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Identification of subtypes of type 2 diabetes in the Chinese population and their distinct complication risk profiles
Qiu Xiao1, Chengjun Zhang1,2, Yanfeng Jiang3,4
1School of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.
Aims:
To identify and validate subgroups of type 2 diabetes in Chinese populations using clustering analysis and assess their complication risks.
Materials And Methods:
Data from 5653 type 2 diabetes patients in the Shanghai Suburban Adult Cohort and Biobank (SSACB) and 6384 in the Southwest China Diabetic Chronic Complications Study were integrated. Using body mass index, fasting blood glucose, age at diabetes diagnosis, and triglycerides to high-density lipoprotein cholesterol ratio, k-means clustering was performed by sex in SSACB and validated in Southwest China Diabetic Chronic Complications Study. Cox and logistic regression models compared complication risks.
Results:
Five type 2 diabetes subgroups were identified: Hyperglycaemic Diabetes (HGD), Obesity-Related Diabetes (ORD), Young-Onset Diabetes (YOD), Insulin Resistance Diabetes (IRD), and Elderly-Onset Diabetes (EOD). Verification in an external validation cohort confirmed the robustness and reproducibility of the identified subgroups. In SSACB, distinct subgroup-specific complication risks were observed. Specifically, the HGD subgroup showed the highest risks for stroke (HR = 1.37, 95% CI: 1.10-1.70), peripheral vascular disease (HR = 1.66, 95% CI: 1.36-2.03), retinopathy (HR = 3.53, 95% CI: 2.53-4.90), peripheral neuropathy (HR = 1.89, 95% CI: 1.56-2.30), and nephropathy (HR = 1.81, 95% CI: 1.41-2.34). The IRD subgroup had the highest risk for coronary heart disease (HR = 1.20, 95% CI: 1.01-1.43). Similar risk patterns were observed in the validation cohort.
Conclusions:
We identified five clinically distinct type 2 diabetes subgroups with differential complication risks in the Chinese population, providing a basis for precision diabetes management.
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