Elucidating the heterogeneity of prediabetes through subphenotyping with a two-dimensional tree structure

Prediabetes, an intermediate stage of developing diabetes, exhibits considerable phenotypic heterogeneity. Here, we apply the Discriminative Dimensionality Reduction Tree (DDRTree) algorithm to explore prediabetes heterogeneity in 55,777 participants from the China Cardiometabolic Disease and Cancer Cohort (4C) study. Based on 12 clinically available variables, we identify four distinct phenotypes and observe differential risks of type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), and cardiovascular disease (CVD). Phenotype 4, characterized by hyperglycemia, insulin resistance, obesity, elevated triglycerides, and liver enzymes, has the highest T2DM risk, while phenotype 3, predominantly driven by obesity, insulin resistance, hyperglycemia, and dyslipidemia, has the highest CKD risk. Phenotypes 3 and 4 show higher CVD risk, with distinct distributions of CVD subtypes. These findings are validated in the external cohort SN_2009-2021, and a user-friendly online tool is provided for individual risk prediction. Overall, our study elucidates the intricate dynamics of prediabetes progression, aiding in personalized management for prediabetes care.

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Journal
Cell Reports Medicine
Published
2025-07-01
DOI
https://doi.org/10.1016/j.xcrm.2025.102212
Citations
2
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
3.63

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article

Elucidating the heterogeneity of prediabetes through subphenotyping with a two-dimensional tree structure

Yufang Bi, Jie Zheng, Yilan Ding, Jiajun Zhao et al.
2 citations
Cell Reports Medicine
Genetic Associations and Epidemiology
3.63
article

Elucidating the heterogeneity of prediabetes through subphenotyping with a two-dimensional tree structure

Yufang Bi, Jie Zheng, Yilan Ding, Jiajun Zhao, Yiming Mu, Jieli Lu, Zuojie Luo, Xuejiang Gu, Xuefeng Yu, Lixin Shi, Xulei Tang, Xinguo Hou, Zhiyun Zhao, Guijun Qin, Tiange Wang, Yu Xu, Guang Ning, Shuangyuan Wang, Shengli Wu, Feixia Shen, Ruying Hu, Xingkun Xu, Huapeng Wei, Youmin Wang, Tianshu Zeng, Guixia Wang, Qing Su, Zhengnan Gao, Yán Li, Chao Liu, Weiqing Wang, Li Chen, Gang Chen, Lulu Chen, Qiang Li, Qin Wan, Tao Yang, Mian Li, Min Xu, Hong Lin, Yanan Huo, Huacong Deng, Yingfen Qin, Yuhong Chen, Feiyue Huang, Xiaojing Jia, Yinfei Zhang
article en
2 citations

Abstract

Prediabetes, an intermediate stage of developing diabetes, exhibits considerable phenotypic heterogeneity. Here, we apply the Discriminative Dimensionality Reduction Tree (DDRTree) algorithm to explore prediabetes heterogeneity in 55,777 participants from the China Cardiometabolic Disease and Cancer Cohort (4C) study. Based on 12 clinically available variables, we identify four distinct phenotypes and observe differential risks of type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), and cardiovascular disease (CVD). Phenotype 4, characterized by hyperglycemia, insulin resistance, obesity, elevated triglycerides, and liver enzymes, has the highest T2DM risk, while phenotype 3, predominantly driven by obesity, insulin resistance, hyperglycemia, and dyslipidemia, has the highest CKD risk. Phenotypes 3 and 4 show higher CVD risk, with distinct distributions of CVD subtypes. These findings are validated in the external cohort SN_2009-2021, and a user-friendly online tool is provided for individual risk prediction. Overall, our study elucidates the intricate dynamics of prediabetes progression, aiding in personalized management for prediabetes care.

Cell Reports MedicineVol. 6(7)
Fujian Medical University (CN), Nanchang University (CN), Shandong University (CN), Harbin Medical University (CN), Sun Yat-sen University (CN), Guangxi Medical University (CN), Jilin University (CN), Anhui Medical University (CN), Wenzhou Medical University (CN), XinHua Hospital (CN), Ruijin Hospital (CN), First Affiliated Hospital of Wenzhou Medical University (CN), Affiliated Hospital of Southwest Medical University (CN), Jiading District Central Hospital (CN), Sun Yat-sen Memorial Hospital (CN), Dalian Municipal Central Hospital (CN), Jiangxi Provincial People's Hospital (CN), Shandong Provincial Hospital (CN), First Hospital of Jilin University (CN), First Affiliated Hospital of GuangXi Medical University (CN), Wuhan Union Hospital (CN), The Affiliated Yongchuan Hospital of Chongqing Medical University (CN), Second Affiliated Hospital of Harbin Medical University (CN), Zhejiang Center for Disease Control and Prevention (CN), First Affiliated Hospital of Anhui Medical University (CN), Fujian Provincial Hospital (CN), Karamay Central Hospital (CN), Jiangsu Province Hospital (CN), First Affiliated Hospital of Zhengzhou University (CN), Tongji Hospital (CN), Chinese People's Liberation Army (CN), Qilu Hospital of Shandong University (CN), First Hospital of Lanzhou University (CN), Huazhong University of Science and Technology (CN), Lanzhou University (CN), Nanjing Medical University (CN), Chongqing Medical University (CN)
Shanghai Municipal Health Commission, National Natural Science Foundation of China, Ministry of Science and Technology of the People's Republic of China, Science and Technology Commission of Shanghai Municipality, National Science and Technology Major Project
Zero hunger
Openalex Percentile: Top 7%
Genetic Associations and Epidemiology
3.63
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