Characterization of data-driven clusters in diabetes-free adults and their utility for risk stratification of type 2 diabetes

BACKGROUND

The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. 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.

METHODS

Data on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. 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. The risk of type 2 diabetes was assessed using Cox proportional hazards models. The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes.

RESULTS

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). 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. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years.

CONCLUSIONS

Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.

The SLC16A11 risk haplotype is associated with decreased insulin action, higher transaminases and large-size adipocytes

Objective A haplotype at chromosome 17p13 that reduces expression and function of the solute carrier transporter SLC16A11 is associated with increased risk for type 2 diabetes in Mexicans. We aim to investigate the detailed metabolic profile of SLC16A11 risk haplotype carriers to identify potential physiological mechanisms explaining the increased type 2 diabetes risk. Design Cross-sectional study. Methods We evaluated carriers (n = 72) and non-carriers (n = 75) of the SLC16A11 risk haplotype, with or without type 2 diabetes. An independent sample of 1069 subjects was used to replicate biochemical findings. The evaluation included euglycemic-hyperinsulinemic clamp, frequently sampled intravenous glucose tolerance test (FSIVGTT), dual-energy X-ray absorptiometry (DXA), MRI and spectroscopy and subcutaneous abdominal adipose tissue biopsies. Results Fat-free mass (FFM)-adjusted M value was lower in carriers of the SLC16A11 risk haplotype after adjusting for age and type 2 diabetes status (β = -0.164, P = 0.04). Subjects with type 2 diabetes and the risk haplotype demonstrated an increase of 8.76 U/L in alanine aminotransferase (ALT) (P = 0.02) and of 7.34 U/L in gamma-glutamyltransferase (GGT) (P = 0.05) compared with non-carriers and after adjusting for gender, age and ancestry. Among women with the risk haplotype and normal BMI, the adipocyte size was higher (P < 0.001). Conclusions Individuals carrying the SLC16A11 risk haplotype exhibited decreased insulin action. Higher serum ALT and GGT levels were found in carriers with type 2 diabetes, and larger adipocytes in subcutaneous fat in the size distribution in carrier women with normal weight.