Annals of Clinical Nutrition and Metabolism

Original Articles

Triglyceride-glucose index predicts future metabolic syndrome in an adult population, Korea: a prospective cohort study: Min-Su Park; Ann Clin Nutr Metab 2024;16(3):168-172. Published online December 1, 2024; DOI: https://doi.org/10.15747/ACNM.2024.16.3.168

Abstract PDF: Purpose: The triglyceride-glucose (TyG) index has been proposed as a reliable surrogate marker for insulin resistance. This study aimed to assess the utility of the TyG index in predicting the future presence of metabolic syndrome (MetS) in an adult population.
Methods: A total of 3,241 adults aged 40–70 years were included in this cross-sectional study. MetS was diagnosed based on the modified National Cholesterol Education Program Adult Treatment Panel III criteria, which requires the presence of at least three of the following components: abdominal obesity, elevated blood pressure, dysglycemia, hypertriglyceridemia, and low high-density lipoprotein cholesterol.
Results: In comparison to the homeostasis model assessment of insulin resistance (HOMA-IR), the TyG index exhibited superior diagnostic performance, with a higher area under the receiver operating characteristic curve of 0.854 vs. 0.702 for HOMA-IR. The 95% confidence interval for the TyG index was narrower, reflecting a more consistent predictive ability. Sensitivity for the TyG index was 79.7%, while specificity was 79.3%, compared to HOMA-IR, which showed a sensitivity of 52.7% and specificity of 78.3%.
Conclusion: The TyG index is a highly effective and robust tool for identifying individuals at risk for MetS, demonstrating superior sensitivity and predictive accuracy over HOMA-IR. This index could be a valuable clinical marker for early detection of MetS, aiding in the prevention and management of associated metabolic disorders.

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Multi-biomarker approach to metabolic syndrome and associated diseases in Turkey: a cross sectional study: Semra Can Mamur, Omer Colak, Selma Metintas, Inci Arikan, Mehmet Kara; Ann Clin Nutr Metab 2023;15(3):88-96. Published online December 1, 2023; DOI: https://doi.org/10.15747/ACNM.2023.15.3.88

Abstract PDF: Purpose: Biomarker for cardiovascular diseases (CVDs) are important in the clinical monitoring of individuals with metabolic syndrome (MetS). The use of these biomarkers in combination may be predictive of CVDs. This study aimed to demonstrate the ability of multiple biomarkers to predict MetS, diabetes mellitus (DM), and CVDs. The use of multiple biomarkers instead of a single biomarker may be more useful in early diagnosis. We investigated the use of a multi-biomarker approach in MetS and associated diseases.
Methods: The study was performed by selecting control (n=30), MetS (n=30), MetS+DM (n=30), and MetS+CVD (n=30) groups from data of the Eskisehir Healthy Hearts Project conducted from January 2008 to October 2009 in Turkey. We recorded serum level of biomarkers, including lipid profile, liver enzyme, paraoxonase, arylesterase and arginase to find their difference among the groups.
Results: Compared to the control group, gamma-glutamyl transferase (GGT) and arginase levels increased, while paraoxonase and arylesterase activity and high-density lipoprotein–cholesterol levels were low in the patient groups (P<0.001). A negative correlation was observed between paraoxonase and arylesterase activity and MetS.
Conclusion: We believe that the combined use of biomarkers, including GGT, arginase, paraoxonase, and arylesterase, may be useful in predicting diseases such as MetS and CVDs.

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