, insulin resistance was defined as the lowest sex-specific quartile of insulin sensitivity. The AUC of the receiver operating characteristic curve of HDL-cholesterol and TG levels for detecting insulin resistance was similar to that of the TG-to-HDL-cholesterol ratio (0.676 vs 0.673; p = 0.685), but smaller than the AUC of NMR-detected lipoproteins (0.676 vs 0.745; p < 0.001). NMR lipoproteins added discriminative value to HDL-cholesterol and TG levels (net reclassification improvement of 40.0%; p < 0.001; and integrated discrimination improvement of 9.5%; p < 0.001), with net benefit within predicted probabilities of between 10% and 50% by Vickers' decision-curve analysis. We also demonstrated additive value to demographic variables, BMI and levels of fasting glucose, TG, and HDL-cholesterol (net reclassification improvement of 14.0%; p < 0.001; and integrated discrimination improvement of 4.5%; p < 0.001). NMR lipoproteins, which can be measured in the fasting state, add information to the TG and HDL-cholesterol ratio across a broad range on insulin resistance. Depending on the other risk factors of insulin resistance that are incorporated, NMR lipoproteins permit the correct reclassification of an additional 14-40% of individuals.