ArticleDiabetologia2026
Heterogeneity of diabetes and disease progression with a tree-like representation: findings from the China Cardiometabolic Disease and Cancer Cohort (4C) study.
Article in Diabetologia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Phenotypic Heterogeneity of Obesity and Short-Term Cardiometabolic Risk Factors Transitions: A Population-Based Cohort Study.Diabetes, obesity & metabolism · 2026Article
- Deficit accumulation frailty and risk of incident chronic kidney disease: a prospective analysis of the UK biobank and CHARLS cohorts.International urology and nephrology · 2026Article
- Age-specific effects of hemoglobin A1c, blood pressure, and cholesterol levels on incident cardiovascular diseases among adults with diabetes in China: a 10-year prospective cohort study.Life metabolism · 2026Article
- Age-stratified associations of glycemia, blood pressure, and cholesterol with mortality in diabetes: A prospective cohort study.BMC medicine · 2026Article
- Phenotyping obesity through a two-dimensional tree structure reveals cardiometabolic heterogeneity.Cell reports. Medicine · 2025Article
- From visualization to prediction: Dissecting metabolic heterogeneity with DDRTree.Cell reports. Medicine · 2025Article
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Abstract
aims/hypothesisDiabetes heterogeneity has been modelled as a continuum in European populations, but its phenotypes and long-term comorbidity risks remain unclear in Chinese individuals. This study aimed to identify distinct phenotypes and evaluate their links to future cardiometabolic risks in a large Chinese cohort.
methodsThe discriminative dimensionality reduction with trees (DDRTree) algorithm was used to develop a tree structure based on nine clinical variables. Cox proportional hazard models or logistic regression models were used to analyse probabilities of diabetes-related outcomes.
resultsThis study included 19,612 individuals with newly diagnosed diabetes (36.8% male, mean age 59.01 years [SD 8.63]) from the China Cardiometabolic Disease and Cancer Cohort (4C) study. All nine clinical variables used for establishing DDRTree models were gradient distributed across the tree. By overlaying risks of diabetes-related outcomes, we show how these risks differ by participant phenotype. Participants characterised by hyperglycaemia, obesity and dyslipidaemia showed elevated risks of insulin initiation, hypoglycaemia and chronic kidney diseases, while those with hypertension and high creatinine, total cholesterol and alanine aminotransferase levels were associated with a higher risk of CVD. Notably, social determinants and lifestyle factors further contributed to the observed heterogeneity. CONCLUSIONS/
interpretationThese findings characterise the heterogeneity of diabetes phenotypes and complication risks in the Chinese population, suggesting potential implications for personalised diabetes care. Given the observed phenotypic differences, management strategies should consider population-specific characteristics.
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