Phenotyping obesity through a two-dimensional tree structure reveals cardiometabolic heterogeneity

作者：Xiaojing Jia, Hong Lin, Yilan Ding, Chunyan Hu, Shuangyuan Wang, Mian Li, Yu Xu, Min Xu, Feiyue Huang, Feixia Shen, Xuejiang Gu, Yiming Mu, Lulu Chen, Tianshu Zeng, Lixin Shi, Qing Su, Xuefeng Yu, Yán Li, Guijun Qin, Qin Wan, Gang Chen, Xulei Tang, Zhengnan Gao, Ruying Hu, Zuojie Luo, Yingfen Qin, Li Chen, Xinguo Hou, Yanan Huo, Qiang Li, Guixia Wang, Yinfei Zhang, Chao Liu, Youmin Wang, Shengli Wu, Yujin Zhu, Tao Yang, Huacong Deng, Jiajun Zhao, Yifang Zhang, Xingkun Xu, Huapeng Wei, Jie Zheng, Tiange Wang, Zhiyun Zhao, Guang Ning, Yuhong Chen, Weiqing Wang, Yufang Bi, Jieli Lu · 发表于：Cell Reports Medicine · 年份：2025 · DOI：10.1016/j.xcrm.2025.102372 · 被引用次数：5 · 研究领域：Adipose Tissue and Metabolism、Diet and metabolism studies、Metabolomics and Mass Spectrometry Studies

Obesity, a major public health challenge, is characterized by substantial phenotypic heterogeneity. Here, we employ the discriminative dimensionality reduction tree (DDRTree) method to routine clinical data from 18,733 Chinese individuals with obesity enrolled in the nationwide China Cardiometabolic Disease and Cancer Cohort (4C) study. We identify five distinct metabolic phenotypes, among which the phenotype characterized by hyperglycemia and insulin resistance exhibits a higher risk of glycemic deterioration, while the phenotype characterized by hypertension and dyslipidemia demonstrates an elevated risk of microvascular and macrovascular diseases. These findings are validated in an independent prospective cohort. Additionally, we reveal distinctive metabolomic features that contribute to the heterogeneity of obesity in the 4C study. To translate our findings into practice, we develop a user-friendly online tool to assess event risks in the obese population. Overall, our analysis illustrates the underlying phenotypic variations influencing subsequent obesity-related outcomes, emphasizing the importance of precision medicine in obesity management.