Washirasaksiri Chaiwat, Borrisut Nutsakol, Lapinee Varisara, Sitasuwan Tullaya, Tinmanee Rungsima, Kositamongkol Chayanis, Ariyakunaphan Pinyapat, Tangjittipokin Watip, Plengvidhya Nattachet, Srivanichakorn Weerachai
Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
ASEAN Institute for Health Development, Mahidol University, Salaya, Thailand.
BMJ Open Diabetes Res Care. 2025 Jun 9;13(3):e004803. doi: 10.1136/bmjdrc-2024-004803.
Pre-diabetes comprises diverse subphenotypes linked to varying complications, type 2 diabetes, and mortality outcomes. This study aimed to explore these outcomes across different pre-diabetes subphenotypes.
The dataset included adults without type 2 diabetes with baseline HbA1c and fasting plasma glucose (FPG) measurements from Siriraj Hospital, Bangkok, Thailand. The participants were classified into six subphenotypes via the -means clustering method on the basis of age, body mass index, FPG, HbA1c, high-density lipoprotein cholesterol and alanine aminotransferase levels. The incidences of type 2 diabetes, long-term vascular complications and mortality were compared among subphenotypes over a median follow-up of 8.8 years, employing Kaplan-Meier curves and Cox regression analysis adjusted for sex, statin use and hypertension status.
Among the 4915 participants (mean age 60.1±10.1 years; 54.6% female), six clusters emerged: cluster 1, low risk (n=650; 13.2%); cluster 2, mild dysglycemia elderly (n=791; 16.1%); cluster 3, severe dysglycemia obese (n=1127; 22.9%); cluster 4, mild dysglycemia obese (n=963; 19.7%); cluster 5, severe dysmetabolic obese (n=337; 6.9%); and cluster 6, severe dysglycemia elderly (n=1042; 21.2%). Clusters were classified into diabetes risk subgroups: low risk (clusters 1 and 4) and high risk (clusters 3 and 5). Cluster 6 exhibited the highest risk, with significantly increased incidences of macrovascular complications (adjusted HR 2.22, 1.51-3.27) and type 2 diabetes (1.73, 1.42-2.12). In contrast, cluster 4 demonstrated the lowest risk, with significantly decreased incidences of new chronic kidney disease (0.65, 0.44-0.96), microvascular complications (0.62, 0.43-0.89) and mortality (0.25, 0.10-0.63).
Our pre-diabetes phenotyping approach effectively provides valuable insights into the risk of type 2 diabetes, vascular complications and mortality in individuals with pre-diabetes. Those with high-risk phenotypes should be prioritized for type 2 diabetes and cardiovascular interventions to mitigate risks.
糖尿病前期包含多种与不同并发症、2型糖尿病及死亡结局相关的亚表型。本研究旨在探究不同糖尿病前期亚表型的这些结局。
数据集包括来自泰国曼谷诗里拉吉医院的无2型糖尿病的成年人，其有基线糖化血红蛋白（HbA1c）和空腹血糖（FPG）测量值。根据年龄、体重指数、FPG、HbA1c、高密度脂蛋白胆固醇和丙氨酸转氨酶水平，通过K均值聚类法将参与者分为六种亚表型。在8.8年的中位随访期内，采用Kaplan-Meier曲线和经性别、他汀类药物使用及高血压状态校正的Cox回归分析，比较各亚表型中2型糖尿病、长期血管并发症和死亡的发生率。
在4915名参与者中（平均年龄60.1±10.1岁；54.6%为女性），出现了六个聚类：聚类1，低风险（n = 650；13.2%）；聚类2，轻度血糖异常老年人（n = 791；16.1%）；聚类3，重度血糖异常肥胖者（n = 1127；22.9%）；聚类4，轻度血糖异常肥胖者（n = 963；19.7%）；聚类5，重度代谢异常肥胖者（n = 337；6.9%）；聚类6，重度血糖异常老年人（n = 1042；21.2%）。聚类被分为糖尿病风险亚组：低风险（聚类1和4）和高风险（聚类3和5）。聚类6表现出最高风险，大血管并发症（校正后风险比2.22，1.51 - 3.27）和2型糖尿病（1.73，1.42 - 2.12）的发生率显著增加。相比之下，聚类4显示出最低风险，新发慢性肾脏病（0.65，0.44 - 0.96）、微血管并发症（0.62，0.43 - 0.89）和死亡（0.25，0.10 - 0.63）的发生率显著降低。
我们的糖尿病前期表型分析方法有效地为糖尿病前期个体发生2型糖尿病、血管并发症和死亡的风险提供了有价值的见解。对于具有高风险表型的个体，应优先进行2型糖尿病和心血管干预以降低风险。
