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Risk prediction of the metabolic syndrome using TyG Index and SNPs: a 10-year longitudinal prospective cohort study

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Abstract

TyG (triglyceride and glucose) index using triglyceride and fasting blood glucose is recommended as a useful marker for insulin resistance. To clarify whether the TyG index is a marker for predicting metabolic syndrome (MetS) and to investigate the importance of single-nucleotide polymorphisms (SNPs) in MetS diagnosis. From 2001 to 2014, a longitudinal prospective cohort study of 3580 adults aged 40–70 years was conducted. The area under the receiver operating characteristic curves (AUROC) and Youden index (YI) was calculated to assess the diagnostic value. During the 14-year follow-up, 1270 subjects developed MetS. Five SNPs in four genes (BUD13 rs10790162, ZPR1 rs2075290, APOA5 rs2266788, APOA5 rs2075291, and MKL1 rs4507196) significantly correlated with susceptibility to MetS (p < 0.00005). The areas under the curve of TyG index and HOMA-IR were 0.854 (95% confidence interval [CI], 0.841–0.867) and 0.702 (95% CI, 0.684–0.721), respectively. Despite no statistical significance, AUROC and YI were increased when MetS was diagnosed using TyG index and the five SNPs. TyG index might be useful for identifying individuals at high risk of developing MetS. The combination of TyG index and SNPs showed better diagnostic accuracy than TyG index alone, indicating the potential value of novel SNPs for MetS diagnosis.

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The data used to support the findings of this study are included within the article. All data generated or analyzed during this study are included in this published article and its supplementary information.

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Funding

The authors did not receive any grant or financial support to perform this study.

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Authors and Affiliations

  1. Department of Dental Pharmacology, College of Dentistry, Dankook University, Cheonan, Republic of Korea

    Sang Wook Kang

  2. Department of Biomedical Laboratory Science, Catholic Kwandong University, Gangneung, Republic of Korea

    Su Kang Kim

  3. Management Research Institute, Kyung Hee University, Seoul, Republic of Korea

    Young Sik Kim

  4. Department of Surgery, School of Medicine, Kyung Hee University, Seoul, Republic of Korea

    Min-Su Park

Authors
  1. Sang Wook Kang
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  2. Su Kang Kim
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Contributions

SWK, SKK, YSK, and MSP designed the research; SWK and MSP contributed to review and editing; SWK, SKK, YSK, and MSP preformed the experimental work and analysis; and SWK, SKK, and MSP wrote the paper. All authors approved the manuscript.

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Correspondence to Min-Su Park.

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The authors declare that there is no conflict of interest.

Ethical approval

This study was performed in line with the principles of the Declaration of Helsinki. The present study was approved by the Institutional Review Board (IRB; KBP-2017–014) of Korea Centers for Disease Control and Prevention.

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Written informed consent was obtained from all enrolled patients.

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Kang, S.W., Kim, S.K., Kim, Y.S. et al. Risk prediction of the metabolic syndrome using TyG Index and SNPs: a 10-year longitudinal prospective cohort study. Mol Cell Biochem 478, 39–45 (2023). https://doi.org/10.1007/s11010-022-04494-1

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  • DOI: https://doi.org/10.1007/s11010-022-04494-1

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