Ito Ryoma, Mizushiri Satoru, Nishiya Yuki, Ono Shoma, Tamura Ayumi, Hamaura Kiho, Terada Akihide, Tanabe Jutaro, Yanagimachi Miyuki, Wai Kyi Mar, Kudo Yutaro, Ihara Kazushige, Takahashi Yoshiko, Daimon Makoto
Department of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Department of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
J Clin Med. 2023 Jan 19;12(3):810. doi: 10.3390/jcm12030810.
Recent attempts to classify adult-onset diabetes using only six diabetes-related variables (GAD antibody, age at diagnosis, BMI, HbA1c, and homeostatic model assessment 2 estimates of b-cell function and insulin resistance (HOMA2-B and HOMA2-IR)) showed that diabetes can be classified into five clusters, of which four correspond to type 2 diabetes (T2DM). Here, we classified nondiabetic individuals to identify risk clusters for incident T2DM to facilitate the refinement of prevention strategies. Of the 1167 participants in the population-based Iwaki Health Promotion Project in 2014 (baseline), 868 nondiabetic individuals who attended at least once during 2015-2019 were included in a prospective study. A hierarchical cluster analysis was performed using four variables (BMI, HbA1c, and HOMA2 indices). Of the four clusters identified, cluster 1 (n = 103), labeled as "obese insulin resistant with sufficient compensatory insulin secretion", and cluster 2 (n = 136), labeled as "low insulin secretion", were found to be at risk of diabetes during the 5-year follow-up period: the multiple factor-adjusted HRs for clusters 1 and 2 were 14.7 and 53.1, respectively. Further, individuals in clusters 1and 2 could be accurately identified: the area under the ROC curves for clusters 1and 2 were 0.997 and 0.983, respectively. The risk of diabetes could be better assessed on the basis of the cluster that an individual belongs to.
最近尝试仅使用六个与糖尿病相关的变量（谷氨酸脱羧酶抗体、诊断时年龄、体重指数、糖化血红蛋白以及β细胞功能和胰岛素抵抗的稳态模型评估2估计值（HOMA2-B和HOMA2-IR））对成人发病型糖尿病进行分类，结果表明糖尿病可分为五个聚类，其中四个对应2型糖尿病（T2DM）。在此，我们对非糖尿病个体进行分类以确定发生T2DM的风险聚类，从而促进预防策略的完善。在2014年基于人群的磐城健康促进项目（基线）的1167名参与者中，868名在2015 - 2019年期间至少参加过一次检查的非糖尿病个体被纳入一项前瞻性研究。使用四个变量（体重指数、糖化血红蛋白和HOMA2指数）进行分层聚类分析。在确定的四个聚类中，聚类1（n = 103），标记为“肥胖且胰岛素抵抗但有足够代偿性胰岛素分泌”，以及聚类2（n = 136），标记为“胰岛素分泌低”，在5年随访期内被发现有患糖尿病的风险：聚类1和聚类2的多因素调整后风险比分别为14.7和53.1。此外，可以准确识别聚类1和聚类2中的个体：聚类1和聚类2的受试者工作特征曲线下面积分别为0.997和0.983。根据个体所属的聚类可以更好地评估患糖尿病的风险。
