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  • Title: The natural logarithm of zinc-α2-glycoprotein/HOMA-IR is a better predictor of insulin sensitivity than the product of triglycerides and glucose and the other lipid ratios.
    Author: Qu C, Zhou X, Yang G, Li L, Liu H, Liang Z.
    Journal: Cytokine; 2016 Mar; 79():96-102. PubMed ID: 26797477.
    Abstract:
    AIM: The euglycemic-hyperinsulinemic clamp (EHC) is not available in most clinical settings and is costly, time consuming and invasive, and requires trained staff. Therefore, an accessible and inexpensive test to identify insulin resistance (IR) is needed. The aim of this study is to assess whether zinc-α2-glycoprotein (ZAG) index [Ln ZAG/homeostasis model assessment of IR (HOMA-IR)] is a better surrogate index for estimating IR or metabolic syndrome (MetS) compared with other surrogate indices. METHODS: We performed a population-based cross-sectional study. Two hundred healthy subjects, 102 polycystic ovary syndrome (PCOS) patients, 97 newly diagnosed type 2 diabetes mellitus (nT2DM) and 84 impaired glucose tolerance (IGT) subjects were enrolled. The EHC was performed to identify IR. Circulating ZAG and adiponectin levels were determined by ELISA. RESULTS: The ZAG index was significantly lower in participants with IR including IGT, nT2DM and PCOS than in those without IR. In addition, subjects with MetS had lower ZAG indices and higher the product of fasting triglycerides and glucose (TyG) indices than those without MetS. The ZAG index showed a significantly stronger association with M values than the other surrogate indices, whereas the TyG index showed a stronger association with MetS. The optimal cutoff value of the ZAG index for detection of IR was 2.97 with a sensitivity of 88% and a specificity of 91%, whereas the optimal cutoff value of TyG index for detection of MetS was 4.90 with a sensitivity of 82% and a specificity of 86%. CONCLUSION: The ZAG index is a better marker than the other surrogate indices for identifying IR, whereas the TyG index has high sensitivity and specificity for identifying MetS.
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