School of Medicine, Nankai University, Tianjin, China.
Department of Endocrinology, the First medical center of PLA General Hospital, Beijing, China.
J Diabetes. 2024 Aug;16(8):e13596. doi: 10.1111/1753-0407.13596.
Novel diabetes phenotypes were proposed by the Europeans through cluster analysis, but Chinese community diabetes populations might exhibit different characteristics. This study aims to explore the clinical characteristics of novel diabetes subgroups under data-driven analysis in Chinese community diabetes populations.
We used K-means cluster analysis in 6369 newly diagnosed diabetic patients from eight centers of the REACTION (Risk Evaluation of cAncers in Chinese diabeTic Individuals) study. The cluster analysis was performed based on age, body mass index, glycosylated hemoglobin, homeostatic modeled insulin resistance index, and homeostatic modeled pancreatic β-cell functionality index. The clinical features were evaluated with the analysis of variance (ANOVA) and chi-square test. Logistic regression analysis was done to compare chronic kidney disease and cardiovascular disease risks between subgroups.
Overall, 2063 (32.39%), 658 (10.33%), 1769 (27.78%), and 1879 (29.50%) populations were assigned to severe obesity-related and insulin-resistant diabetes (SOIRD), severe insulin-deficient diabetes (SIDD), mild age-associated diabetes mellitus (MARD), and mild insulin-deficient diabetes (MIDD) subgroups, respectively. Individuals in the MIDD subgroup had a low risk burden equivalent to prediabetes, but with reduced insulin secretion. Individuals in the SOIRD subgroup were obese, had insulin resistance, and a high prevalence of fatty liver, tumors, family history of diabetes, and tumors. Individuals in the SIDD subgroup had severe insulin deficiency, the poorest glycemic control, and the highest prevalence of dyslipidemia and diabetic nephropathy. Individuals in MARD subgroup were the oldest, had moderate metabolic dysregulation and the highest risk of cardiovascular disease.
The data-driven approach to differentiating the status of new-onset diabetes in the Chinese community was feasible. Patients in different clusters presented different characteristics and risks of complications.
欧洲人通过聚类分析提出了新型糖尿病表型，但中国社区糖尿病人群可能表现出不同的特征。本研究旨在通过数据驱动分析探讨中国社区糖尿病人群中新发糖尿病亚组的临床特征。
我们使用来自 REACTION（中国糖尿病个体癌症风险评估）研究的 8 个中心的 6369 例新诊断糖尿病患者进行 K-均值聚类分析。聚类分析基于年龄、体重指数、糖化血红蛋白、稳态模型胰岛素抵抗指数和稳态模型胰岛β细胞功能指数。采用方差分析（ANOVA）和卡方检验对临床特征进行评估。进行逻辑回归分析以比较亚组之间慢性肾脏病和心血管疾病的风险。
总体而言，2063（32.39%）、658（10.33%）、1769（27.78%）和 1879（29.50%）人群分别被分配到严重肥胖相关和胰岛素抵抗性糖尿病（SOIRD）、严重胰岛素缺乏性糖尿病（SIDD）、轻度年龄相关性糖尿病（MARD）和轻度胰岛素缺乏性糖尿病（MIDD）亚组。MIDD 亚组的个体风险负担相当于糖尿病前期，但胰岛素分泌减少。SOIRD 亚组的个体肥胖、存在胰岛素抵抗以及脂肪肝、肿瘤、糖尿病家族史和肿瘤的患病率较高。SIDD 亚组的个体存在严重的胰岛素缺乏、血糖控制最差以及血脂异常和糖尿病肾病的患病率最高。MARD 亚组的个体年龄最大、代谢失调最严重且心血管疾病风险最高。
通过数据驱动的方法对中国社区新发糖尿病的状态进行分类是可行的。不同亚组的患者表现出不同的特征和并发症风险。
