Hsu Paul Wei-Che, Chen Yi-Rong, Sheu Wayne Huey-Herng
Institute of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan, Taiwan.
Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.
J Diabetes Investig. 2025 May;16(5):907-916. doi: 10.1111/jdi.70004. Epub 2025 Feb 13.
Current metabolic syndrome (mets) criteria often lack consideration for age and gender differences. This study introduces the mets-Z score, a novel tool designed to enhance mets assessment and improve long-term outcome predictions.
The mets-Z score was developed using principal component analysis (PCA) to weight five mets indicators-waist circumference, blood glucose, blood pressure, high-density lipoprotein (HDL) cholesterol, and triglycerides-by gender and age. Data from 188,739 Taiwan Biobank participants, stratified by gender and age groups (20-39, 40-54, 55-64, 65+ years), were analyzed. Predictive performance for type 2 diabetes mellitus onset was assessed over a 4- to 5-year follow-up.
The mets-Z score achieved superior accuracy in predicting type 2 diabetes mellitus onset, with an AUC of 0.76 in men and 0.80 in women, significantly outperforming conventional indices (P < 0.0001).
By integrating age- and gender-specific variations, the mets-Z score provides a more personalized and precise tool for assessing metabolic and diabetes risk, surpassing existing methods. The tool is available for public use at http://bioinfolab.nhri.edu.tw/metsz/, supporting broader applications in precision medicine.
当前的代谢综合征（mets）标准常常未考虑年龄和性别差异。本研究引入了mets-Z评分，这是一种旨在加强mets评估并改善长期结局预测的新工具。
mets-Z评分是使用主成分分析（PCA）开发的，用于按性别和年龄对五个mets指标——腰围、血糖、血压、高密度脂蛋白（HDL）胆固醇和甘油三酯——进行加权。分析了来自台湾生物银行188,739名参与者的数据，这些数据按性别和年龄组（20 - 39岁、40 - 54岁、55 - 64岁、65岁及以上）分层。在4至5年的随访期间评估了2型糖尿病发病的预测性能。
mets-Z评分在预测2型糖尿病发病方面具有更高的准确性，男性的曲线下面积（AUC）为0.76，女性为0.80，显著优于传统指标（P < 0.0001）。
通过整合年龄和性别特异性差异，mets-Z评分为评估代谢和糖尿病风险提供了一种更个性化、更精确的工具，超越了现有方法。该工具可在http://bioinfolab.nhri.edu.tw/metsz/上供公众使用，支持在精准医学中的更广泛应用。
