Heterogeneity in the pathogenesis of type 2 diabetes represents a challenge for disease prevention. During recent decades, the incidence of type 2 diabetes has increased or, at best, remained stable, while its prevalence and overall burden continue to increase. Type 2 diabetes is one of the most common causes of mortality, disability, and health expenditure worldwide. These results could be used to develop more precise public health interventions. Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years. Compared to the LRHB cluster, the VLR and LRLB clusters showed a lower risk, while the HRHBP, HRBF, and HRIR clusters showed a higher risk of developing type 2 diabetes. Six risk phenotypes were identified independently in both cohorts: very low-risk (VLR), low-risk low β-cell function (LRLB), low-risk high β-cell function (LRHB), high-risk high blood pressure (HRHBP), high-risk β-cell failure (HRBF), and high-risk insulin-resistant (HRIR).
The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes. The risk of type 2 diabetes was assessed using Cox proportional hazards models. Clusters were based on sex, family history of diabetes, educational attainment, fasting blood glucose and insulin levels, estimated insulin resistance and β-cell function, systolic and diastolic blood pressure, and BMI. Methodsĭata on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level.
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