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

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.

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Publication Details

Journal
Cell Reports Medicine
Published
2025-09-25
DOI
https://doi.org/10.1016/j.xcrm.2025.102372
Citations
1
Primary Topic
Adipose Tissue and Metabolism
Type
article
Field-Weighted Citation Impact
1.16
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article

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

Yufang Bi, Jie Zheng, Yilan Ding, Jiajun Zhao et al.
1 citations
Cell Reports Medicine
Adipose Tissue and Metabolism
1.16
article

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

Yufang Bi, Jie Zheng, Yilan Ding, Jiajun Zhao, Yiming Mu, Jieli Lu, Zuojie Luo, Xuejiang Gu, Xuefeng Yu, Lixin Shi, Xulei Tang, Xinguo Hou, Zhang Yi-fang, Zhiyun Zhao, Guijun Qin, Tiange Wang, Yu Xu, Guang Ning, Shuangyuan Wang, Shengli Wu, Feixia Shen, Ruying Hu, Chunyan 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, Yujin Zhu, Yanan Huo, Huacong Deng, Yingfen Qin, Yuhong Chen, Feiyue Huang, Xiaojing Jia, Yinfei Zhang
article en
1 citations

Abstract

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.

Cell Reports MedicineVol. 6(11)
Fujian Medical University (CN), Nanchang University (CN), Shandong University (CN), Harbin Medical University (CN), Sun Yat-sen University (CN), Guangxi Medical University (CN), Shanghai Jiao Tong 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)
Openalex Percentile: Top 18%
Adipose Tissue and Metabolism
1.16
DOIOpen Access PDFOpenAlex
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